Clinical characteristics and prognosis for delirium in Spanish internal medicine departments: An analysis from a large clinical-administrative database

Rev Clin Esp. 2019;219(8):415---423

Revista Clínica Española www.elsevier.es/rce

ORIGINAL ARTICLE

Clinical characteristics and prognosis for delirium in Spanish internal medicine departments: An analysis from a large clinical-administrative database夽 J. Marco a,∗ , M. Méndez a , A.J. Cruz-Jentoft b , J.L. García Klepzig a , E. Calvo a , J. Canora c , A. Zapatero c , R. Barba d a

Departmento de Medicina Interna, Hospital Clínico San Carlos, Madrid, Spain Servicio de Geriatría, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, Spain c Departamento de Medicina Interna, Hospital de Fuenlabrada, Fuenlabrada, Madrid, Spain d Departamento de Medicina Interna, Hospital Rey Juan Carlos, Móstoles, Madrid, Spain b

Received 27 December 2018; accepted 12 February 2019 Available online 3 May 2019

KEYWORDS Delirium; Prognosis; Mortality risk; Elderly; Internal medicine; Big data

Abstract Objectives: To investigate the prevalence of reported delirium and its associated factors and costs. Design: Retrospective and descriptive analysis of a national clinical-administrative database that includes all patients hospitalized in Spain in internal medicine departments from January 2007 to December 2014. Material and method: The study included the patients’ sociodemographic and clinical data (sex, age, diagnosis and procedures). Results: The prevalence of reported delirium was 2.5% (114,343 of 4,628,397 discharge reports). Delirium was most common in the 81---90-year age group (48%) and in institutionalized patients (4.5% vs. 2.9%; p < .001). The diagnoses most associated with delirium were dementia (14% vs. 7% for patients without delirium), cerebrovascular disease (17% vs. 11%), malnutrition (4% vs. 2%), pressure ulcers (4% vs. 2%), dysphagia (2% vs. 0.2%) and hyponatraemia (5% vs. 2%) (p < .001 in all cases). Patients with delirium also had longer mean stays (11.85 ± 13.15 days vs. 9.49 ± 11.17) and higher hospital mortality (OR: 1.41; 95% CI: 1.39---1.43; p = .0001). The costs attributable to delirium in 8 years exceeded D 100 million (almost D 1000 per hospitalization/patient). We developed a predictive model for the risk of developing delirium, which has insufficient sensitivity but is useful for identifying low-risk patients.

夽

Please cite this article as: Marco J, Méndez M, Cruz-Jentoft AJ, García Klepzig JL, Calvo E, Canora J, et al. Características clínicas noles: análisis de una gran base de datos clínicodel delirio y sus implicaciones pronósticas en los servicios de medicina interna espa˜ administrativa. Rev Clin Esp. 2019;219:415---423. ∗ Corresponding author. E-mail address: [email protected] (J. Marco). 2254-8874/© 2019 Elsevier Espa˜ na, S.L.U. and Sociedad Espa˜ nola de Medicina Interna (SEMI). All rights reserved.

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J. Marco et al. Conclusions: Patients who develop delirium during their hospitalization in internal medicine have a longer stay, greater mortality and an increased risk of being institutionalized at discharge. Delirium is probably poorly reported in the discharge reports prepared by internists. © 2019 Elsevier Espa˜ na, S.L.U. and Sociedad Espa˜ nola de Medicina Interna (SEMI). All rights reserved.

PALABRAS CLAVE Delirio; Pronóstico; Riesgo de mortalidad; Anciano; Medicina interna; Big data

