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The course of depressive symptoms in unipolar depressive disorder during electroconvulsive therapy: A latent class analysis
Journal of Affective Disorders 124 (2010) 141–147
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Journal of Affective Disorders j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j a d
Research report
The course of depressive symptoms in unipolar depressive disorder during electroconvulsive therapy: A latent class analysis S. Cinar a,⁎, R.C. Oude Voshaar a,b, J.G.E. Janzing a, T.K. Birkenhäger c, J.K. Buitelaar a, W.W. van den Broek c a
Radboud University Nijmegen Medical Centre, Nijmegen Centre for Evidence-Based Practice, Department of Psychiatry, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands b Forum GGZ Nijmegen, Department of Old Age Psychiatry, Nijmegen, The Netherlands c Department of Psychiatry, Erasmus Medical Centre, Rotterdam, The Netherlands
a r t i c l e
i n f o
Article history: Received 23 August 2009 Received in revised form 1 November 2009 Accepted 1 November 2009 Available online 20 November 2009 Keywords: Electroconvulsive therapy ECT Speed of response Major depression
a b s t r a c t Background: Research examining the course of depressive symptoms during electroconvulsive therapy (ECT) is relatively scarce. Objective: To classify patients according to the course of their depressive symptoms while receiving ECT. Methods: The sample consisted of 156 consecutive patients receiving ECT for unipolar depressive disorder. Depressive symptoms were measured weekly with the Montgomery– Asberg Depression Rating Scale. Latent class analysis was applied to identify distinct trajectories of symptom improvement. Results: We identified five classes of different trajectories (improvement rates) of depressive symptoms, i.e. fast improvement (39 patients), intermediate improvement (47 patients), slow improvement (30 patients), slow improvement with delayed onset (18 patients), and finally a trajectory with no improvement (20 patients). The course of depressive symptoms at the end of the treatment within the trajectories of intermediate improvement, slow improvement and slow improvement with delayed onset, was still improving and did not achieve a plateau. Conclusion: The different courses of depressive symptoms during ECT probably contribute to mixed results of prediction studies of ECT outcome. Data suggest that for a large group of patients no optimal clinical endpoint can be identified, other than full remission or no improvement at all, to discontinue ECT. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Unipolar major depression is a common and disabling psychiatric disorder leading to serious disruptions in all major areas of functioning (Kessler et al., 2003). Electroconvulsive therapy (ECT) is considered to be the most effective, short-term biological treatment for major depression. Meta-analysis of 1144 patients in 18 trials showed ECT to be superior to
⁎ Corresponding author. Radboud University Nijmegen Medical Centre, Department of Psychiatry (961), PO Box 9101, 6500 HB Nijmegen, The Netherlands. Tel.: +31 24 3613489; fax: +31 24 3540561. E-mail address: [email protected] (S. Cinar). 0165-0327/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jad.2009.11.002
pharmacotherapy with an effect size of 0.80 (UK ECT Review group, 2003). The Consortium for Research in ECT (CORE) (Husain et al., 2004) reported a 75% remission rate among 217 patients in the United States, only 5% of whom required more than 12 treatment sessions. In Europe, remission rates are estimated around 50% with an average number of ECT sessions around 14 (Birkenhäger et al., 2003; Van den Broek et al., 2004; Vreede et al., 2005). This might be due to confounding by indication, as in European countries the indication for ECT is more strictly reserved for a higher level of previous pharmacotherapy failure. In some US studies, the latter was associated with poorer response to ECT (Dombrovski et al., 2005; Tsuchiyama et al., 2005), although these results have not been
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replicated by other research groups (Heijnen et al., 2008; Kho et al., 2004; Pluijms et al., 2002; Rasmussen et al., 2007; Van den Broek et al., 2004). Decreased response to ECT might be due to long episode duration before starting ECT (Pluijms et al., 2002). Although ECT is widely used for treatment of major depression in clinical practice, empirical evidence determining the optimal number of sessions for an ECT course is still lacking. A recent audit of electroconvulsive therapy practices in Belgium shows that ECT utilization rates and number of treatment sessions widely varies between clinics (Sienaert et al., 2006). Most guidelines, however, advocate relatively short treatment courses, comprising 6 to 12 treatment sessions on average (American Psychiatric Association, 2001; National Institute for Clinical Excellence, 2003; NYS Office of Mental Health, 2007). The Health Authorities in British Columbia even recommend a second opinion if patients need more than 15 ECT treatments in an index course of treatment (Mental Health Evaluation and Community Consultation Unit, 2000). There is no advice available for patients with a partial response, however. The Dutch guidelines (Van den Broek et al., 2000) do not mention a standard number of treatment sessions, but advise to treat a patient until one of the following endpoints is reached: 1) full remission, 2) no response after ten bilateral ECT sessions with adequate seizures, and 3) no further improvement during the last four ECT sessions using bilateral electrode placement, after at least ten ECT sessions. Studies describing the course of depressive symptoms during ECT treatment are relatively scarce. In the CORE study, 54% of the patients showed a response (N50% decrease of HAMD score) after only three ECT sessions. In order to investigate whether a threshold of symptom reduction after various numbers of ECT sessions would predict response or remission, subsequent analyses were performed, but did not yield clinically relevant results (Husain et al., 2004). Other studies focused on the speed of response to ECT. They showed associations between a fast response and younger age (Rich et al., 1984; Shapira and Lerer, 1999), psychotic features (Kho et al., 2003; Petrides et al., 2001) and high depression severity at baseline (Kho et al., 2004). In addition, a rapid response was associated with a three times weekly ECT schedule (Lerer et al., 1995) and a high seizure energy index (Kho et al., 2004). Applying latent class analysis (LCA) to longitudinal datasets allows to identify specific subgroups (called trajectories) empirically, based on changing symptom scores. Nevertheless, LCA has never been utilized to investigate the course of depressive symptoms during ECT. In the present study, we set out to classify depressed patients receiving ECT according to their course of depressive symptoms during treatment. The aim was to establish whether there were distinct trajectories of depressive symptoms during ECT treatment and, secondly, to describe clinical and ECT variables associated with these different trajectories.
in the Netherlands with a long history of ECT practice. Patients were included in the study if they met the DSM-IV criteria for major depressive disorder based on clinical observation during a routinely drug-free period of one week, and confirmed by the Mini International Neuropsychiatric Interview version 5 (Sheehan et al., 1998). Exclusion criteria were bipolar disorder, schizoaffective disorder, primary psychotic disorder, neurological illness and life-threatening medical illness. For patients who received more than one course of ECT during the study period, only their first course was analyzed. 2.2. ECT procedures ECT was administered twice weekly using a brief pulse constant current apparatus (Thymatron System IV, Somatics, IL, USA). Seizure threshold was determined by empirical stimulus titration during the first session. It was defined as the stimulus dosage that elicits a seizure of at least 25 s according to the cuff method. If the starting stimulus dose failed to elicit a seizure of at least 25 s duration as measured by the cuff method, stimulus charge was increased according to the titration schedule and the patient was restimulated after 30 s. For the second treatment, the stimulus dosage was set at 1.5 times the initial seizure threshold for bilateral treatment (bitemporal) and at 6 times the initial seizure threshold for unilateral treatment. During the course of ECT, stimulus dosage settings were adjusted upward in order to maintain seizure duration of at least 25 s as measured by the cuff method. During the ECT sessions, anesthesia was achieved with intravenous administration of metoclopramide 10 mg, glycopyrrolate 0.002– 0.003 mg/kg, a bolus injection of alfentanil 0.010–0.015 mg/ kg and etomidate 0.2–0.3 mg/kg or propofol followed by succinylcholine 0.5–1.0 mg/kg for muscle relaxation. Patients were withdrawn from all psychotropic medication at least 1 week before ECT and were maintained drugfree during the course of ECT in all but 5 cases with severe anxiety or agitation. These patients were treated with haloperidol 1 to 5 mg. 2.3. Primary outcome variable Clinical evaluation of depressive symptoms was performed weekly using the Montgomery–Asberg Depression Rating Scale (MADRS) (Williams and Kobak, 2008). The main outcome variable was the course of MADRS scores. In addition, the scores on the 17-item version of the Hamilton Rating Scale for Depression (HAM-D17) (Hamilton, 1960) were obtained 1 to 3 days prior to ECT and 1 to 3 days after treatment termination. Remission was defined as a HAMD17 score of ≤7. Treatment failure or non-remission was defined as a HAM-D17 score of ≥8. Response was defined as a HAM-D17 end score improvement of at least 50% compared to baseline.
