The effect of co-morbidity on the rehabilitation process in elderly patients after hip fracture

Archives of Gerontology and Geriatrics 45 (2007) 281–294 www.elsevier.com/locate/archger

The effect of co-morbidity on the rehabilitation process in elderly patients after hip fracture Yan Press a,b,c,d,e,*, Yacov Grinshpun a,b, Alex Berzak a,b,e, Michael Friger b,f, A. Mark Clarfield a,b,g a

Department of Geriatrics, Soroka Medical Hospital, POB 151, Beersheva 84101, Israel Faculty of Health Sciences, Ben-Gurion University of the Negev, POB 653, Beersheva 84653, Israel c Department of Family Medicine, Ben-Gurion University of the Negev, POB 653, Beersheva 84653, Israel d ‘‘Sial’’ Family Medicine and Primary Care Research Center, Ben-Gurion, University of the Negev, POB 653, Beersheva 84653, Israel e Yasski Clinic, Clalit Health Services, POB 616, Beersheva 84541, Israel f Department of Epidemiology, Ben-Gurion University of the Negev, POB 653, Beersheva 84653, Israel g Department of Geriatric Medicine, Sir Mortimer B. Davis Jewish General Hospital, McGill University, 3755 Cote Ste Catherine, Montreal H3T 1E2, Canada b

Received 28 June 2006; received in revised form 16 January 2007; accepted 18 January 2007 Available online 12 March 2007

Abstract We conducted a prospective observational study involving patients older than 65 years admitted for rehabilitation to the Geriatric Department of a university hospital after surgical treatment of hip fracture. We assessed functional status before, during and at the end of rehabilitation and as a measure of success of rehabilitation we calculated the Montebello Rating Factor Score (MRFS). In an attempt to make this index more reflective of changes in rehabilitative status we revised it accordingly. We measured demographic characteristics, cognitive function, affective status and co-morbidity. Data were collected from 102 patients with average age 79.0  6.5 years over a period of 12 months. In the uinvariant analysis, cognitive status, length of stay in Geriatric Department and co-morbidity were found as significant predictors of rehabilitation success. In the linear regression only Severity Index (SI) of Cumulative Illness Rating Scale for Geriatrics (CIRS-G) was found as a statistically significant predictor of rehabilitation outcome. In our context, we found that only co-morbidity (as measured by CIRS) is the best predictor of rehabilitation outcome of elderly patients after surgical repair of hip fracture. # 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Co-morbidity; Rehabilitation; Hip fracture in elderly; The Montebello Rating Factor Score; Cumulative Illness Rating Scale for Geriatrics * Corresponding author at: Department of Geriatrics, Soroka Medical Hospital, POB 151, Beersheva 84101, Israel. Tel.: +972 8 6407 740; fax: +972 8 6407 795. E-mail address: [email protected] (Y. Press). 0167-4943/$ – see front matter # 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2007.01.059