Características clínicas del delirio y sus implicaciones pronósticas en los servicios de medicina interna espa˜ noles: análisis de una gran base de datos clínico-administrativa Resumen Objetivos: Investigar la prevalencia del delirio reportado, los factores asociados y los costes. Dise˜ no: Análisis retrospectivo y descriptivo de una base de datos clínico-administrativa nacional que incluye todos los pacientes ingresados en Espa˜ na en los servicios de medicina interna desde enero de 2007 a diciembre de 2014. Material y método: Se incluyen datos sociodemográficos y clínicos (sexo, edad, diagnóstico y procedimientos), entre otros. Resultados: La prevalencia del delirio reportado fue del 2,5% (114.343 de 4.628.397 informes de alta). El delirio fue más frecuente en el grupo de 81 a 90 a˜ nos (48%) y en pacientes institucionalizados (4,5% vs 2,9%; p < 0,001). Los diagnósticos más asociados al delirio fueron demencia (14% vs 7% en los sujetos sin delirio), enfermedad cerebrovascular (17% vs 11%), desnutrición (4% vs 2%), úlceras por presión (4% vs 2%), disfagia (2% vs 0,2%) e hiponatremia (5% vs 2%); p < 0,001 en todos los casos. También tuvieron una estancia media más larga: 11,85 (DE: 13,15) días vs 9,49 (DE: 11,17) días, y mortalidad intrahospitalaria más elevada (OR: 1,41; IC 95%: 1,39-1,43; p = 0,0001). El coste atribuible al delirio en 8 a˜ nos supera los 100 millones de euros (casi 1.000 D por ingreso/paciente). Elaboramos un modelo predictivo del riesgo de desarrollar delirio sin sensibilidad suficiente pero útil para identificar pacientes de bajo riesgo. Conclusiones: Los pacientes que desarrollan delirio durante su ingreso en medicina interna tienen una estancia más prolongada, mayor mortalidad y mayor riesgo de ser institucionalizados al alta. El delirio está probablemente poco reportado en los informes de alta que elaboran los internistas. © 2019 Elsevier Espa˜ na, S.L.U. y Sociedad Espa˜ nola de Medicina Interna (SEMI). Todos los derechos reservados.

Background Delirium is a clinical syndrome that typically affects hospitalized patients and institutionalized elderly individuals. The condition is characterized by acute cognitive impairment and a fluctuating inability to maintain attention. The prevalence of delirium varies depending on the study population, context and diagnostic criteria employed, with incidence rates ranging from 10% to 80%.1 The scarce studies that have prospectively analyzed delirium in Spain have reported a prevalence of approximately 20%.2,3 Delirium is frequently underreported in discharge reports, especially for polypathological patients with long diagnostic lists. This situation could reflect a failure in the diagnosis, coding errors or a truly low prevalence. This relatively low figure for the phenotype in the large clinical-administrative databases could reduce the credibility of prevalence rates reported through this pathway to determine the actual situation of delirium.4

Delirium in elderly hospitalized patients has been associated with severe adverse effects and an increase in hospitalization costs.5 A meta-analysis that investigated the mortality risk, institutionalization and dementia of elderly patients with delirium showed that delirium was an independent risk factor for these 3 events.6 Numerous studies have shown the efficacy of delirium prevention strategies, most of which are multidisciplinary and nonpharmacological. The success of these strategies, however, is far from ideal.7---11 The current recommendations on drug treatment reserve antipsychotics and other sedatives for risk situations for the patient or medical personnel or when other essential medical therapies can be interrupted.12 A recent meta-analysis supported multilevel interventions without clear evidence that melatonin or cholinesterase inhibitors were useful.1 Given the high prevalence of delirium in hospitalized patients and its negative impact on hospitalization and on patients who are subsequently institutionalized, we decided to employ the minimum basic data set (MBDS) to investigate the prevalence of delirium and its associated factors

Clinical characteristics and prognosis for delirium in Spain. The MBDS is a database that hospitals of Spain’s public health network must fill out and send to the Ministry of Health, Consumer Affairs and Social Welfare. The ultimate objective is to obtain a state standard, a collection of indicators that define the activity of Spain’s National Health System (SNHS) concerning the admissions classified using diagnosis-related groups (DRGs). The MBDS has been useful as a research tool in other studies conducted by the Clinical Management Workgroup of the Spanish Society of Internal Medicine.12---17 In this case, we employed data from more than 4.5 million discharges and more than 100,000 cases of delirium over a period of 8 years.