2. Methods 2.4. Clinical variables 2.1. Design and population A clinical sample was of inpatients suffering from unipolar major depressive disorder who received ECT treatment between September 2000 and November 2007 at the depression unit of Erasmus Medical Centre, a tertiary, academic centre
In addition to demographic variables (age, gender), the following disease-related variables were assessed: history of prior depressive episodes, pharmacotherapy treatment failure, ECT treatment in history, the presence of psychotic features and the presence of a previously diagnosed co-
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morbid personality disorder. The presence of psychotic features (dichotomized) was established using DSM-IV criteria for depressive disorder with psychotic features, and assessed within the first week of hospitalization (see above). Pharmacotherapy treatment failure was defined as the use of at least two courses of antidepressants of different classes during a sufficiently long period of time (at least 4 weeks) using a therapeutic dosage (modern antidepressants) or an adequate blood level (tricyclic agents). It was included as a dichotomized variable as well. History of prior ECT and previous pharmacotherapy treatment failure was only recorded for patients included after 2002. 2.5. Data analysis A latent class analysis (LCA) was conducted using MPLUS (Muthén and Muthén, 2006). The assumption behind this LCA is that there exist a certain number of distinct trajectories of depressive symptoms according to which subjects can be grouped. These trajectories are known as latent classes. They are based on the reaction to ECT treatment in terms of a time profile, with each subject belonging to one class. Latent class modeling aims to obtain the smallest number of classes accounting for all associations between the variables, in this case the MADRS scores. This implies local independence within classes, as the probability of a certain level of depressive symptoms is independent of the level of symptoms at any other time of measurement. The posterior probability of belonging to a class can be obtained for each person, with subjects allocated to the class for which this probability is the largest. Class-specific probabilities, given membership of that class, allow profiles of reaction to ECT treatment to be developed for subjects in each class. Latent class models are fitted successively, starting with a one-class model (whereby it is assumed that all subjects have the same trajectory of depressive symptoms during ECT) and then adding another class for each successive model. The number of classes with the lowest BIC value (goodness of fit statistic) (Nylund et al., 2007) was chosen on the prerequisite of sufficiently large classes (defined as at least 10% of the sample). In order to compare characteristics between classes, we performed Chi-square tests, ANOVA and Kruskal Wallis tests using SPSS for Windows (version 16.0 ). Post-hoc tests were computed with Chi-square tests, Mann–Whitney U tests or Tukey post-hoc tests in case an ANOVA procedure was applied. Statistical significance was defined as p b .05. We did not correct for multiple comparisons, as the post-hoc comparison between classes was merely explorative. 3. Results 3.1. Patient recruitment Within the study period, 210 patients received 221 courses of ECT (9 patients received a second course and 1 a third course; these 2nd and 3rd courses were excluded from further analyses). A total of 54 patients met one of the exclusion criteria (bipolar disorder, n = 19; psychotic disorder, n = 20; catatonia, n = 1; other condition, n = 8; unknown diagnosis, n = 6), leaving a final study sample of 156 patients (74%)
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suffering from a unipolar depressive disorder. Initially, 78/156 (50%) patients were treated with right unilateral ECT. Of those, 17/78 (22%) were crossed over to bilateral ECT because of insufficient response after 3 to 11 treatments. The other 78 patients received bilateral ECT from the start, because of the severity of the illness according to clinical observation or prior response to bilateral ECT. Classifying patients that were crossed over from unilateral to bilateral ECT as treatment failures for unilateral ECT, we found similar success rates for patients initially starting with unilateral compared to those initially starting with bilateral ECT (43/78 (55%) versus 42/78 (55%) remission, χ2 = 0.00, df = 1, p = 1.00). The average age of the study sample was 64.3 years (range 21–89) and the male-female ratio 1:3 (23%:77%). The mean severity of depressive symptoms was 38.1 (SD 9.0) as measured with the MADRS and 27.6 (SD 7.2) as measured with the HAM-D17. Psychotic features were present in 73/156 (47%) of the patients and 51/88 (58%) received ECT due to pharmacotherapy treatment failure. A total of 108/156 patients (69%) had a history of previous depressive episodes and 25/88 (28%) patients had received a prior ECT course. The median number of ECT sessions in the current episode was 12 (range 1–36). As presented in Table 1, the fit statistics indicated that the BIC-values decreased for every additional LCA class. However, in light of the smaller size of classes starting from the sixsolution and the fact that the additional classes could be considered subsets of previous identified trajectories, we chose the 5-class solution as best. This solution provided classes with sufficient subjects for subsequent analyses with classes above 10%. One patient was excluded from these analyses because of missing MADRS scores. Another patient was excluded due to an atypical course during ECT, that is, extremely fluctuating MADRS scores. The LCA revealed five latent classes representing different profiles of depressive symptoms changing over time after ECT (called trajectories; see Fig. 1). Trajectory I included 39 patients (25%) who showed immediate improvement of depressive symptoms and could be labeled ‘fast improvement’. Trajectory II comprised 47 patients (31%) and was labeled ‘intermediate improvement’ as the course of improvement of depressive symptoms was intermediate between trajectory I and III. Trajectory III consisted of 30 (20%) patients with a very gradual symptom improvement and could be labeled ‘slow improvement’. Trajectory IV consisted of 18 patients (12%) and was marked by initial slight deterioration before responding and was labeled ‘slow improvement with delayed onset’. Finally, the fifth class consisted of 20 patients (13%) with virtually no response to treatment and was labeled ‘no improvement’. Table 2 presents the average outcome, demographics, and psychiatric and ECT characteristics for patients per trajectory (class). The five trajectories did not differ with respect to their baseline depression severity, number of depressive episodes, or presence of psychotic features. As expected, overall differences between the five trajectories with subsequent significant post-hoc tests were found for treatment outcome (in order of decreasing remission rates for trajectory labeled ‘fast improvement’, ‘intermediate improvement’, ‘slow improvement’, ‘slow improvement with delayed onset’, and ‘no improvement’), pharmacotherapy treatment failure (less
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Table 1 Fit statistics for latent class analysis identifying classes of depressive symptoms during ECT: Bayesian information criteria values. Class
1
2
3
4
5
6
7
8
9
10
BIC value
11217
8870
8126
7863
7687
7572
7521
7446
7423
7407
common in the trajectories ‘fast improvement’ and ‘no improvement’) and a co-morbid personality disorder (more likely in trajectory ‘no improvement’). Patients in the trajectory labeled ‘no improvement’ more often received bilateral ECT than patients in the other trajectories. 4. Discussion Our sample of patients receiving ECT for unipolar major depressive disorder could be described as a severely depressed population of inpatients: the mean HAM-D17 score was 27.6 points, 47% had psychotic features, and 58% had a significant level of pharmacotherapy treatment failure. The proportion of patients in our sample with psychotic features appears to be high. This may be explained by the selection of depressed inpatients, about 33% of depressed inpatients at our unit has psychotic features (Birkenhäger et al., 2008). Furthermore, since in The Netherlands ECT is a fairly exceptional treatment administered almost exclusively to severely depressed patients with melancholic features, the selection of patients for ECT may well have increased the proportion of patients with “psychotic features”. After delivering an average number of 12 ECT sessions, the remission rate was 56%, similar to previous European ECT studies (Birkenhäger et al., 2003; Van den Broek et al., 2004; Vreede et al., 2005). Within this patient population, we identified five trajectories of depressive symptoms during ECT, using latent class analysis. Based on decreasing, thus improving, BIC values, a higher number of trajectories (up to 10) could be identified. These solutions however, were not suitable, as the low number of subjects within each additional
trajectory would not allow meaningful subsequent analyses. Moreover, only more subclasses with almost identical courses of depressive symptoms would have been created, as the additional classes were created by splitting up trajectories with a gradual or slow response that were previously identified. Within trajectory I (39 patients), called ‘fast improvement’, 84% of the patients remitted and 94% responded to ECT, receiving 7 ECT sessions on average. The proportion of successfully treated patients gradually decreased for the trajectories ‘intermediate improvement’ (47 patients, 63% remitted, 91% responded) and ‘slow improvement’ (30 patients, 55% remitted, 81% responded) after an average number of 11 and 14 sessions, respectively. The other two trajectories included smaller numbers of patients. The trajectory of ‘slow improvement with a delayed onset’ included 18 patients and had a less favorable outcome; the remission rate was 33% and the response rate was 65%, after 16 sessions on average. The trajectory ‘no improvement’ included 20 patients of whom only 1 patient remitted and 2 responded to ECT. The average number of sessions was 15. The only patient who remitted in this ‘no improvement’ trajectory, demonstrated a highly fluctuating depression severity score during the last four weeks of ECT. Therefore, a stable remission was unlikely, even though our remission criterium (HAM-D17 end score of ≤7) was met. Patients in this ‘no improvement’ trajectory were significantly more often diagnosed with a co-morbid personality disorder. These findings are in line with previous studies yielding significantly lower success rates for ECT in patients with comorbid personality disorders (Vreede et al., 2005; Sareen et al., 2000), which may be partly explained by a higher level of pharmacotherapy treatment failure (Feske et al., 2004). Howev-
Fig. 1. Course of depressive symptoms during ECT among depressive patients, as measured by the MADRS.
