Journal of Affective Disorders 169 (2014) 170–178

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Bipolar disorder and comorbidity: Increased prevalence and increased relevance of comorbidity for hospital-based mortality during a 12.5-year observation period in general hospital admissions Dieter Schoepf a,n, Reinhard Heun a,b a b

Department of Psychiatry, University of Bonn, D-53105 Bonn, Germany Department of Psychiatry, Radbourne Unit Royal Derby Hospital, Uttoxeter Road, Derby, United Kingdom

art ic l e i nf o

a b s t r a c t

Article history: Received 1 May 2014 Received in revised form 26 July 2014 Accepted 6 August 2014 Available online 26 August 2014

Background: Bipolar disorder (BD) is associated with an increase of psychiatric and physical comorbidities, but the effects of these disorders on general hospital-based mortality are unclear. Consequently, we investigated whether the burden of comorbidity and its relevance on hospital-based mortality differed between individuals with and without BD during a 12.5-year observation period in general hospital admissions. Methods: During 1 January 2000 and 30 June 2012, 621 individuals with BD were admitted to three General Manchester Hospitals. All comorbidities with a prevalence Z1% were compared with those of 6210 randomly selected and group-matched hospital controls of the same age and gender, regardless of priority of diagnoses. Comorbidities that increased the risk for hospital-based mortality (but not mortality outside of the hospitals) were identified using multivariate logistic regression analyses. Results: Individuals with BD had a more severe course of disease than controls that was associated with a higher total number of in-hospital deaths. Individuals with BD compared to controls had a substantial higher burden of comorbidities, the most frequent comorbidities included asthma, type-2 diabetes mellitus (T2DM), and alcohol dependence. 18 other diseases with a surplus of diabetes related complications were also increased. Fourteen comorbidities contributed to the prediction of hospitalbased mortality in univariate analyses. Risk factors for hospital-based mortality in multivariate analyses were ischemic stroke, pneumonia, bronchitis, chronic obstructive pulmonary disease, T2DM, and hypertension. The impact of T2DM on hospital-based mortality was higher in individuals with BD than in controls. Limitations: The study design was not assigned to assess the type of BD, the current bipolar status, and if individuals with BD were treated with medication. It was neither possible to compare drug effects, nor to compare the adherence to treatment between samples. Conclusion: In one of the largest samples of individuals with BD in general hospitals, the excess comorbity in individuals with BD compared to controls is in particular caused by asthma and T2DM. T2DM and its complications cause significant excess hospital-based mortality in individuals with BD. & 2014 Elsevier B.V. All rights reserved.

Keywords: Bipolar disorder Comorbidity General hospitals Mortality Risk factors

1. Introduction Bipolar disorder (BD) is a major affective disorder that is characterized by extreme mood fluctuations from euphoria to severe depression, interspersed with periods of euthymia. BD affects about 3.7% of the general population (Hirschfeld et al., 2003). Its complexity in treatment is partly caused by higher comorbidity compared to the general population. In a crosssectional US-sample, more than 41% of middle-aged individuals

n

Correspondence to: Tel.: þ 49 228 287 16566. E-mail address: [email protected] (D. Schoepf).

http://dx.doi.org/10.1016/j.jad.2014.08.025 0165-0327/& 2014 Elsevier B.V. All rights reserved.

with BD had at least three physical comorbidities (Carney and Jones, 2006), and 5.9% of the sample had type-2 diabetes mellitus (T2DM). The overall prevalence of detected diabetes mellitus in the general population in high-income countries is around 3–4%. T2DM accounts for 85–95% of all diabetics (International Diabetes Federation, 2003). A study from the Maritime Provinces of Canada that investigated risk factors between diabetic and non-diabetic individuals with BD found that diabetic individuals with BD were on an average 10 years older (52.5 vs. 42.8 years), more obese, had higher body mass indices, suffered more from hypertension, and had higher rates of rapid cycling (Ruzickova et al., 2003). A pooled analysis from multiple randomized double-blind medication trials of 1362 non-diabetic individuals with BD showed that T2DM