Methods We conducted a retrospective study that analyzed the information provided by the Ministry of Health, Social Services and Equality from the MBDS of the discharges of patients admitted to the internal medicine departments of SNHS hospitals between January 1, 2007 and December 31, 2014. The diagnoses and procedures were coded using the 5th edition of the International Classification of Diseases-9th Revision-Clinical Modification (ICD-9-CM). The discharge processes were grouped using the patient classification system All Patients Diagnosis-Related Groups (AP-DRG) (version 21). The MBDS data include the classification by hospital size; hospitalization conditions (1, emergency; 2, scheduled); and circumstances of discharge (1, to home, 2, transfer to another hospital, 3, voluntary discharge, 4, death). The main diagnosis according to the ICD-9 is the reason for admission after the examination of the patient (even when there were significant complications or new independent diagnoses that are recorded as secondary diagnoses). These secondary diagnoses (up to 12) can coexist with the main diagnosis. Each patient in our series was classified into a DRG, which are useful for classifying admissions by diagnosis and procedure under the assumption that patients with similar diagnoses consume similar resources and thereby incur similar expenses. Each DRG has a relative weight that reflects the intensity of resources consumed. To identify the patients with delirium, we selected the following ICD-9 codes: ICD-9-CM 298 or 293.5 as the primary or secondary diagnosis in any of the diagnosis fields of the discharge report. We calculated the Ch arlson comorbidity index (CCI)18,19 for each patient. This index is based on the ICD categories and reflects the number and severity of the comorbidities. The ICD has been adapted for use in clinical-administrative databases and assigns a weight (on a scale from 1 to 16), scoring up to 19 medical conditions. The final score ranges from 0 to 37 (a score ≥2 predicts a mortality >50% per year). Based on the ICD-9-CM, we identified the following risk factors in the primary and secondary diagnosis fields (ICD-9-CM codes shown in parentheses): pressure ulcer (707*), urinary tract infection (599.00, 590*, 646.60---49, 601), sepsis (038*, 995.91, 995.92), congestive heart failure (398.91, 404*, 402.11, 402.91, 428---428.9), peripheral arterial disease (440---448), dementia (290---290.9), cancer (140.0---172.9, 174.0---195.8, 200---208.9), metastatic cancer (196.0---199.99), cerebrovascular disease (430---438), malnutrition (260---263.9), colitis by Clostridium difficile

417 (008.45), upper gastrointestinal hemorrhage (530.2, 530.82, 531, 532*, 533* 534*, 535.10---60, 537.83), liver disease (571.0---571.99; 572.2---572.8), acquired immune deficiency syndrome (042.00, V08), septicemia by methicillin-sensitive Staphylococcus aureus (038.11), septicemia by methicillinresistant Staphylococcus aureus (038.12), bladder catheter (57.94), nasogastric tube (96.35), enteral nutrition (96.6), parenteral nutrition (99.15), gastrostomy (44.11, 44.19, 44.32) and palliative care consultation (V66.7).

Statistical analysis We performed a descriptive analysis of the patients included with the demographic and clinical variables, comparing the hospitalized patients with and without delirium. For the dichotomous variables, we employed the chi-squared test with Yates correction and Fisher’s exact test when the expected value in a cell was <5. For the quantitative variables, we employed Student’s t-test for independent samples. We analyzed the rate at which delirium was coded during the study period. Given that this was a government database, controlling the confounding variables was essential. For this reason, we performed a logistic regression analysis to determine the risk of mortality and readmission attributable to the presence of delirium after correcting for potential confounding factors such as age, Charlson index, sex and the presence of dementia. The OR and confidence intervals (CI) were calculated based on the coefficients of the regression indices. We also performed an estimate of the expenditure attributable to the presence of delirium during the hospitalization. To this end, we calculated the figure for the extra stay attributable to delirium, multiplying it by the cost for 1 day of hospitalization and then by the total number of episodes of delirium identified over the course of the study period. This operation enabled us to obtain a total expenditure figure, as well as the extra expenditure per patient. Using our data, we constructed a model for predicting the risk of developing delirium during the hospitalization using the presence or absence of the following variables during the hospitalization, as well as age and sex: diabetes, dementia, dysphagia, depression, malnutrition, hyponatremia, pneumonia, urinary tract infection, sepsis and admission from a nursing home. For our model, we calculated the calibration using the Hosmer---Lemeshow test and calculated the discriminatory capacity using a receiver operating characteristic curve. The threshold for statistical significance was set at p < .05. We employed the commercial software SPSS version 16 (SPSS Inc., Chicago, IL). The study was not evaluated by an ethics committee given that this was a completely anonymous computerized database with no possibility of linking the information to individuals.

Results We analyzed a total of 4,628,397 discharges by internal medicine departments during the study period (2007---2014) from all hospitals of the SNHS. We identified a diagnosis of delirium in 114,343 discharge reports (prevalence of 2.5%).

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Table 1 Analysis by age group of delirium in spanish internal medicine departments (2007---2014).