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Table 2 Descriptives of the five identified classes by latent class analysis. Variables
Class I
Class II
Class III
Class IV
Class V
Fast improvement
Intermediate improvement
Slow improvement
Slow, with delayed onset
No improvement
N
(n = 39)
(n = 47)
(n = 30)
(n = 18)
(n = 20)
Treatment outcome Remission, n (%)
154
32 (84)
29 (63)
16 (55)
6 (33)
1 (6)
Response, n (%)
137
33 (94)
38 (91)
21 (81)
11 (65)
2 (12)
HDRS baseline, mean (SD)
141
26 (7)
26 (7)
29 (7)
32 (7)
28 (7)
HDRS after ECT, mean (SD)
148
4 (3)
8 (5)
8 (5)
13 (9)
20 (7)
MADRS baseline, mean (SD)
109
35 (9)
38 (11)
39 (8)
42 (8)
41 (7)
MADRS after ECT, mean (SD)
151
4 (4)
8 (5)
8 (6)
16 (15)
27 (9)
Patient characteristics Age in years, mean (SD)
154
63 (12)
64 (14)
69 (11)
69 (14)
58 (16)
Female gender, n (%)
154
30 (77)
36 (77)
23 (77)
16 (89)
13 (65)
Psychiatric characteristics First depressive episode, n (%)
153
11 (28)
14 (30)
9 (30)
4 (22)
8 (42)
Therapy resistance, n (%)
87
7 (33)
20 (71)
10 (59)
10 (83)
3 (33)
Psychotic features, n (%)
154
15 (39)
19 (40)
19 (63)
11 (61)
8 (40)
Personality disorder, n (%)
118
2 (7)
6 (17)
2 (8)
2 (15)
7 (44)
ECT treatment in history, n (%)
87
7 (33)
7 (25)
3 (18)
3 (25)
5 (56)
ECT characteristics No. of ECT sessions, mean (SD)
154
7 (3)
11 (3)
14 (4)
16 (5)
15 (5)
Delivering of ECT:
154
• Bilateral ECT only, n (%)
78
18 (46)
19 (40)
16 (53)
11 (61)
14 (70)
• Right unilateral ECT, n (%)
60
20 (51)
20 (43)
13 (43)
5 (28)
2 (10)
• Switch uni-bilateral ECT, n (%)
16
1 (3)
8 (17)
1 (3)
2 (11)
4 (20)
Threshold dosage, mean (SD)
154
20 (17)
17 (14)
18 (14)
15 (10)
13 (8)
Dosage during ECT, mean (SD)
133
47 (30)
59 (42)
67 (39)
67 (40)
37 (20)
Mean (SD) seizure duration (cuff)
154
46 (18)
43 (14)
39 (16)
36 (12)
54 (22)
Mean (SD) EEG seizure duration
154
74 (29)
66 (24)
62 (23)
60 (22)
81 (30)
Mean (SD) PSI
146
79 (19)
83 (12)
80 (15)
76 (19)
81 (16)
Statistics
χ2 = 34.4, df = 4, p b .001 χ2 = 52.2, df = 4, p b .001 F = 2.4, df = 4, p = .055 F = 30.3, df = 4, p b .001 F = 1.5, df = 4, p = .21 F = 33.5, df = 4, p b .001
F = 2.6, df = 4, p = .040 χ2 = 3.0, df = 4, p = .554
χ2 = 1.9, df = 4, p = .75 χ2 = 12.7 df = 4, p = .013 χ2 = 7.0, df = 4, p = .14 χ2 = 12.1 df = 4, p = .016 χ2 = 4.7, df = 4, p = .32
F = 29.3, df = 4, p b .001 χ2 = 17.3, df = 8, p = .028 χ2 = 6.2, df = 4, p = .19 χ2 = 11.0, df = 4, p = .027 χ2 = 8.4, df = 4, p = .078 F = 1.1, df = 4, p = .38 F = 3.0, df = 4, p = .021 F = 3.793, df = 4, p = .006 F = 2.761, df = 4, p = .030 F = 0.789, df = 4, p = .534
Abbreviations: M, mean; SD, standard deviation; ECT, electroconvulsive therapy; EEG, electro encephalogram; PSI, Postictal Suppression index; HAM-D17, Hamilton Depression rating scale —17 item version; MADRS, Montgomery–Asberg Depression Rating Scale.
er, in our sample the prevalence of pharmacotherapy treatment failure was similar to patients within the trajectory ‘fast improvement’ and even lower compared to patients in other trajectories. Our finding of five meaningful trajectories within a homogeneous patient population of 156 patients with unipolar depressive disorder might explain why the predic-
tion of ECT outcome has produced inconsistent results (Vreede et al., 2005; Dombrovski et al., 2005; Tsuchiyama et al., 2005; Pluijms et al., 2002; Rasmussen et al., 2007; Kho et al., 2005; Fink et al., 2007) and why efforts to identify specific responses within the first ECT sessions were inconclusive (Husain et al., 2004). Interestingly, the baseline severity of depressive symptoms did not differ between the
146
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different trajectories. Extrapolation of the course of depressive symptoms suggests that an even better outcome would have been achieved when continuing ECT for patients within the trajectories ‘intermediate improvement’, ‘slow improvement’, and ‘slow improvement with a delayed onset’, whereas prolonging the ECT course of patients assigned to the trajectories ‘fast improvement’ and ‘no improvement’ would not have resulted in a different outcome. Some limitations have to be taken into account for a proper interpretation. First, our results need replication in independent and larger samples, given the modest sample size of the present study. Secondly, describing a convenience sample of patients in routine clinical care, we did not have data on psychomotor retardation, duration of illness, age of first depressive episode and vegetative symptoms which might also have been related to ECT outcome (Dombrovski et al., 2005; Buchan et al., 1992; Hickie et al., 1996). Furthermore, data on history of prior ECT were not collected for patients treated before 2002. Thirdly, there could be an influence of electrode placement, as bilateral electrode placement is associated with faster improvement (Lerer et al., 1995) and the efficacy of bilateral ECT may be superior to unilateral ECT (Kellner et al., 2010), although this potential difference in efficacy did not show in the present study. Unfortunately, our sample size is too small to perform meaningful cluster analyses for patients receiving unilateral and bilateral ECT separately. The fast response trajectory, however, had more often unilateral electrode placement than the other groups. Furthermore, high-dosage right unilateral ECT, as applied in our sample, is equivalent to bilateral ECT with respect to the response rate as well as speed of response rate (Sackeim et al., 2000). The ‘slow improvement with delayed onset’ trajectory might partly be explained by an artifact due to the switch from unilateral to bilateral electrode placement after 6 sessions. However, as the prevalence of patients switching from unilateral to bilateral ECT did not differ between the five trajectories, this switch cannot fully explain the delayed onset of this trajectory. Finally, we delivered ECT twice weekly, thereby limiting generalization to clinics applying a thrice weekly pattern. Most patients in ECT studies also receive concomitant psychotropic drugs which is likely to hinder interpretation of results (Baghai et al., 2006; Nothdurfter et al., 2006). A major strength of our study is that, besides 5 patients who received low doses of haloperidol, all patients were free of psychotropic drug use during the ECT course. Therefore, the trajectories identified in our sample are not influenced by psychotropic drugs like benzodiazepines, mood stabilizers, antidepressants, and antipsychotic drugs, often used in this patient population. In conclusion, latent class analysis is a useful technique to analyze change of depressive symptoms over time. The results of this study suggest that prolonging the ECT course is recommendable, except for patients who achieve a clear remission (as occurred in trajectory I) and for patients with no response at all (as occurred in trajectory V). Previous studies using different methodologies also failed to identify a maximum number of ECT sessions within a treatment course, although most international guidelines suggest that a maximum number does exist (Abrams, 2002).Therefore, psychiatrists who deliver ECT according to current guidelines
might discontinue ECT prematurely, before remission is achieved, in a subgroup of patients who might have been able to attain remission with a prolonged ECT course. This means that a considerable number of patients should be offered more than 12–15 ECT sessions. Role of funding source There are not any study sponsor(s) involved in this study.
Conflict of interest There is not any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the work submitted that could inappropriately influence, or be perceived to influence, our work.