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1. Introduction Hip fracture is one of the leading causes of morbidity and mortality (Cauley et al., 2000; Koot et al., 2000) in the elderly population with the world incidence rising from 1.7 million in 1990 to approximately 6.3 million by the year 2050 (Cooper et al., 1992). A significant number of patients after hip fracture will lose their independence (Cree et al., 2001; Jones et al., 2002; Roder et al., 2003) and the risk of institutionalization following such fractures is high (Cree et al., 2000). While the best place for rehabilitation has been questioned in some studies (Huusko et al., 2002; Roder et al., 2003), at least in industrial countries, a significant proportion of the elderly undergo such care in various geriatric and rehabilitation units. Predictors of successful rehabilitation have been investigated in a large number of studies but with inconsistent results. For example, although age was found to be a significant negative prognostic predictor in some works (Mossey et al., 1989; Magaziner et al., 1990; Rochon et al., 1996; Naughton et al., 1999; Cree et al., 2000; Koot et al., 2000), this relationship was not found in others (Heruti et al., 1999; Beloosesky et al., 2002). Similarly, while cognitive impairment predicted a poor outcome in several groups (Mossey et al., 1989; Magaziner et al., 1990; Lieberman et al., 1996; Cree et al., 2000; Landi et al., 2002), it did not in another study (Beloosesky et al., 2002). Functional status (Mossey et al., 1989; Heruti et al., 1999; Naughton et al., 1999; Cree et al., 2000; Di Libero et al., 2001; Giaquinto et al., 2001; Jones et al., 2002), gender (Lieberman et al., 1996; Heruti et al., 1999; Cree et al., 2000), social support (Cooper et al., 1992; Naughton et al., 1999) and mood disturbances (Mossey et al., 1989; Magaziner et al., 1990) have all been investigated as predictors of prognosis as well. Typically, older patients often suffer from more than one disease. As such, co-morbidity has been investigated as prognostic predictor among many groups of elderly patients including those with arthritis (Berkanovic and Hurwicz, 1990; Gabriel et al., 1999), patients in geriatric residential population (Parmelee et al., 1995), in long-term care institutions (Bravo et al., 2002), in those with chronic disability (Rochon et al., 1996), in frail patients treated in general hospital (Landi et al., 2002), in geropsychiatric practice (Miller et al., 1992), in patients admitted for rehabilitation for various reasons (Naughton et al., 1999; Di Libero et al., 2001; Giaquinto et al., 2001; Patrick et al., 2001; Rozzini et al., 2002), in peritoneal dialysis patients (Fried et al., 2001), in patients after cardiac surgery (Jaeger et al., 1994) and also in older patients after hip fracture (Lieberman et al., 1996; Koot et al., 2000; Cree et al., 2001; Di Libero et al., 2001; Giaquinto et al., 2001; Patrick et al., 2001; Leibson et al., 2002). Only a few of the studies investigated co-morbidity in patients after hip fracture used formal scales of co-morbidity (Di Libero et al., 2001; Giaquinto et al., 2001; Patrick et al., 2001). Methods that evaluate co-morbidity using measures of disease severity fall into two general categories: (i) assessment the summation of severity scores of all relevant conditions, and (ii) use of the most severe co-morbid disease present as the determinant of the severity of co-morbidity (Guralnik, 1996). The Charlson Co-morbidity Index (CCI) (Charlson et al., 1987) and CIRS-G (Miller et al., 1992) belong to the first category. While the CIRS-G has been evaluated and has been found to possess good inter-rater reliability and face validity (Miller et al., 1992), in contrast, to the best of our knowledge, the CCI has not been studied as a predictor of prognosis in hip fracture patients.

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The purpose of this study was to evaluate the influence of co-morbidity on rehabilitation outcomes utilizing a revision of the MRFS (Drubach et al., 1994) through measurement of the CCI and CIRS-G.

2. Patients and methods 2.1. Patients and rehabilitation process We assessed a total of 102 patients after surgical treatment of hip fracture admitted for rehabilitation from the Department of Orthopedics to the 25 bed Geriatrics Department of Soroka Medical Center, a 1000 bed tertiary care university hospital in Beersheva, Israel. The criteria for admission to the Geriatrics Department have been described elsewhere (Lieberman et al., 2004). The study took place between 14 November 2002 and 6 June 2004. For technical reasons unrelated to study, it was necessary to have a recruitment recess of 9 months during the study period. The only exclusion criteria were age <65 and death during hospitalization. In addition to medical care (provided by geriatricians) and to standard nursing care, inpatient rehabilitation typically included both physical therapy (1.0–1.5 h/day) and occupational therapy (1.0–1.5 h/day) on 5 out of 7 days per week. All patients admitted to the geriatric department underwent routine assessment by multi-disciplinary staff including physicians, nurses, physical therapist, occupational therapist, and social worker. 2.2. Assessment of cognitive function Cognitive function was assessed by using the Mini-Mental State Examination (MMSE) (Folstein et al., 1975) which develops a global score (ranging from 0 to 30, the higher is better). 2.3. Assessment of mood status Mood status was assessed by the 30 item Geriatric Depression Scale (GDS) (Yesavage et al., 1982–1983) which scores ranging from 0 to 30 where a score 10 indicates significant depressive symptomatology. 2.4. Assessment of functional status Functional status was assessed by Functional Independence Measure (FIM) (Keith et al., 1987), a seven-point ordinal scale in 18 items that measures self-care (eating, grooming, bathing, dressing upper and lower body and toileting), sphincter control (bladder and bowel), mobility (transfers to bed, chair/wheelchair, toilet and tub/shower), locomotion (walking/wheelchair and climbing stairs), communication (comprehension and expression) and cognition (social interaction, problem solving and memory). Scores on each item range from 1 (total dependence) to 7 (total independence) with a total score ranging from 18 to126. The scale was assessed by a team made up of a geriatrician, nurse,