Annual cases of delirium 700000 600000 500000

Age group, years <50, n (%) 50---60, n (%) 61---70, n (%) 71---80, n (%) 81---90, n (%) 91---100, n (%) <100, n (%)

Delirium (n = 114,343)

No delirium (n = 4,513,026)

5886 (5%) 4358 (4%) 8834 (8%) 30,935 (27%) 51,074 (48%) 12,990 (11%) 266 (0.2%)

580,134 (13%) 346,466 (8%) 598,548 (13%) 1,295,759 (29%) 1,394,603 (31%) 292,504 (6.5%) 5012 (0.1%)

Data based on discharge reports of the minimum basic data set.

Of these, 14,925 cases had delirium as the primary diagnosis, and 99,418 had it as the secondary diagnosis. The patients with delirium were generally elderly (mean age, 79.0 ± 12.8 vs. 71.9 ± 16.9 years; p < .0001). With most cases of delirium in the 81---90-year age group (48% of all cases) (Table 1). The patients’ mean age increased over the course of the study period (76.6 years in 2007 vs. 80.3 years in 2014) as the number of cases coded per year increased. We found no significant differences by sex (47.4% vs. 47.8% in women; p = .053). Delirium was significantly more common in patients admitted from nursing homes (4.5% vs. 2.9%; p < .0001), and these patients were significantly more often

400000 300000 200000 100000 0 2007

2008

Figure 1

2009

2010

2011

2012

2014

Annual cases of delirium.

discharged to an institution than were the general population (4.3% vs. 1.2%). The diagnoses most commonly associated with delirium during the hospitalization were dementia (14% vs. 7%), depression (11.2% vs. 7.1%), cerebrovascular disease (17% vs. 11%), malnutrition (4% vs. 2%), pressure ulcers (4% vs. 2%), dysphagia (2% vs. 0.2%) and hyponatremia (5% vs. 2%) (p < .001 in all cases) (Table 2). The number of comorbidities (evaluated using the CCI) in the population with delirium increased over the study period. Figs. 1 and 2 show the temporal progression of the annual cases of delirium over the study period. Fig. 2 shows the comorbidity of the study population expressed according to the Charlson index for each year. The patients with delirium coded in their discharge report also had a higher rate of sepsis (5% vs. 3%), urinary

Table 2 Univariate analysis of the secondary diagnosis codes associated with delirium in the internal medicine departments (2007---2014).

Mean age, years (SD) Female, n (%) Mean stay, days (SD) Institutionalized, n (%) Charlson Comorbidity Index >2, n (%) Mean Charlson Comorbidity Index COPD, n (%) Diabetes, n (%) Heart failure, n (%) Anemia, n (%) Cerebrovascular disease, n (%) Pneumonia, n (%) Dementia, n (%) Chronic renal failure, n (%) Urinary tract infection, n (%) Neoplasia, n (%) Depression, n (%) Ischemic heart disease, n (%) Peripheral artery disease, n (%) Obesity, n (%) Chronic liver disease n (%) Sepsis, n (%) Hyponatremia, n (%) Malnutrition, n (%) Pressure ulcer, n (%) Dysphagia, n (%)

Delirium (n = 99,418)

No delirium (n = 4,527,938)

p

79.1 (12.8) 46,824 (47.1) 11.85 (13.15) 4460 (5) 21,818 (22) 1.69 35,059 (35) 29,602 (30) 22,350 (28) 18,208 (18) 17,167 (17) 13,794 (14) 13,466 (14) 13,164 (13) 11,819 (12) 11,044 (11) 7591 (8) 6275 (6) 5499 (6) 5465 (5) 5277 (5) 5129 (5) 4550 (5) 4017 (4) 3551 (4) 1838 (2)

71.9 (16.9) 2,147,066 (47.4) 9.49 (11.17) 130,891 (2.9) 958,885 (21) 1.56 165,037 (36) 1,273,451 (28) 1,070,044 (24) 754,272 (17) 502,048 (11) 486,834 (11) 334,478 (7) 497,157 (11) 299,332 (7) 502,839 (11) 286,239 (6) 377,869 (8) 250,784 (6) 361,408 (8) 249,405 (6) 135,949 (3) 94,362 (2) 84,849 (2) 104,619 (2) 37,360 (1)

.0001 .053 .0001 .0001 .0001

The comorbidities are shown in order of delirium frequency. Data based on discharge reports of the minimum basic data set.