D. Schoepf, R. Heun / Journal of Affective Disorders 169 (2014) 170–178

emerged in 1.3% with a median time of 63 days. This group was more obese, older, had higher non-fasting glucose levels, suffered more hypertension, and had more often a non-Caucasian ethnicity (Morriss and Mohamed, 2005). Mortality studies report the all cause mortality in BD to be two times increased compared to the general population. Complete suicide occurs in 10–15% of cases, which is usually more pronounced at younger ages and in the first year after the initial diagnosis (Ösby et al., 2001). Other risk factors for premature death represent physical diseases that are either related to intravenous street drug use of younger individuals with BD such as HIV and hepatitis C infections or to physical diseases that usually become prevalent in older individuals with BD (Beyer et al., 2005). A representative Swedish national-cohort study found that adults with BD died prematurely from multiple causes, including cardiovascular disease (CVD), diabetes, chronic obstructive pulmonary disease (COPD), influenza or pneumonia, unintentional injuries, and suicide (Crump et al., 2013). Knowledge of specific diseases that are risk factors for general hospital-based mortality in adults with BD is of clinical relevance to intensify efforts that aim of the reduction of avoidable mortality. 1.1. Aim of study The aim of this study is to evaluate in a representative general hospital-based sample if the prevalences of various psychiatric and physical diseases and their impact on hospital-based mortality differ between individuals with BD and hospital controls. Four specific hypotheses were tested. (1) Individuals with BD have a more severe course of disease during the observation period than controls, i.e. individuals with BD compared to controls (i) are more often admitted as emergencies at their initial hospitalization, (ii) have an extended length of hospital stay at their initial hospitalization, (iii) have a higher total number of admissions during the observation period, and (iv) have a higher total number of in-hospital deaths. (2) The prevalences of various psychiatric and physical comorbidities are increased in individuals with BD compared to controls. (3) Various, but not all physical comorbidities contribute to the prediction of hospital-based mortality in individuals with BD and controls. (4) The impact of some physical comorbidities on hospital-based mortality is higher in individuals with BD than in controls.

2. Methods 2.1. Sample definitions The initial sample included all individuals (n¼369,488) that were admitted for hospital treatment in three General Manchester Hospitals between January 1, 2000, and June 30, 2012. The selected sample under investigation consisted of all 621 individuals with BD that were hospitalized during the observation period (n¼621, Table 1). The inclusion criteria were diagnosis of BD, age 18 years or above and hospital care for at least 24 h. All BD outpatient treatment cases and all BD partial hospitalization treatment cases (day treatment only) for 24 h or less were excluded. The subsample of deceased individuals with BD included all 60 individuals with BD that died in any of the three hospitals during the study period (n¼60, Table 1). The subsample of individuals with BD who survived included those individuals with BD that did not die in any of the three hospitals during the observation period (n¼ 561, Table 1). A control sample was identified to equalize age and gender distributions by group-matching each adult with BD at initial admission with 10 randomly selected hospital controls of the same gender and age (71 year; n¼ 6210, Table 1), using SPSS version 20.0. The subsample of deceased controls included the controls that

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died in any of the three hospitals during the observation period (n¼520, Table 1). The subsample of control survivors included the controls that did not die in any of the three hospitals during the observation period (n¼ 5690, Table 1). 2.2. Sampling strategy and definitions of clinical course parameters Anonymous information of discharge diagnoses were received from the computerized hospital activity analysis register. Vital status concerning in-hospital death up to June 30, 2012 was determined by record linkage to the National Health Tracing Services. The general hospital mortality data were crosschecked against the hospital case records and patient information system. For each patient, follow-up was commenced at initial admission to hospital treatment from January 1, 2000, up to June 30, 2012. A distinction was drawn between hospitalization as an emergency case or other at initial admission during the observation period. The length of hospital stay was defined as the number of inpatient days at initial admission during the observation period. Readmissions occurring within one day after discharge were counted to the corresponding hospitalization. The number of hospital stays was defined as the total number of hospitalizations within the observation period. Length of follow-up was defined as days from initial hospitalization until the day of in-hospital death in the subgroups of deceased individuals respectively until the end of the observation period in the subsamples of surviving individuals, i.e. June 30, 2012. Confidentiality of information was maintained in accordance with the UK Data Protection Act. The patient information was anonymous and non-identifiable when received by the team. Local research approval was obtained. 2.3. Recording of diagnoses BD was diagnosed according to ICD-10 categories F30.x-F31.x by senior physicians responsible for the formulation of the individual treatment plan if mood episodes from other conditions were excluded. If a differential psychiatric diagnosis had to be ruled out, an external psychiatrist was consulted and the recommended clinical investigations were performed. The ICD-10 coding system has been proven largely free of errors for definitive diagnoses, although errors are found in the coding of nonspecific diagnoses (George and Maddock, 1979; Schoepf et al., 2003; Phung et al., 2007). As the study was planned naturalistically with high subject numbers no structured interviews were available and no reliable assessment of the type of BD as well as of the current bipolar status was available. A comorbid disease was defined as any discharge diagnosis of a psychiatric or physical disease except BD during any stay. To achieve sufficient statistical power and clinical relevance we focussed only on comorbidities that appeared in at least 1% of the initial sample. The study design did not allow differentiating if the comorbid disease may cause, may be caused by, or may be otherwise related to another disease in the same patient. 2.4. Data analysis SPSS version 20.0 was used for data analysis. The Student's t test and chi-square analysis were applied for sample and subsample comparisons of sociodemographic and clinical course characteristics. Chi-square analysis was applied for sample and subsample comparisons of comorbidities. Odds ratios (ORs) for comorbidities were calculated by univariate analyses to allow comparisons with other studies. 95% confidence intervals [CIs] were provided. As the effect of comorbidity on hospital-based mortality over time may not have been proportional to the hazard over time to allow for Cox regression analysis, consequently