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physical therapist, and occupational therapist. Four measures of FIM were carried out: before hip fracture (anamnestic FIM = anFIM) was based on the patient and caregiver history; on admission to the geriatric department (FIMa), weekly FIM during hospitalization and a FIM on discharge (FIMd). 2.5. Assessment of co-morbidity The CIRS-G (Miller et al., 1992) permits an estimate of illness burden and diversity on the basis of a physician rating using a five-point scale (score 0–4, the higher score is worse) reflecting the severity of pathology in each of 14 categories (maximum score 56). This scale does not include the primary diagnosis. (For more details please see Appendix A.) We calculated a new variable that reflects the number of categories with severity 3 (N3 + N4; where N3 represents the number of categories with severity 3, N4 represents the number of categories with severity 4). For example, if a patient has 5 of 14 categories with severity 3 and 2 of 14 categories with severity 4, this variable (N3 + N4) is scored as 7. The second tool we used for assessment of co-morbidity was the CCI (Charlson et al., 1987). Because its authors designed this index primarily as a predictor of mortality it presents a list of 19 conditions with fixed degrees of severity according to the relative risk of death. If a risk was calculated at 1.2 but <1.5, this disease received a score of 1; if the relative risk was 1.5 but <2.5, a score of 2; if 2.5 but <3, a score of 3; both a second metastatic solid tumor and HIV-AIDS received a score 6. A total score (TS) is calculated. The age score (AS) represents an extra point for each decade above age 50 and is used for adjusting the CCI for age. The total combined score (TCS) derived by adding AS to the TS. (For more details see Appendix B.) Both the CIRS-G and the CCI were completed close to admission by one of three authors (YP, YG, AB) on the basis of information in the patient’s chart. Where there was any doubt, a consensus was reached through discussion among the three investigators. 2.6. Measurement of rehabilitation process For quantitative measurement of rehabilitation process the MRFS (Drubach et al., 1994) is often used. It is calculated by taking the difference between FIMd and FIMa divided by the difference between highest possible score (anFIM) and FIMa as follows: MRFS ¼

FIMd  FIMa anFIM  FIMa

(1)

However, as this index reflexes only the absolute gains in functional status it can be misleading. For example, if one compares two hypothetical patients: the first was quite functional before the fracture with a value of anFIM of 120; after fracture repair, on admission to the rehabilitation department, her FIMa has dropped to 60. After rehabilitation, her FIMd has risen to 80. In this case the MRFS will be 0.33: MRFS ¼

FIMd  FIMa 80  60 ¼ ¼ 0:33 anFIM  FIMa 120  60

(2)

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The second patient, who was much more dependent before having suffered her hip fracture had anFIM 80, FIMa has dropped to 20 and after rehabilitation FIMd has risen to 40. In this case the MRFS will also be 0.33: MRFS ¼

FIMd  FIMa 40  20 ¼ ¼ 0:33 anFIM  FIMa 80  20

(3)

As such, according to the MRFS formula, both of these two patients enjoyed an equal level of rehabilitative success. However, it should be clear that they are indeed different. As such, we have adjusted the MRFS to make it more relevant to clinical practice by changing the calculation from an absolute to a relative one as follows: MRFS-R ¼

ðFIMd  FIMaÞ=FIMd ðanFIM  FIMaÞ=anFIM

(4)

where MRFS-R indicates the revised version of MRFS. Using this modification, in the first case (anFIM = 120, FIMa = 60, FIMd = 80) the MRFS-R would total 0.5, as follows: MRFS-R ¼

ð80  60Þ=80 ¼ 0:5 ð120  60Þ=120

(5)

while in the second case (anFIM = 80, FIMa = 20, FIMd = 40) the MRFS-R would be higher at 0.67: MRFS-R ¼

ð40  20Þ=40 ¼ 0:67 ð80  20Þ=80

(6)