.0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001 .478 .0001 .0001 .469 .0001 .0001 .003 .0001 .0001 .0001 .0001

Clinical characteristics and prognosis for delirium

419

Carlson index by year 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1 2005

2006

2007

2008

Figure 2

2009

2010

2011

2012

2013

2014

Carlson index by year.

tract infection (12% vs. 7%) and pneumonia (14% vs. 10.7%) (p < .0001) (Table 2). The patients with obesity had a lower likelihood of delirium that those without obesity (5% vs. 8%, p < .0001) (Table 2). Most of the risk factors we selected were associated in our series with the presence of delirium in the discharge report, with the exception of peripheral arterial disease and cancer. In terms of the analyzed procedures, we found significant differences between the population with and without delirium. Magnetic resonance imaging and the placement of urinary catheters, nasogastric tubes and central venous pathways were performed more often on the population with delirium. We found no significant differences in the transfusion of blood products, and computed tomography was performed less often in the population with delirium encoded in the discharge report. Finally, the patients with delirium had a significantly longer mean stay (11.85 ± 13.15 days vs. 9.49 ± 11.17, p < .0001) and a higher hospital mortality (12% vs. 10%, p < .0001). Daily hospitalization and internal medicine costs have been estimated at D 400 in Spain. Our study has shown a mean increase of 2.36 days in the length of stay attributable to delirium; each patient with delirium therefore incurred

an increase in costs of D 944 per hospitalization. With 114,343 episodes of delirium during the 8-year study period, the excess expenditures attributable to delirium increased to D 107,939,792 for the SNHS. The multivariate analysis showed that the development of delirium during hospitalization in our series was independently associated with age, the male sex and hyponatremia (OR, 2.05; 95% CI 1.94---2.06; p < .0001), dysphagia (OR, 1.65; 95% CI 1.57---1.73; p < .0001), malnutrition (OR, 1.75; 95% CI 1.7---1.81; p < .0001) and urinary tract infection (OR, 1.54; 95% CI 1.51---1.57; p < .0001) (Table 3). Originating from an institution (nursing home) also increased the risk of delirium (OR, 1.09; 95% CI 1.05---1.12; p < .0001). Delirium was also independently associated with the in-hospital mortality risk (OR, 1.41; 95% CI 1.39---1.43; p = .0001) after correcting for age and sex in the multiple logistic regression model (Table 4). In the analysis of the encoded procedures, bladder catheterization and nasogastric intubation were more common for the patients with delirium (Tables 5 and 6). By taking advantage of the considerable sample size, we constructed a model to predict the risk of developing delirium during hospitalization. This model reached a sensitivity of only 39.8% (false negatives, 60%) but had a much better specificity (80%). The AUC, however, was just acceptable (0.656). This result meant that our model was able to identify patients with a low risk of developing delirium but could not predict those with a high risk.

Discussion We have shown that 2.5% of patients hospitalized in Spanish internal medicine departments over an 8-year period had a delirium diagnosis coded in their discharge report and that this situation is associated with a significantly longer hospital stay and significantly greater mortality. We confirmed that numerous comorbidities and procedures, as well as living in an institution, are associated with the presence of delirium during the hospitalization.

Table 3 Logistic regression analysis of the comorbidities associated with delirium in Spanish internal medicine departments (2007---2014). Variable

Odds ratio

95% CI

p < .0001

Age Female sex Institutionalized Diabetes Dementia Dysphagia Depression Malnutrition Hyponatremia Pneumonia Urinary tract infection Sepsis

1.38 0.80 1.09 1.02 1.39 1.65 1.31 1.75 2.05 1.21 1.54 1.31

1.38---1.39 0.79---0.81 1.05---1.12 1008---1036 1.38---1.36 1.57---1.73 1.28---1.35 1.70---1.81 1.94---2.06 1.19---1.24 1.54---1.51 1.28---1.35

.0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001 .0001

Data based on discharge reports of the minimum basic data set.

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Table 4 Multiple logistic regression analysis of the association between death during hospitalization and delirium, age and sex in Spanish internal medicine departments (2007---2014). Variable

Odds ratio

95% CI

p < .0001

Age Male sex Delirium

1.104 1.02 1.54

1.104---1.105 1.019---1.026 1.52---1.57

.0001 .0001 .0001

Data based on discharge reports of the minimum basic data set.