Acknowledgements We thank M. Lappenschaar, who kindly provided the statistical support for our analysis. References Abrams, R., 2002. Electroconvulsive therapy, 3rd ed. Oxford University Press, New York. American Psychiatric Association, 2001. The Practice of Electroconvulsive Therapy: Recommendations for Treatment, Training and Privileging. 2nd Ed. Washington DC: a Task Force Report of the American Psychiatric Association. Baghai, T.C., Marcuse, A., Brosch, M., Schule, C., Eser, D., Northdurfter, C., Steng, Y., Noack, I., Pietschmann, K., Moller, H.J., Rupprecht, R., 2006. The influence of concomitant antidepressant medication on safety, tolerability and clinical effectiveness of electroconvulsive therapy. World J. Biol. Psychiatry 7 (2), 82–90. Birkenhäger, T.K., Pluijms, E.M., Lucius, S.A., 2003. ECT response in delusional versus non-delusional depressed inpatients. J. Affect. Disord. 74 (2), 191–195. Birkenhäger, T.K., Van den Broek, W.W., Mulder, P.G., Moleman, P., Bruijn, J.A., 2008. Efficacy of imipramine in psychotic versus nonpsychotic depression. J. Clin. Psychopharmacol. 28 (2), 166–170. Buchan, H., Johnstone, E., McPherson, K., Palmer, R.L., Crow, T.J., Brandon, S., 1992. Who benefits from electroconvulsive therapy? Combined results of the Leicester and Northwick Park trials. Br. J. Psychiatry 160, 355–359. Dombrovski, A.Y., Mulsant, B.H., Haskett, R.F., Prudic, J., Begley, A.E., Sackeim, H.A., 2005. Predictors of remission after electroconvulsive therapy in unipolar major depression. J. Clin. Psychiatry 66 (8), 1043–1049. Feske, U., Mulsant, B.H., Pilkonis, P.A., Soloff, P., Dolata, D., Sackeim, H.A., Haskett, R.F., 2004. Clinical outcome of ECT in patients with major depression and comorbid borderline personality disorder. Am. J. Psychiatry 161 (11), 2073–2080. Fink, M., Rush, A.J., Knapp, R., Rasmussen, K., Mueller, M., Rummans, T.A., O'Connor, K., Husain, M., Biggs, M., Bailine, S., Kellner, C.H., 2007. DSM melancholic features are unreliable predictors of ECT response: a CORE publication. J. ECT 23 (3), 139–146. Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56–62. Heijnen, W.T., Van den Broek, W.W., Birkenhäger, T.K., 2008. Treatment failure with a tricyclic antidepressant followed by lithium addition and response to subsequent electroconvulsive therapy. J. Clin. Psychiatry 69 (12), 1887–1891. Hickie, I., Mason, C., Parker, G., Brodaty, H., 1996. Prediction of ECT response: validation of a refined sign-based (CORE) system for defining melancholia. Br. J. Psychiatry 169, 68–74. Husain, M.M., Rush, A.J., Fink, M., Knapp, R., Petrides, G., Rummans, T., Biggs, M.M., O'Connor, K., Rasmussen, K., Litle, M., Zhao, W., Bernstein, H.J., Smith, G., Mueller, M., McClintock, S.M., Bailine, S.H., Kellner, C.H., 2004. Speed of response and remission in major depressive disorder with acute electroconvulsive therapy (ECT): a Consortium for Research in ECT (CORE) report. J. Clin. Psychiatry 65 (4), 485–491. Kellner, C.H., Knapp, R., Husain, M.M., Rasmussen, K., Sampson, S., Cullum, M., McClintock, S.M., Tobias, K.G., Martino, C., Mueller, M., Bailine, S.H., Fink, M., Petrides, G., 2010. Comparing Bifrontal, Bitemporal, and Right Unilateral Electrode Placement in ECT: a multisite study from CORE (Consortium for Research in ECT). Br. J. Psychiatry 196, 226–234.
S. Cinar et al. / Journal of Affective Disorders 124 (2010) 141–147 Kessler, R.C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K.R., Rush, A.J., Walters, E.E., Wang, P.S., 2003. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 289, 3095–3105. Kho, K.H., van Vreeswijk, M.F., Simpson, S., Zwinderman, A.H., 2003. A metaanalysis of electroconvulsive therapy efficacy in depression. J. ECT 19 (3), 139–147. Kho, K.H., Blansjaar, B.A., Vothknecht, S., Cornelissen, N.M., Koomen, E., Zwinderman, A.H., Linszen, D.H., 2004. A study into predictors for the speed of response to electroconvulsive therapy. J. ECT 20 (3), 154–159. Kho, K.H., Zwinderman, A.H., Blansjaar, B.A., 2005. Predictors for the efficacy of electroconvulsive therapy: chart review of a naturalistic study. J. Clin. Psychiatry 66 (7), 894–899. Lerer, B., Shapira, B., Calev, A., Tubi, N., Drexler, H., Kindler, S., Lidsky, D., Schwartz, J.E., 1995. Antidepressant and cognitive effects of twiceversus three-times-weekly ECT. Am. J. Psychiatry 152, 564–570. Mental Health Evaluation & Community Consultation Unit, 2000. Electroconvulsive Therapy — Guidelines for Health Authorities in British Columbia. British Columbia Ministry of Health Services. Muthén, L.K., Muthén, B.O., 2006. Mplus version 4.1 statistical analysis with latent variables user's guide. National Institute for Clinical Excellence (NICE), 2003. Guidance on the use of electroconvulsive therapy. London (UK): National Institute for Clinical Excellence (NICE); (Technology appraisal; no. 59). Nothdurfter, C., Eser, D., Schüle, C., Zwanzger, P., Marcuse, A., Noack, I., Moller, H.J., Rupprecht, R., Baghai, T.C., 2006. The influence of concomitant neuroleptic medication on safety, tolerability and clinical effectiveness of electroconvulsive therapy. World J. Biol. Psychiatry 7 (3), 162–170. Nylund, K.L., Asparouhov, T., Muthen, B., 2007. Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Struct. Equ. Modeling 14, 535–569. NYS Office of Mental Health Guidance on Electroconvulsive Therapy (ECT), 2007. New York. Petrides, G., Fink, M., Husain, M.M., Knapp, R.G., Rush, A.J., Mueller, M., Rummans, T.A., O'Connor, K.M., Rasmussen Jr., K.G., Bernstein, H.J., Biggs, M., Bailine, S.H., Kellner, C.H., 2001. ECT remission rates in psychotic versus nonpsychotic depressed patients: a report from CORE. J. ECT 17 (4), 244–253. Pluijms, E.M., Birkenhäger, T.K., Huijbrechts, I.P., Moleman, P., 2002. Influence of resistance to antidepressant pharmacotherapy on shortterm response to electroconvulsive therapy. J. Affect. Disord. 69, 93–99. Rasmussen, K.G., Mueller, M., Knapp, R.G., Husain, M.M., Rummans, T.A., Sampson, S.M., O'Connor, M.K., Petrides, G., Fink, M., Kellner, C.H., 2007.
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Antidepressant medication treatment failure does not predict lower remission with ECT for major depressive disorder: a report from the consortium for research in electroconvulsive therapy. J. Clin. Psychiatry 68 (11), 1701–1706. Rich, C.L., Spiker, D.G., Jewell, S.W., Neil, J.F., Black, N.A., 1984. The efficiency of ECT: I. Response rate in depressive episodes. Psychiatry Res. 11, 167–176. Sackeim, H.A., Prudic, J., Devanand, D.P., Nobler, M.S., Lisanby, S.H., Peyser, S., Fitzsimons, L., Moody, B.J., Clark, J., 2000. A prospective, randomized, double-blind comparison of bilateral and right unilateral electroconvulsive therapy at different stimulus intensities. Arch. Gen. Psychiatry 57, 425–434. Sareen, J., Enns, M.W., Guertin, J.E., 2000. The impact of clinically diagnosed personality disorders on acute and one-year outcomes of electroconvulsive therapy. J. ECT 16 (1), 43–51. Shapira, B., Lerer, B., 1999. Speed of response to bilateral ECT: an examination of possible predictors in two controlled trials. J. ECT 15 (3), 202–206. Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., Amorim, P., Janavs, J., Weiller, E., Hergueta, T., Baker, R., Dunbar, G.C., 1998. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 59 (20), 22–33. Sienaert, P., Dierick, M., Degraeve, G., Peuskens, J., 2006. Electroconvulsive therapy in Belgium: a nationwide survey on the practice of electroconvulsive therapy. J. Affect. Disord. 90 (1), 67–71. Tsuchiyama, K., Nagayama, H., Yamada, K., Isogawa, K., Katsuragi, S., Kiyota, A., 2005. Predicting efficacy of electroconvulsive therapy in major depressive disorder. Psychiatry Clin. Neurosci. 59 (5), 546–550. UK ECT review group, 2003. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. Lancet 361 (9360), 799–808. Van den Broek, W.W., Huyser, J., Koster, A.M., 2000. Richtlijn Elektroconvulsietherapie. Richtlijnen Nederlandse Vereniging voor Psychiatrie, Uitgeverij Boom, Amsterdam. Van den Broek, W.W., de Lely, A., Mulder, P.G., Birkenhäger, T.K., Bruijn, J.A., 2004. Effect of antidepressant medication resistance on short-term response to electroconvulsive therapy. J. Clin. Psychopharmacol. 24 (4), 400–403. Vreede, I.M., Burger, H.B., van Vliet, I.M., 2005. Prediction of response to ECT with routinely collected data in major depression. J. Affect. Disord. 86, 323–327. Williams, J.B., Kobak, K.A., 2008. Development and reliability of a structured interview guide for the Montgomery Asberg Depression Rating Scale (SIGMA). Br. J. Psychiatry 192 (1), 52–58.