We hold that the second patient realized his rehabilitation potential more than did the first, and that the MRFS-R is a more useful way in which to quantify the differences than is the MRFS alone since it controls in part for the pre-fracture functional status. 2.7. Statistical methods The data were analyzed using the SPSS software (Statistical Package for the Social Sciences, SPSS Inc., Chicago) on a mainframe computer. Rehabilitation outcomes (MRFS and MRFS-R) served as the main dependent variables. To analyze the association of MRFS and MRFS-R with different variables x2 statistic or t-tests were used, as appropriate. A linear regression model was developed to examine which of the variables are statistically significant in predicting rehabilitation outcomes. Statistical significance was determined at the p < 0.05 level throughout.

3. Results 3.1. Demographic characteristics Data were collected from 102 patients (72 women, 30 men) with a mean age of 79  6.5 years; who had resided in Israel an average of 32.6  20 years. All were admitted to the

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Table 1 Demographic characteristics and type of surgery after hip fracture (n = 102) n

%

Gender (males)

30

29.4

Place of birth Africa Asia Europe South America Israel

30 7 61 2 2

29.4 6.9 59.8 2 2

Total Education 4 years 5–8 years 9 years Total Living status With children Alone With spouse LTC Missing data Total Family status Married Widow Divorced Total Number of children None 1–3 children 4 children Total Formal caregiver None 10 h/week 10–15 h/week Total Type of the surgical repair Internal fixation Hemi-arthroplasty THR Total

102

33 26 43 102

23 37 38 2 2 102

44 52 6 102

16 57 29 102

57 29 11 102

68 30 4 102

100

32.4 25.5 42.1 100

22.5 26.3 37.2 2 2 100

43.2 50.9 5.9 100

15.6 55.9 28.4 100

55.9 28.4 10.8 100

66.7 29.4 3.9 100

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Geriatrics Department from the Orthopedics Department for rehabilitation after hip fracture and surgical repair. The detailed demographic characteristics and type of surgery are shown in Table 1. 3.2. Rehabilitation outcomes In our sample, the most prominent co-morbidities measured by CIRS-G were hematopoetic, vascular and cardiac. The most prominent co-morbidities according to this scale of CCI were dementia (D), myocardial infarction (MI) and congestive heart failure (CHF). The mean MMSE on admission was 23.6  5.5, the mean GDS was 8.8  5.5. For all other tests data were complete, except for the GDS where we had missing data for eight patients. The mean length of stay (LOS) in Geriatric Department was 19.6  6.3 days. The functional status, co-morbidity scores and rehabilitation outcomes measured by the MRFS and MRFS-R, are shown in Table 2. Table 3 indicates all the correlations among continuous variables: the MRFS-R was positively correlated with MMSE ( p < 0.01) and LOS in Geriatric Department ( p < 0.05). A significant ( p < 0.01) but negative correlation was found with parameters of CIRS that defined severity of diseases (and not number of diseases): SI and sum of number categories at levels 3 and 4 severity (N3 + N4) of CIRS-G. No significant correlation was found with age, gender, education, length of residency in Israel and depressive symptomatology (as measured by the GDS). No significant correlation was found with co-morbidity measured by CCI (TS and TCS). All significant correlations (MMSE, LOS, SI) were included in the linear regression. Because of a very high correlation (r = 0.78) between SI and N3 + N4 and more prominent

Table 2 Functional status, indexes of co-morbidity and of rehabilitation (n = 102)

anFIM FIMa FIMd

Mean  S.D.

Range

113.0  15.6 74.9  14.4 88.4  17.9

60 to 126 39 to 101 37 to 113

CIRS-G TNCEa Total CIRS-G Score SI N3 categories N4 categories N3 + N4

5.23  1.73 9.9  3.99 1.88  0.39 0.68  0.91 0.09  0.32 0.76  0.98

1 2 1 0 0 0

CCI TS TCS

1.87  1.56 5.36  1.62

0 to 6 2 to 10

Indexes of rehabilitation MRFS MRFS-R

0.39  0.31 0.46  0.32

0.53 to 2.22 0.86 to 1.98

a

TNCE: total number categories endorsed.