Table 5 Univariate statistical analysis of the procedures associated with delirium in Spanish internal medicine departments (2007---2014).

Computed axial tomography Magnetic resonance imaging Transfusion of blood products Urinary catheter Nasogastric tube Central venous catheter

Delirium (n = 99,418)

No delirium (n = 4,527,938)

p

11,032 4886 5630 5139 501 3346

636,933 163,101 255,406 89,908 17,757 125,229

<.0001 <.0001 .476 <.0001 <.0001 <.0001

(11%) (5%) (6%) (5%) (0.5%) (3.4%)

(14%) (4%) (6%) (2%) (0.4) (2.8)

Data based on discharge reports of the minimum basic data set.

Table 6 Logistic regression analysis of the association between delirium during hospitalization and the use of urinary catheters, nasogastric tubes and central venous catheters in Spanish internal medicine departments (2007---2014). Variable

Odds ratio

95% CI

p < .0001

Urinary catheter Nasogastric tube Central venous catheter

2.682 1.282 1.221

2.606---2.761 1.173---1.402 1.179---1.264

.0001 .0001 .0001

Data based on discharge reports of the minimum basic data set.

Prevalence The prevalence of 2.5% in our study is lower than the recently reported 16.5% in a patient group with neurological conditions hospitalized in Spain4 and the 19.1% reported in an acute care medical ward of a general hospital.2 In the literature, the figures reach 50% of hospitalized patients at risk of delirium, with rates that vary according to the study population (mean age, comorbidities) and the scenario (hospital department, unit, residence).20 In our study, we obtained the information exclusively from the discharge report, and delirium was not detected systematically. These 2 facts are surely responsible, at least in part, for the low prevalence detected in our series. Delirium is probably underreported in discharge reports.

Factors associated with delirium Unlike other studies, we observed that delirium was not associated with an increased degree of comorbidity as evaluated by the adapted version of the CCI,1 although none of the other studies employed this index as a measure of comorbidity. A systematic literature review showed how the number of comorbidities was associated with the persistence of delirium at the time of and beyond the discharge.21

The independent factors associated with an increase in the presence of delirium in our series were related to age, residence (institutionalization), neuropsychiatric comorbidities (dementia and depression), metabolic comorbidities (diabetes, nutritional malnutrition and dysphagia), hydroelectrolytic disorders (hyponatremia) and infectious disorders (sepsis, urinary tract infections and pneumonia). These factors have been previously reported in hospitalized patients with delirium and can be considered as precipitating factors. A meta-analysis of 11 studies with a total of 2388 patients (411 participants and 1927 controls) identified the following factors: dementia, age, comorbidity, severity of the acute disease, infection, reduced activities of daily life, immobility, sensory impairment, bladder catheterization, urea and electrolyte disorders and malnutrition. In another prospective study, both previous dementia and the severity of the acute disease appeared as clear risk factors for developing delirium in patients older than 80 years hospitalized in internal medicine wards. The multivariate analysis identified infection and uremia as additional risk factors. The presence of more than 4 risk factors, hyponatremia, depression and previous functional deficit were only identified as risk factors in the univariate analysis.22,23 The analysis of the procedures performed by internal medicine departments show that patients with delirium are catheterized more often than