Contents lists available at ScienceDirect
Journal of Affective Disorders j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j a d
Research report
The course of depressive symptoms in unipolar depressive disorder during electroconvulsive therapy: A latent class analysis S. Cinar a,⁎, R.C. Oude Voshaar a,b, J.G.E. Janzing a, T.K. Birkenhäger c, J.K. Buitelaar a, W.W. van den Broek c a
Radboud University Nijmegen Medical Centre, Nijmegen Centre for Evidence-Based Practice, Department of Psychiatry, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands b Forum GGZ Nijmegen, Department of Old Age Psychiatry, Nijmegen, The Netherlands c Department of Psychiatry, Erasmus Medical Centre, Rotterdam, The Netherlands
a r t i c l e
i n f o
Article history: Received 23 August 2009 Received in revised form 1 November 2009 Accepted 1 November 2009 Available online 20 November 2009 Keywords: Electroconvulsive therapy ECT Speed of response Major depression
a b s t r a c t Background: Research examining the course of depressive symptoms during electroconvulsive therapy (ECT) is relatively scarce. Objective: To classify patients according to the course of their depressive symptoms while receiving ECT. Methods: The sample consisted of 156 consecutive patients receiving ECT for unipolar depressive disorder. Depressive symptoms were measured weekly with the Montgomery– Asberg Depression Rating Scale. Latent class analysis was applied to identify distinct trajectories of symptom improvement. Results: We identified five classes of different trajectories (improvement rates) of depressive symptoms, i.e. fast improvement (39 patients), intermediate improvement (47 patients), slow improvement (30 patients), slow improvement with delayed onset (18 patients), and finally a trajectory with no improvement (20 patients). The course of depressive symptoms at the end of the treatment within the trajectories of intermediate improvement, slow improvement and slow improvement with delayed onset, was still improving and did not achieve a plateau. Conclusion: The different courses of depressive symptoms during ECT probably contribute to mixed results of prediction studies of ECT outcome. Data suggest that for a large group of patients no optimal clinical endpoint can be identified, other than full remission or no improvement at all, to discontinue ECT. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Unipolar major depression is a common and disabling psychiatric disorder leading to serious disruptions in all major areas of functioning (Kessler et al., 2003). Electroconvulsive therapy (ECT) is considered to be the most effective, short-term biological treatment for major depression. Meta-analysis of 1144 patients in 18 trials showed ECT to be superior to
⁎ Corresponding author. Radboud University Nijmegen Medical Centre, Department of Psychiatry (961), PO Box 9101, 6500 HB Nijmegen, The Netherlands. Tel.: +31 24 3613489; fax: +31 24 3540561. E-mail address: [email protected] (S. Cinar). 0165-0327/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jad.2009.11.002
pharmacotherapy with an effect size of 0.80 (UK ECT Review group, 2003). The Consortium for Research in ECT (CORE) (Husain et al., 2004) reported a 75% remission rate among 217 patients in the United States, only 5% of whom required more than 12 treatment sessions. In Europe, remission rates are estimated around 50% with an average number of ECT sessions around 14 (Birkenhäger et al., 2003; Van den Broek et al., 2004; Vreede et al., 2005). This might be due to confounding by indication, as in European countries the indication for ECT is more strictly reserved for a higher level of previous pharmacotherapy failure. In some US studies, the latter was associated with poorer response to ECT (Dombrovski et al., 2005; Tsuchiyama et al., 2005), although these results have not been
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replicated by other research groups (Heijnen et al., 2008; Kho et al., 2004; Pluijms et al., 2002; Rasmussen et al., 2007; Van den Broek et al., 2004). Decreased response to ECT might be due to long episode duration before starting ECT (Pluijms et al., 2002). Although ECT is widely used for treatment of major depression in clinical practice, empirical evidence determining the optimal number of sessions for an ECT course is still lacking. A recent audit of electroconvulsive therapy practices in Belgium shows that ECT utilization rates and number of treatment sessions widely varies between clinics (Sienaert et al., 2006). Most guidelines, however, advocate relatively short treatment courses, comprising 6 to 12 treatment sessions on average (American Psychiatric Association, 2001; National Institute for Clinical Excellence, 2003; NYS Office of Mental Health, 2007). The Health Authorities in British Columbia even recommend a second opinion if patients need more than 15 ECT treatments in an index course of treatment (Mental Health Evaluation and Community Consultation Unit, 2000). There is no advice available for patients with a partial response, however. The Dutch guidelines (Van den Broek et al., 2000) do not mention a standard number of treatment sessions, but advise to treat a patient until one of the following endpoints is reached: 1) full remission, 2) no response after ten bilateral ECT sessions with adequate seizures, and 3) no further improvement during the last four ECT sessions using bilateral electrode placement, after at least ten ECT sessions. Studies describing the course of depressive symptoms during ECT treatment are relatively scarce. In the CORE study, 54% of the patients showed a response (N50% decrease of HAMD score) after only three ECT sessions. In order to investigate whether a threshold of symptom reduction after various numbers of ECT sessions would predict response or remission, subsequent analyses were performed, but did not yield clinically relevant results (Husain et al., 2004). Other studies focused on the speed of response to ECT. They showed associations between a fast response and younger age (Rich et al., 1984; Shapira and Lerer, 1999), psychotic features (Kho et al., 2003; Petrides et al., 2001) and high depression severity at baseline (Kho et al., 2004). In addition, a rapid response was associated with a three times weekly ECT schedule (Lerer et al., 1995) and a high seizure energy index (Kho et al., 2004). Applying latent class analysis (LCA) to longitudinal datasets allows to identify specific subgroups (called trajectories) empirically, based on changing symptom scores. Nevertheless, LCA has never been utilized to investigate the course of depressive symptoms during ECT. In the present study, we set out to classify depressed patients receiving ECT according to their course of depressive symptoms during treatment. The aim was to establish whether there were distinct trajectories of depressive symptoms during ECT treatment and, secondly, to describe clinical and ECT variables associated with these different trajectories.
in the Netherlands with a long history of ECT practice. Patients were included in the study if they met the DSM-IV criteria for major depressive disorder based on clinical observation during a routinely drug-free period of one week, and confirmed by the Mini International Neuropsychiatric Interview version 5 (Sheehan et al., 1998). Exclusion criteria were bipolar disorder, schizoaffective disorder, primary psychotic disorder, neurological illness and life-threatening medical illness. For patients who received more than one course of ECT during the study period, only their first course was analyzed. 2.2. ECT procedures ECT was administered twice weekly using a brief pulse constant current apparatus (Thymatron System IV, Somatics, IL, USA). Seizure threshold was determined by empirical stimulus titration during the first session. It was defined as the stimulus dosage that elicits a seizure of at least 25 s according to the cuff method. If the starting stimulus dose failed to elicit a seizure of at least 25 s duration as measured by the cuff method, stimulus charge was increased according to the titration schedule and the patient was restimulated after 30 s. For the second treatment, the stimulus dosage was set at 1.5 times the initial seizure threshold for bilateral treatment (bitemporal) and at 6 times the initial seizure threshold for unilateral treatment. During the course of ECT, stimulus dosage settings were adjusted upward in order to maintain seizure duration of at least 25 s as measured by the cuff method. During the ECT sessions, anesthesia was achieved with intravenous administration of metoclopramide 10 mg, glycopyrrolate 0.002– 0.003 mg/kg, a bolus injection of alfentanil 0.010–0.015 mg/ kg and etomidate 0.2–0.3 mg/kg or propofol followed by succinylcholine 0.5–1.0 mg/kg for muscle relaxation. Patients were withdrawn from all psychotropic medication at least 1 week before ECT and were maintained drugfree during the course of ECT in all but 5 cases with severe anxiety or agitation. These patients were treated with haloperidol 1 to 5 mg. 2.3. Primary outcome variable Clinical evaluation of depressive symptoms was performed weekly using the Montgomery–Asberg Depression Rating Scale (MADRS) (Williams and Kobak, 2008). The main outcome variable was the course of MADRS scores. In addition, the scores on the 17-item version of the Hamilton Rating Scale for Depression (HAM-D17) (Hamilton, 1960) were obtained 1 to 3 days prior to ECT and 1 to 3 days after treatment termination. Remission was defined as a HAMD17 score of ≤7. Treatment failure or non-remission was defined as a HAM-D17 score of ≥8. Response was defined as a HAM-D17 end score improvement of at least 50% compared to baseline.