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Table 1 Sociodemographic and clinical characteristics of the initial sample subdivided into bipolar sample and control sample. Characteristics

Initial sample Bipolar sample

Sociodemographic description Number, N (%) Mean age, years 7 SD Female gender, N (%) Marital status (married), N (%) Caucasian ethnicity, N (%) South Asian ethnicity, N (%) Afro-Caribbean ethnicity, N (%) Unknown ethnicity, N (%) Clinical description Initial admission (emergency), N (%) Length of hospital stay at initial hospitalization during 2000–2012, days 7SD Mean number of admissions, N Average length of follow-up, days7 SD

Control sample

All

Deceased

Survivors

All

Deceased

Survivors

621 (100) 47.3 7 0.7 366 (58.9) 133 (21.4)nnn 505 (81.3)nnn 23 (3.7)nnn 27 (4.3)nnn 66 (10.6)

60 (9.7) 65.2 7 1.8 (1)nn 111 (43.5) 17 (28.3) (1)nn,(2)n 48 (80.0) (1)n 3 (5.0) (1)n 3 (5.0) (1)n ND

561 (90.3) 45.4 7 0.7 255 (41.0) 116 (20.7) 457 (81.5) 20 (3.6) 24 (20.7) ND

6210 (100) 47.3 7 0.2 3660 (58.9) 2537 (40.9) 4410 (71.0) 536 (8.6) 317 (5.1) 947 (15.3)

520 (8.4) 66.37 0.6nnn 240 (46.2)nnn 246 (47.3)nnn 425 (81.7)nnn 18 (3.5)nnn 11 (2.1)nnn ND

5690 (91.6) 45.6 7 0.2 3420 (60.1) 2333 (41.0) 3985 (70.0) 518 (9.1) 306 (5.4) ND

419 (67.5)nnn 5.7 7 0.8nnn

41 (68.3) (2)nn 13.2 72.7(1)nn

378 (67.4) 5.0 7 0.8

2712 (43.7) 3.2 70.2

204 (39.2) 10.9 71.1nnn

2466 (43.3) 2.5 7 0.1

12.0nnn 18147 54.0nnn

19.8 (1)nnn, (2)nnn 14107 176 (1)n, (2)n

11.2 18577 56.5

6.4 70.1 21517 17.5

8.5 nnn 992 7 45.7nnn

6.2 22577 18.0

Stars indicate in the first column sample comparisons between all individuals with BD and all controls, in the second column subsample comparisons (1) between deceased individuals with BD and individuals with BD who did not die in any of the three hospitals and (2) between deceased individuals with BD and deceased controls, in the fifth column subsample comparisons between deceased controls and control survivors. ND¼ no data. n

pr 0.05. p r0.01. nnn p r0.001. nn

multivariate forward logistic regression analysis with in-hospital death as dependent variable was used to identify possible comorbidities that were risk factors for hospital-based mortality. Covariates included various comorbidities taking into consideration colinearity and clinical plausibility. To test the robustness of the findings a multivariate backward logistic regression analysis was carried out. A potential risk factor for hospital-based mortality was defined as any comorbidity that contributed to the prediction of in-hospital death. P-values were calculated two-tailed; p o0.05 was taken as significant. No adjustments were made for multiple comparisons to allow the comparison of this study with similar studies. Impact was defined as the strength and significance of an association. The strength of associations between comorbidities in individuals with BD and controls was compared by the ORs and the significance of associations between comorbidities in individuals with BD and controls was compared using 95% CIs (Schoepf et al., 2012, 2014a, 2014b; Heun et al., 2013).