Clinical characteristics and prognosis for delirium the general population, a maneuver linked to delirium in other studies.24 Among the other procedures, only computed tomography is performed more often in the general population, which could suggest that delirium develops in a patient group especially susceptible to iatrogenesis. Among the other procedures, only computed tomography is performed more often in the general population, which could suggest that delirium develops in a patient group especially susceptible to iatrogenesis. It is worth asking, however, whether instrumentalization and the excess of procedures undergone by these patients are the cause or consequence of the delirium they develop. Of course, our study was not designed to answer this question. However, a number of the measures taken with these patients can lead to excessive instrumentalization and should be avoided (e.g., clamping measures that lead to a loss of pathways, phlebitis [sometimes septic] and the need for placing central venous pathways). The progression of confusional syndromes to frank delirium can prevent sufficient feeding and precipitate bronchoaspiration or the need for an artificial feeding tube. There is only one solution for this: early identification and prevention of at-risk patients. For elderly hospitalized patients, depressive symptoms, cognitive impairment and dementia are known risk factors for developing delirium. Malnutrition frequently occurs in patients with cognitive impairment, even those with mild impairment, and is associated with an increased risk of developing delirium during the hospitalization.25---28 Hyponatremia and infections are the most common acute conditions associated with the development of intrahospital delirium in elderly patients. This information could be useful for identifying patients at risk and implementing more rigorous measures aimed at prevention. Delirium is a marker of cognitive frailty and of a poor outcome of hospitalization. According to previous studies,4,29 the presence of delirium lengthens the stay and thereby increases the hospitalization costs. The importance of delirium might continue to be underestimated while its social and economic implications continue to be undocumented.30 Current estimates suggest that this disease complicates the hospitalizations of more than 2.3 million elderly individuals annually in the United States, representing 17.5 million days of hospitalization for a total amount exceeding 4 billion dollars.7 In our study, the excess costs attributable to delirium in 8 years exceeded D 100 million, with a mean of almost D 1000 per hospitalization/patient. A study on patients older than 65 years hospitalized for acute disease showed that delirium present at admission behaved as an independent risk factor for hospital mortality and mortality at 3 months of discharge.7 A systematic review and meta-analysis of 42 studies on critically ill patients with delirium showed that delirium was associated with increased mortality risk, institutionalization and dementia.31 In our study, the mean age of the patients with delirium increased over the study period. The comorbidities evaluated with the CCI also increased. Delirium in many cases can be interpreted as the consequence of hospitalization for patients with internal (comorbidities) and external risk factors (hospitalization-related). Numerous strategies aimed at mitigating the severe repercussions of delirium have been attempted; however, the initial experiences were not favorable.8,9,5 More recent

421 studies have achieved somewhat better efficacy, although the evidence is still limited.32 It is also important to note that errors in treating these patients can also lead to the development of this condition.33

Predictive model Our predictive model did not achieve the desired objective. However, the model showed a good capacity for identifying patients at low risk of developing delirium during the hospitalization. A significant number of predictive scales and models have been published for identifying patients at risk. In postsurgical patients, the preoperative situation is the best predictor, and age behaves as an independent factor. Postsurgical delirium is 4 times more common in emergency surgery than in elective surgery.34 In elderly patients in general, incidental delirium is independently associated with a poorer functional state (Barthel index) and dehydration (creatinine-urea ratio).35 However, we still lack a good model to identify medical patients with a high risk of delirium. Prevention measures and improving the early diagnosis are the first steps in treating delirium in Spanish internal medicine departments, where the mean age has exceeded 74 years and the CCI approaches 5.36 Multilevel interventions (pharmacological, environmental and rehabilitative) have been shown to be the most effective when resolving this condition.

Limitations Our study does not lack limitations. As with any retrospective study based on clinical-government data, it is safe to say that not all diagnoses of delirium were correctly included. Considering the low prevalence observed in our study, it is more than likely that a considerable number of cases were not registered, A problem that has already been reported in other studies with large databases.4 Having numerous comorbidities is not uncommon in patients hospitalized in internal medicine (22% of our series had a CCI > 2), Which would explain why the diagnosis of intrahospital delirium can go unreported or be considered a minor diagnosis in hospitalized patients with severe acute processes and a considerable number of complications. In any case, one of the strengths of our study is the considerable sample size and statistical power it confers. We had access to more than 4.5 million discharge reports and more than 100,000 episodes of delirium over the course of 8 years, a number rarely accessible among publications on this topic.

Conclusions Our analysis of an extensive clinical-government database of more than 4.5 million discharges and 100,000 episodes of delirium in patients hospitalized in internal medicine departments in Spain over 8 years shows that these patients are older than other hospitalized patients, have a longer mean stay and have greater mortality. Institutionalization was associated with a greater prevalence of delirium and a greater possibility of being

422 discharged to an institution than the rest of the hospitalized population. Unlike other studies, we found that the patients with a higher level of comorbidities (measured by the CCI) did not have a greater risk of developing delirium. Delirium is infracoded and likely underreported in the discharge reports prepared by internists. This issue needs improvement in the management of this disease, which currently lacks prevention and whose negative repercussions represent patient suffering and death and healthcare system expenditures.

Funding This research study received no grant or financial assistance from funding agencies of the public, private or commercial sector.

Conflicts of interest None of the authors are subject to conflicts of interest concerning this article.

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