2. Methods 2.4. Clinical variables 2.1. Design and population A clinical sample was of inpatients suffering from unipolar major depressive disorder who received ECT treatment between September 2000 and November 2007 at the depression unit of Erasmus Medical Centre, a tertiary, academic centre
In addition to demographic variables (age, gender), the following disease-related variables were assessed: history of prior depressive episodes, pharmacotherapy treatment failure, ECT treatment in history, the presence of psychotic features and the presence of a previously diagnosed co-
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morbid personality disorder. The presence of psychotic features (dichotomized) was established using DSM-IV criteria for depressive disorder with psychotic features, and assessed within the first week of hospitalization (see above). Pharmacotherapy treatment failure was defined as the use of at least two courses of antidepressants of different classes during a sufficiently long period of time (at least 4 weeks) using a therapeutic dosage (modern antidepressants) or an adequate blood level (tricyclic agents). It was included as a dichotomized variable as well. History of prior ECT and previous pharmacotherapy treatment failure was only recorded for patients included after 2002. 2.5. Data analysis A latent class analysis (LCA) was conducted using MPLUS (Muthén and Muthén, 2006). The assumption behind this LCA is that there exist a certain number of distinct trajectories of depressive symptoms according to which subjects can be grouped. These trajectories are known as latent classes. They are based on the reaction to ECT treatment in terms of a time profile, with each subject belonging to one class. Latent class modeling aims to obtain the smallest number of classes accounting for all associations between the variables, in this case the MADRS scores. This implies local independence within classes, as the probability of a certain level of depressive symptoms is independent of the level of symptoms at any other time of measurement. The posterior probability of belonging to a class can be obtained for each person, with subjects allocated to the class for which this probability is the largest. Class-specific probabilities, given membership of that class, allow profiles of reaction to ECT treatment to be developed for subjects in each class. Latent class models are fitted successively, starting with a one-class model (whereby it is assumed that all subjects have the same trajectory of depressive symptoms during ECT) and then adding another class for each successive model. The number of classes with the lowest BIC value (goodness of fit statistic) (Nylund et al., 2007) was chosen on the prerequisite of sufficiently large classes (defined as at least 10% of the sample). In order to compare characteristics between classes, we performed Chi-square tests, ANOVA and Kruskal Wallis tests using SPSS for Windows (version 16.0 ). Post-hoc tests were computed with Chi-square tests, Mann–Whitney U tests or Tukey post-hoc tests in case an ANOVA procedure was applied. Statistical significance was defined as p b .05. We did not correct for multiple comparisons, as the post-hoc comparison between classes was merely explorative. 3. Results 3.1. Patient recruitment Within the study period, 210 patients received 221 courses of ECT (9 patients received a second course and 1 a third course; these 2nd and 3rd courses were excluded from further analyses). A total of 54 patients met one of the exclusion criteria (bipolar disorder, n = 19; psychotic disorder, n = 20; catatonia, n = 1; other condition, n = 8; unknown diagnosis, n = 6), leaving a final study sample of 156 patients (74%)
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suffering from a unipolar depressive disorder. Initially, 78/156 (50%) patients were treated with right unilateral ECT. Of those, 17/78 (22%) were crossed over to bilateral ECT because of insufficient response after 3 to 11 treatments. The other 78 patients received bilateral ECT from the start, because of the severity of the illness according to clinical observation or prior response to bilateral ECT. Classifying patients that were crossed over from unilateral to bilateral ECT as treatment failures for unilateral ECT, we found similar success rates for patients initially starting with unilateral compared to those initially starting with bilateral ECT (43/78 (55%) versus 42/78 (55%) remission, χ2 = 0.00, df = 1, p = 1.00). The average age of the study sample was 64.3 years (range 21–89) and the male-female ratio 1:3 (23%:77%). The mean severity of depressive symptoms was 38.1 (SD 9.0) as measured with the MADRS and 27.6 (SD 7.2) as measured with the HAM-D17. Psychotic features were present in 73/156 (47%) of the patients and 51/88 (58%) received ECT due to pharmacotherapy treatment failure. A total of 108/156 patients (69%) had a history of previous depressive episodes and 25/88 (28%) patients had received a prior ECT course. The median number of ECT sessions in the current episode was 12 (range 1–36). As presented in Table 1, the fit statistics indicated that the BIC-values decreased for every additional LCA class. However, in light of the smaller size of classes starting from the sixsolution and the fact that the additional classes could be considered subsets of previous identified trajectories, we chose the 5-class solution as best. This solution provided classes with sufficient subjects for subsequent analyses with classes above 10%. One patient was excluded from these analyses because of missing MADRS scores. Another patient was excluded due to an atypical course during ECT, that is, extremely fluctuating MADRS scores. The LCA revealed five latent classes representing different profiles of depressive symptoms changing over time after ECT (called trajectories; see Fig. 1). Trajectory I included 39 patients (25%) who showed immediate improvement of depressive symptoms and could be labeled ‘fast improvement’. Trajectory II comprised 47 patients (31%) and was labeled ‘intermediate improvement’ as the course of improvement of depressive symptoms was intermediate between trajectory I and III. Trajectory III consisted of 30 (20%) patients with a very gradual symptom improvement and could be labeled ‘slow improvement’. Trajectory IV consisted of 18 patients (12%) and was marked by initial slight deterioration before responding and was labeled ‘slow improvement with delayed onset’. Finally, the fifth class consisted of 20 patients (13%) with virtually no response to treatment and was labeled ‘no improvement’. Table 2 presents the average outcome, demographics, and psychiatric and ECT characteristics for patients per trajectory (class). The five trajectories did not differ with respect to their baseline depression severity, number of depressive episodes, or presence of psychotic features. As expected, overall differences between the five trajectories with subsequent significant post-hoc tests were found for treatment outcome (in order of decreasing remission rates for trajectory labeled ‘fast improvement’, ‘intermediate improvement’, ‘slow improvement’, ‘slow improvement with delayed onset’, and ‘no improvement’), pharmacotherapy treatment failure (less
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Table 1 Fit statistics for latent class analysis identifying classes of depressive symptoms during ECT: Bayesian information criteria values. Class
1
2
3
4
5
6
7
8
9
10
BIC value
11217
8870
8126
7863
7687
7572
7521
7446
7423
7407
common in the trajectories ‘fast improvement’ and ‘no improvement’) and a co-morbid personality disorder (more likely in trajectory ‘no improvement’). Patients in the trajectory labeled ‘no improvement’ more often received bilateral ECT than patients in the other trajectories. 4. Discussion Our sample of patients receiving ECT for unipolar major depressive disorder could be described as a severely depressed population of inpatients: the mean HAM-D17 score was 27.6 points, 47% had psychotic features, and 58% had a significant level of pharmacotherapy treatment failure. The proportion of patients in our sample with psychotic features appears to be high. This may be explained by the selection of depressed inpatients, about 33% of depressed inpatients at our unit has psychotic features (Birkenhäger et al., 2008). Furthermore, since in The Netherlands ECT is a fairly exceptional treatment administered almost exclusively to severely depressed patients with melancholic features, the selection of patients for ECT may well have increased the proportion of patients with “psychotic features”. After delivering an average number of 12 ECT sessions, the remission rate was 56%, similar to previous European ECT studies (Birkenhäger et al., 2003; Van den Broek et al., 2004; Vreede et al., 2005). Within this patient population, we identified five trajectories of depressive symptoms during ECT, using latent class analysis. Based on decreasing, thus improving, BIC values, a higher number of trajectories (up to 10) could be identified. These solutions however, were not suitable, as the low number of subjects within each additional
trajectory would not allow meaningful subsequent analyses. Moreover, only more subclasses with almost identical courses of depressive symptoms would have been created, as the additional classes were created by splitting up trajectories with a gradual or slow response that were previously identified. Within trajectory I (39 patients), called ‘fast improvement’, 84% of the patients remitted and 94% responded to ECT, receiving 7 ECT sessions on average. The proportion of successfully treated patients gradually decreased for the trajectories ‘intermediate improvement’ (47 patients, 63% remitted, 91% responded) and ‘slow improvement’ (30 patients, 55% remitted, 81% responded) after an average number of 11 and 14 sessions, respectively. The other two trajectories included smaller numbers of patients. The trajectory of ‘slow improvement with a delayed onset’ included 18 patients and had a less favorable outcome; the remission rate was 33% and the response rate was 65%, after 16 sessions on average. The trajectory ‘no improvement’ included 20 patients of whom only 1 patient remitted and 2 responded to ECT. The average number of sessions was 15. The only patient who remitted in this ‘no improvement’ trajectory, demonstrated a highly fluctuating depression severity score during the last four weeks of ECT. Therefore, a stable remission was unlikely, even though our remission criterium (HAM-D17 end score of ≤7) was met. Patients in this ‘no improvement’ trajectory were significantly more often diagnosed with a co-morbid personality disorder. These findings are in line with previous studies yielding significantly lower success rates for ECT in patients with comorbid personality disorders (Vreede et al., 2005; Sareen et al., 2000), which may be partly explained by a higher level of pharmacotherapy treatment failure (Feske et al., 2004). Howev-
Fig. 1. Course of depressive symptoms during ECT among depressive patients, as measured by the MADRS.