to to to to to to

9 20 3 4 2 4

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Table 3 Spearman’s correlation coefficients among continuous variables (n = 102)

Age Residency in Israel time MMSE GDS Length of stay in geriatric department anFIM FIMa FIMd TNCE TCIRS SI N3 + N4 TS TCS MRFS

MRFS

MRFS-R

0.05 0.02 0.3y 0.16 0.24* 0.04 0.2* 0.56y 0.01 0.2* 0.3y 0.34 0 0

0.01 0.18 0.26y 0.17 0.25* 0.06 0.12 0.49y 0 0.18 0.39y 0.33y 0 0.01 0.99y

Note: *p < 0.05; yp < 0.01.

correlation between SI and MRFS-R than N3 + N4 and MRFS-R (r = 0.39 versus r = 0.33) we decided to include SI and not N3 + N4 in this regression. According to this model only SI was significant predictor of rehabilitation process (t = 4.504, beta = 0.411, p < 0.0001). As well as 16% of variance in rehabilitation process was uniquely accounted for by SI of CIRS.

4. Discussion Our main finding was that only co-morbidity as measured by SI of CIRS was a significant predictor of rehabilitation among elderly patients after surgical repair of hip fracture. Neither age, gender, cognitive status (measured by MMSE) nor mood (as measured by the GDS) influenced rehabilitation. We also did not find that LOS influenced rehabilitation, at least according to MRFS-R. With respect to age, our findings are not consistent with previous studies, which have shown advanced age as a predictor of poor rehabilitation (Mossey et al., 1989; Magaziner et al., 1990; Rochon et al., 1996; Naughton et al., 1999; Cree et al., 2000; Koot et al., 2000). One possibility may be that chronological age alone does not influence the rehabilitation results. An alternative explanation was that somehow, selection bias in admitting patients to the geriatrics ward may have influenced our results. Cognitive status was also not found to be a predictor of the rehabilitation process. This is in contrast to Heruti et al. (1999), who found that cognitive status (as measured by the cognitive part of FIMa) as opposed to age, sex and LOS was the only significant predictor of rehabilitation (odds ratio = OR = 2.2, 95% confidence interval = CI = [1.5– 3.7]). Unfortunately, while Heruti et al. (1999) did not use MMSE in their regression analysis, they found a high correlation between MMSE and the cognitive part of FIMa

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(r = 0.794). In our sample, the patients had very similar mean MMSE (23.6  5.4 in our sample versus 23.4  5.3 in Heruti’s sample) and a very similar correlation between MMSE and cognitive part of FIMa (r = 0.743). However, we could not demonstrate that MMSE was correlated with the MRFS-R. Beloosesky et al. (2002) found similar results in that cognitive status did not influence the rehabilitation process in patients after hip fracture. Some studies (Mossey et al., 1989; Magaziner et al., 1990) have found that depressive symptomatology was associated with poor prognosis after hip fracture. However, we did not find any association between such symptoms (measured by GDS) and the rehabilitation outcome. That being said, we did note a significant association between GDS and SI, anFIM, FIMa and FIMd but not with MRFS-R. This phenomenon may by explained by the possibility that patients with a lower pre-morbid functional status (measured by anFIM) have a higher GDS and a lower functional status at discharge and because the MRFS-R may overcomes influence of FIM differences the association between GDS and MRFS-R attenuated. The fact that neither GDS, MMSE nor age were correlated with rehabilitation outcomes was also observed by Patrick et al. (2001). In their study, only FIMa and co-morbidity affected the rehabilitation process. This group used ‘‘FIM-gain’’ (difference between FIMa and FIMd) and FIM-gain divided by LOS as a measure of rehabilitation outcomes. Because FIMa is including in the MRFS-R, we did not use this variable in our regression analysis. However, the mental and affective status can influence the results of rehabilitation (measured by MRFS-R) because there are a part of CIRS (‘‘psychiatric disease’’ of CIRS). In one study (Patrick et al., 2001) only 6% of the variance in the rehabilitation process was accounted for by co-morbidity. In our study this figure was somewhat higher and reached 16%. The difference may be explained at least in part by different way in which we measured ‘‘rehabilitation efficiency’’ where we utilized MRFS-R while Patrick et al. (2001) used the FIM-gain. In our study we compare two scales of co-morbidity, CIRS and CCI as predictors of rehabilitation. However, only the CIRS showed itself as a significant predictor of prognosis. There are several possible explanations. First, the CCI was designed primarily as a predictor of mortality (Bravo et al., 2002; Huusko et al., 2002) and as such way may be less appropriate for measurement of functional gains. In the CCI only a few diseases have two severity degrees. We interpret this to mean that this index only weakly influenced by severity of disease compare with the CIRS, in which each problem has four severity degrees. We found that severity (measured by SI) and not number of diseases (measured by TNCE) influences the rehabilitation (see Table 3): probably this is the reason why CCI is not a good predictor of rehabilitation process. In comparing the MRFS-R with MRFS we found, not surprisingly, that these rehabilitation indices were very highly correlated (r = 0.99, p < 0.01) (Table 3). That being said, the case of MRFS-R the adjusted R2-square was higher than in with the MRFS (0.16 versus 0.12). It suggests that MRFS-R can be a more accurate index than MRFS for the assessment of rehabilitation status.