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Table 2 Descriptives of the five identified classes by latent class analysis. Variables
Class I
Class II
Class III
Class IV
Class V
Fast improvement
Intermediate improvement
Slow improvement
Slow, with delayed onset
No improvement
N
(n = 39)
(n = 47)
(n = 30)
(n = 18)
(n = 20)
Treatment outcome Remission, n (%)
154
32 (84)
29 (63)
16 (55)
6 (33)
1 (6)
Response, n (%)
137
33 (94)
38 (91)
21 (81)
11 (65)
2 (12)
HDRS baseline, mean (SD)
141
26 (7)
26 (7)
29 (7)
32 (7)
28 (7)
HDRS after ECT, mean (SD)
148
4 (3)
8 (5)
8 (5)
13 (9)
20 (7)
MADRS baseline, mean (SD)
109
35 (9)
38 (11)
39 (8)
42 (8)
41 (7)
MADRS after ECT, mean (SD)
151
4 (4)
8 (5)
8 (6)
16 (15)
27 (9)
Patient characteristics Age in years, mean (SD)
154
63 (12)
64 (14)
69 (11)
69 (14)
58 (16)
Female gender, n (%)
154
30 (77)
36 (77)
23 (77)
16 (89)
13 (65)
Psychiatric characteristics First depressive episode, n (%)
153
11 (28)
14 (30)
9 (30)
4 (22)
8 (42)
Therapy resistance, n (%)
87
7 (33)
20 (71)
10 (59)
10 (83)
3 (33)
Psychotic features, n (%)
154
15 (39)
19 (40)
19 (63)
11 (61)
8 (40)
Personality disorder, n (%)
118
2 (7)
6 (17)
2 (8)
2 (15)
7 (44)
ECT treatment in history, n (%)
87
7 (33)
7 (25)
3 (18)
3 (25)
5 (56)
ECT characteristics No. of ECT sessions, mean (SD)
154
7 (3)
11 (3)
14 (4)
16 (5)
15 (5)
Delivering of ECT:
154
• Bilateral ECT only, n (%)
78
18 (46)
19 (40)
16 (53)
11 (61)
14 (70)
• Right unilateral ECT, n (%)
60
20 (51)
20 (43)
13 (43)
5 (28)
2 (10)
• Switch uni-bilateral ECT, n (%)
16
1 (3)
8 (17)
1 (3)
2 (11)
4 (20)
Threshold dosage, mean (SD)
154
20 (17)
17 (14)
18 (14)
15 (10)
13 (8)
Dosage during ECT, mean (SD)
133
47 (30)
59 (42)
67 (39)
67 (40)
37 (20)
Mean (SD) seizure duration (cuff)
154
46 (18)
43 (14)
39 (16)
36 (12)
54 (22)
Mean (SD) EEG seizure duration
154
74 (29)
66 (24)
62 (23)
60 (22)
81 (30)
Mean (SD) PSI
146
79 (19)
83 (12)
80 (15)
76 (19)
81 (16)
Statistics
χ2 = 34.4, df = 4, p b .001 χ2 = 52.2, df = 4, p b .001 F = 2.4, df = 4, p = .055 F = 30.3, df = 4, p b .001 F = 1.5, df = 4, p = .21 F = 33.5, df = 4, p b .001
F = 2.6, df = 4, p = .040 χ2 = 3.0, df = 4, p = .554
χ2 = 1.9, df = 4, p = .75 χ2 = 12.7 df = 4, p = .013 χ2 = 7.0, df = 4, p = .14 χ2 = 12.1 df = 4, p = .016 χ2 = 4.7, df = 4, p = .32
F = 29.3, df = 4, p b .001 χ2 = 17.3, df = 8, p = .028 χ2 = 6.2, df = 4, p = .19 χ2 = 11.0, df = 4, p = .027 χ2 = 8.4, df = 4, p = .078 F = 1.1, df = 4, p = .38 F = 3.0, df = 4, p = .021 F = 3.793, df = 4, p = .006 F = 2.761, df = 4, p = .030 F = 0.789, df = 4, p = .534
Abbreviations: M, mean; SD, standard deviation; ECT, electroconvulsive therapy; EEG, electro encephalogram; PSI, Postictal Suppression index; HAM-D17, Hamilton Depression rating scale —17 item version; MADRS, Montgomery–Asberg Depression Rating Scale.
er, in our sample the prevalence of pharmacotherapy treatment failure was similar to patients within the trajectory ‘fast improvement’ and even lower compared to patients in other trajectories. Our finding of five meaningful trajectories within a homogeneous patient population of 156 patients with unipolar depressive disorder might explain why the predic-
tion of ECT outcome has produced inconsistent results (Vreede et al., 2005; Dombrovski et al., 2005; Tsuchiyama et al., 2005; Pluijms et al., 2002; Rasmussen et al., 2007; Kho et al., 2005; Fink et al., 2007) and why efforts to identify specific responses within the first ECT sessions were inconclusive (Husain et al., 2004). Interestingly, the baseline severity of depressive symptoms did not differ between the
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different trajectories. Extrapolation of the course of depressive symptoms suggests that an even better outcome would have been achieved when continuing ECT for patients within the trajectories ‘intermediate improvement’, ‘slow improvement’, and ‘slow improvement with a delayed onset’, whereas prolonging the ECT course of patients assigned to the trajectories ‘fast improvement’ and ‘no improvement’ would not have resulted in a different outcome. Some limitations have to be taken into account for a proper interpretation. First, our results need replication in independent and larger samples, given the modest sample size of the present study. Secondly, describing a convenience sample of patients in routine clinical care, we did not have data on psychomotor retardation, duration of illness, age of first depressive episode and vegetative symptoms which might also have been related to ECT outcome (Dombrovski et al., 2005; Buchan et al., 1992; Hickie et al., 1996). Furthermore, data on history of prior ECT were not collected for patients treated before 2002. Thirdly, there could be an influence of electrode placement, as bilateral electrode placement is associated with faster improvement (Lerer et al., 1995) and the efficacy of bilateral ECT may be superior to unilateral ECT (Kellner et al., 2010), although this potential difference in efficacy did not show in the present study. Unfortunately, our sample size is too small to perform meaningful cluster analyses for patients receiving unilateral and bilateral ECT separately. The fast response trajectory, however, had more often unilateral electrode placement than the other groups. Furthermore, high-dosage right unilateral ECT, as applied in our sample, is equivalent to bilateral ECT with respect to the response rate as well as speed of response rate (Sackeim et al., 2000). The ‘slow improvement with delayed onset’ trajectory might partly be explained by an artifact due to the switch from unilateral to bilateral electrode placement after 6 sessions. However, as the prevalence of patients switching from unilateral to bilateral ECT did not differ between the five trajectories, this switch cannot fully explain the delayed onset of this trajectory. Finally, we delivered ECT twice weekly, thereby limiting generalization to clinics applying a thrice weekly pattern. Most patients in ECT studies also receive concomitant psychotropic drugs which is likely to hinder interpretation of results (Baghai et al., 2006; Nothdurfter et al., 2006). A major strength of our study is that, besides 5 patients who received low doses of haloperidol, all patients were free of psychotropic drug use during the ECT course. Therefore, the trajectories identified in our sample are not influenced by psychotropic drugs like benzodiazepines, mood stabilizers, antidepressants, and antipsychotic drugs, often used in this patient population. In conclusion, latent class analysis is a useful technique to analyze change of depressive symptoms over time. The results of this study suggest that prolonging the ECT course is recommendable, except for patients who achieve a clear remission (as occurred in trajectory I) and for patients with no response at all (as occurred in trajectory V). Previous studies using different methodologies also failed to identify a maximum number of ECT sessions within a treatment course, although most international guidelines suggest that a maximum number does exist (Abrams, 2002).Therefore, psychiatrists who deliver ECT according to current guidelines
might discontinue ECT prematurely, before remission is achieved, in a subgroup of patients who might have been able to attain remission with a prolonged ECT course. This means that a considerable number of patients should be offered more than 12–15 ECT sessions. Role of funding source There are not any study sponsor(s) involved in this study.
Conflict of interest There is not any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the work submitted that could inappropriately influence, or be perceived to influence, our work.