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Our study suffered from certain weaknesses, involving the possibility of selection bias and lack of possibilities for generalization, in that we recruited only patients admitted to only one geriatric rehabilitation department in one hospital. However, we have no reason to believe that our patients are very different from others in similar departments (Heruti et al., 1999). As well, we did not include the patients who were sent from the Orthopedics Department to long-term rehabilitation (too ill) or were discharged home (too healthy) rather than be admitted to our ward. In conclusion, we found that co-morbidity, as measured by the SI of CIRS, is the best predictor of rehabilitation for elderly patients after surgical repair of hip fracture. In order to confirm our findings, this tool should be evaluated in other settings on patients with different diseases.

Acknowledgement This study was supported by a grant from the Center for Multidisciplinary Research in Aging, Ben-Gurion University of the Negev, Israel.

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Appendix A. CIRS-G (Miller et al., 1992)

291

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Appendix B. CCI (Charlson et al., 1987) Category

Score

Rules for filling

Myocardial Infarction (MY) Congestive Heart Failure (CHF)

1 1

Peripheral vascular disease

1

Cerebrovascular disease, except hemiplegia Dementia Chronic pulmonary disease

1

History of medically documented MI Symptomatic CHF with response to specific treatment Intermittent claudication, peripheral arterial bypass for insufficiency, gangrene, acute arterial insufficiency, untreated aneurysm (6 cm) History of TIA or CVA with no or minor sequelae

1 1

Connective tissue disease (CTD)

1

Ulcerative disease Mild liver disease

1 1

Diabetes mellitus without complications Diabetes mellitus with end organ damage Hemiplegia Moderate to severe renal disease

1

Chronic cognitive deficit Symptomatic dyspnoae due to chronic respiratory conditions (including asthma) SLE, polymyositis, mixed CTD, polymyalgia rheumatica, moderate to severe rheumatoid arthritis Patient who have required treatment for peptic ulcer Cirrhosis without portal hypertension, chronic hepatitis Diabetes with medications

2

Retinopathy, neuropathy, nephropathy

2 2

Second solid tumor (non-metastatic)

2

Leukemia Lymphoma

2 2

Moderate to severe liver disease Second metastatic solid tumor AIDS

3 6 6

Hemiplegia or paraplegia Creatinine > 3 mg/dl, dialysis, transplantation, uremic syndrome Initially treated in the last 5 years. Exclude non-melanomatous skin cancers and in situ cervical carcinoma CML, CLL, AML, ALL, PV Non-Hodgkin’s lymphoma, Hodgkin’s lymphoma, Waldenstro¨m, multiple myeloma Cirrhosis with portal hypertension Self-explaining AIDS and AIDS-related complex

Total Score (TS)

–

Age groups

Age Score (AS)

50–59 60–69 70–79 80–89 90–99

1 2 3 4 5

Notes: TIA, transient ischemic attack; CVA, cerbro-vascular accident; SLE, systemic lupus erythematosus; CML, chronic myeloid leukemia; CLL, chronic lymphoid leukemia; AML, acute myeloid leukemia; ALL, acute lymphoblastic leukemia; PV, polycythemia vera. Total combined score (TCS) = TS + AS.

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