Acknowledgements We thank M. Lappenschaar, who kindly provided the statistical support for our analysis. References Abrams, R., 2002. Electroconvulsive therapy, 3rd ed. Oxford University Press, New York. American Psychiatric Association, 2001. The Practice of Electroconvulsive Therapy: Recommendations for Treatment, Training and Privileging. 2nd Ed. Washington DC: a Task Force Report of the American Psychiatric Association. Baghai, T.C., Marcuse, A., Brosch, M., Schule, C., Eser, D., Northdurfter, C., Steng, Y., Noack, I., Pietschmann, K., Moller, H.J., Rupprecht, R., 2006. The influence of concomitant antidepressant medication on safety, tolerability and clinical effectiveness of electroconvulsive therapy. World J. Biol. Psychiatry 7 (2), 82–90. Birkenhäger, T.K., Pluijms, E.M., Lucius, S.A., 2003. ECT response in delusional versus non-delusional depressed inpatients. J. Affect. Disord. 74 (2), 191–195. Birkenhäger, T.K., Van den Broek, W.W., Mulder, P.G., Moleman, P., Bruijn, J.A., 2008. Efficacy of imipramine in psychotic versus nonpsychotic depression. J. Clin. Psychopharmacol. 28 (2), 166–170. Buchan, H., Johnstone, E., McPherson, K., Palmer, R.L., Crow, T.J., Brandon, S., 1992. Who benefits from electroconvulsive therapy? Combined results of the Leicester and Northwick Park trials. Br. J. Psychiatry 160, 355–359. Dombrovski, A.Y., Mulsant, B.H., Haskett, R.F., Prudic, J., Begley, A.E., Sackeim, H.A., 2005. Predictors of remission after electroconvulsive therapy in unipolar major depression. J. Clin. Psychiatry 66 (8), 1043–1049. Feske, U., Mulsant, B.H., Pilkonis, P.A., Soloff, P., Dolata, D., Sackeim, H.A., Haskett, R.F., 2004. Clinical outcome of ECT in patients with major depression and comorbid borderline personality disorder. Am. J. Psychiatry 161 (11), 2073–2080. Fink, M., Rush, A.J., Knapp, R., Rasmussen, K., Mueller, M., Rummans, T.A., O'Connor, K., Husain, M., Biggs, M., Bailine, S., Kellner, C.H., 2007. DSM melancholic features are unreliable predictors of ECT response: a CORE publication. J. ECT 23 (3), 139–146. Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56–62. Heijnen, W.T., Van den Broek, W.W., Birkenhäger, T.K., 2008. Treatment failure with a tricyclic antidepressant followed by lithium addition and response to subsequent electroconvulsive therapy. J. Clin. Psychiatry 69 (12), 1887–1891. Hickie, I., Mason, C., Parker, G., Brodaty, H., 1996. Prediction of ECT response: validation of a refined sign-based (CORE) system for defining melancholia. Br. J. Psychiatry 169, 68–74. Husain, M.M., Rush, A.J., Fink, M., Knapp, R., Petrides, G., Rummans, T., Biggs, M.M., O'Connor, K., Rasmussen, K., Litle, M., Zhao, W., Bernstein, H.J., Smith, G., Mueller, M., McClintock, S.M., Bailine, S.H., Kellner, C.H., 2004. Speed of response and remission in major depressive disorder with acute electroconvulsive therapy (ECT): a Consortium for Research in ECT (CORE) report. J. Clin. Psychiatry 65 (4), 485–491. Kellner, C.H., Knapp, R., Husain, M.M., Rasmussen, K., Sampson, S., Cullum, M., McClintock, S.M., Tobias, K.G., Martino, C., Mueller, M., Bailine, S.H., Fink, M., Petrides, G., 2010. Comparing Bifrontal, Bitemporal, and Right Unilateral Electrode Placement in ECT: a multisite study from CORE (Consortium for Research in ECT). Br. J. Psychiatry 196, 226–234.
S. Cinar et al. / Journal of Affective Disorders 124 (2010) 141–147 Kessler, R.C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K.R., Rush, A.J., Walters, E.E., Wang, P.S., 2003. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 289, 3095–3105. Kho, K.H., van Vreeswijk, M.F., Simpson, S., Zwinderman, A.H., 2003. A metaanalysis of electroconvulsive therapy efficacy in depression. J. ECT 19 (3), 139–147. Kho, K.H., Blansjaar, B.A., Vothknecht, S., Cornelissen, N.M., Koomen, E., Zwinderman, A.H., Linszen, D.H., 2004. A study into predictors for the speed of response to electroconvulsive therapy. J. ECT 20 (3), 154–159. Kho, K.H., Zwinderman, A.H., Blansjaar, B.A., 2005. Predictors for the efficacy of electroconvulsive therapy: chart review of a naturalistic study. J. Clin. Psychiatry 66 (7), 894–899. Lerer, B., Shapira, B., Calev, A., Tubi, N., Drexler, H., Kindler, S., Lidsky, D., Schwartz, J.E., 1995. Antidepressant and cognitive effects of twiceversus three-times-weekly ECT. Am. J. Psychiatry 152, 564–570. Mental Health Evaluation & Community Consultation Unit, 2000. Electroconvulsive Therapy — Guidelines for Health Authorities in British Columbia. British Columbia Ministry of Health Services. Muthén, L.K., Muthén, B.O., 2006. Mplus version 4.1 statistical analysis with latent variables user's guide. National Institute for Clinical Excellence (NICE), 2003. Guidance on the use of electroconvulsive therapy. London (UK): National Institute for Clinical Excellence (NICE); (Technology appraisal; no. 59). Nothdurfter, C., Eser, D., Schüle, C., Zwanzger, P., Marcuse, A., Noack, I., Moller, H.J., Rupprecht, R., Baghai, T.C., 2006. The influence of concomitant neuroleptic medication on safety, tolerability and clinical effectiveness of electroconvulsive therapy. World J. Biol. Psychiatry 7 (3), 162–170. Nylund, K.L., Asparouhov, T., Muthen, B., 2007. Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Struct. Equ. Modeling 14, 535–569. NYS Office of Mental Health Guidance on Electroconvulsive Therapy (ECT), 2007. New York. Petrides, G., Fink, M., Husain, M.M., Knapp, R.G., Rush, A.J., Mueller, M., Rummans, T.A., O'Connor, K.M., Rasmussen Jr., K.G., Bernstein, H.J., Biggs, M., Bailine, S.H., Kellner, C.H., 2001. ECT remission rates in psychotic versus nonpsychotic depressed patients: a report from CORE. J. ECT 17 (4), 244–253. Pluijms, E.M., Birkenhäger, T.K., Huijbrechts, I.P., Moleman, P., 2002. Influence of resistance to antidepressant pharmacotherapy on shortterm response to electroconvulsive therapy. J. Affect. Disord. 69, 93–99. Rasmussen, K.G., Mueller, M., Knapp, R.G., Husain, M.M., Rummans, T.A., Sampson, S.M., O'Connor, M.K., Petrides, G., Fink, M., Kellner, C.H., 2007.
147
Antidepressant medication treatment failure does not predict lower remission with ECT for major depressive disorder: a report from the consortium for research in electroconvulsive therapy. J. Clin. Psychiatry 68 (11), 1701–1706. Rich, C.L., Spiker, D.G., Jewell, S.W., Neil, J.F., Black, N.A., 1984. The efficiency of ECT: I. Response rate in depressive episodes. Psychiatry Res. 11, 167–176. Sackeim, H.A., Prudic, J., Devanand, D.P., Nobler, M.S., Lisanby, S.H., Peyser, S., Fitzsimons, L., Moody, B.J., Clark, J., 2000. A prospective, randomized, double-blind comparison of bilateral and right unilateral electroconvulsive therapy at different stimulus intensities. Arch. Gen. Psychiatry 57, 425–434. Sareen, J., Enns, M.W., Guertin, J.E., 2000. The impact of clinically diagnosed personality disorders on acute and one-year outcomes of electroconvulsive therapy. J. ECT 16 (1), 43–51. Shapira, B., Lerer, B., 1999. Speed of response to bilateral ECT: an examination of possible predictors in two controlled trials. J. ECT 15 (3), 202–206. Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., Amorim, P., Janavs, J., Weiller, E., Hergueta, T., Baker, R., Dunbar, G.C., 1998. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J. Clin. Psychiatry 59 (20), 22–33. Sienaert, P., Dierick, M., Degraeve, G., Peuskens, J., 2006. Electroconvulsive therapy in Belgium: a nationwide survey on the practice of electroconvulsive therapy. J. Affect. Disord. 90 (1), 67–71. Tsuchiyama, K., Nagayama, H., Yamada, K., Isogawa, K., Katsuragi, S., Kiyota, A., 2005. Predicting efficacy of electroconvulsive therapy in major depressive disorder. Psychiatry Clin. Neurosci. 59 (5), 546–550. UK ECT review group, 2003. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. Lancet 361 (9360), 799–808. Van den Broek, W.W., Huyser, J., Koster, A.M., 2000. Richtlijn Elektroconvulsietherapie. Richtlijnen Nederlandse Vereniging voor Psychiatrie, Uitgeverij Boom, Amsterdam. Van den Broek, W.W., de Lely, A., Mulder, P.G., Birkenhäger, T.K., Bruijn, J.A., 2004. Effect of antidepressant medication resistance on short-term response to electroconvulsive therapy. J. Clin. Psychopharmacol. 24 (4), 400–403. Vreede, I.M., Burger, H.B., van Vliet, I.M., 2005. Prediction of response to ECT with routinely collected data in major depression. J. Affect. Disord. 86, 323–327. Williams, J.B., Kobak, K.A., 2008. Development and reliability of a structured interview guide for the Montgomery Asberg Depression Rating Scale (SIGMA). Br. J. Psychiatry 192 (1), 52–58.