3. Results 3.1. Sociodemographic and clinical course descriptions of samples The demographic and clinical course characteristics are outlined in Table 1. The mean age at initial hospitalization was 47.3 years in the BD sample, 45.4 years in surviving individuals with BD, and 65.2 years in later deceased individuals with BD. A lower proportion of individuals with BD was married compared to controls. The proportion of Caucasians was higher in individuals with BD than in controls. Accordingly, the proportions of South Asians and of Afro-Caribbeans were lower in the BD sample than in the control sample. The duration of follow-up was 1814 days in the BD sample and 2151 days in the control sample. Appropriately, the duration of follow-up differed between the subsamples of deceased and surviving subjects as a consequence of different mortality rates (Table 1, last row). In agreement with our first hypothesis, individuals with BD had a more severe course of disease than controls: they (i) were more likely admitted as emergencies at their initial hospitalization, (ii) had

an extended length of hospital stay at initial hospitalization, (iii) had a nearly two-fold higher number of total hospitalizations, and (iv) had an increased total number of in-hospital deaths between January 1, 2000 and June 30, 2012. Crude hospital-based mortality rates were 9.7% in the BD sample and 8.4% in the control sample. 3.2. Prevalences of comorbid diseases and of suicidal and parasuicidal events In agreement with our second hypothesis, individuals with BD had an excess comorbidity of 21 diseases compared to controls (Table 2). Of all mental comorbidities, alcohol dependence accounted for 8.1% in individuals with BD. The following most common mental comorbidities in the BD sample were anxiety disorder (4.2%) in the form of either generalized anxiety disorder or panic disorder, and opioid dependence (2.6%). The three most common physical comorbidities in individuals with BD were asthma (14.5%), T2DM (12.6%), and COPD (7.6%). Furthermore, the prevalences of 15 other physical comorbidities and of suicidal and parasuicidal events were increased in individuals with BD compared to controls. In contrast, the prevalence of cataract was reduced in individuals with BD compared to controls. Twenty other comorbidities were equally common in both samples. 3.3. Disease contributors to hospital-based mortality (univariate comparisons) In agreement with our third hypothesis, 14 comorbidities contributed to the prediction of hospital-based mortality in univariate comparisons of the prevalence of individual diseases between deceased individuals with BD and individuals with BD that did not die in any of the three hospitals (Table 3). Of all comorbidities, hypertension contributed to 35.0% of the prediction of hospitalbased mortality in the BD sample. The subsequent most prevalent contributing comorbidities to hospital-based mortality in individuals with BD were T2DM (25%), COPD (21.7%), pneumonia (16.7%), bronchitis (15%), and ischemic stroke (10%). In addition, five diabetes related complications (respiratory failure, atrial fibrillation, peripheral

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Table 2 Prevalences (%) and odds-ratios (ORs) of comorbidities and of suicidal and parasuicidal events in 621 individuals with bipolar disorder and 6210 controls. Comorbidities, suicidal, and parasuicidal events registered in discharge records 2000–2012

Initial sample Bipolar sample

Control sample

Odds ratio

N/621, (100%)

N/6210, (100%)

[CI-95%], p

Increased prevalences of comorbid diseases and of suicidal- and parasuicidal events in individuals with bipolar disorder Overdose with suicidal intent 71 (11.4) 45 (0.7) Parasuicide 74 (11.9) 47 (0.8) Non-specific dementia 10 (1.6) 18 (0.3) Parkinsonism 7 (1.1) 13 (0.2) Respiratory failure 12 (1.9) 24 (0.4) Opioid dependence 16 (2.6) 32 (0.5) Epilepsy 40 (6.4) 83 (1.3) Anxiety disorder (GAD or PD) 26 (4.2) 58 (0.9) Alcohol dependence 50 (8.1) 137 (2.2) Cellulitis 16 (2.6) 42 (0.7) Duodenal ulcer 6 (1.0) 16 (0.3) Pneumonia 24 (3.9) 72 (1.2) Duodenitis 7 (1.1) 22 (0.4) COPD 47 (7.6) 162 (2.6) Bronchitis 25 (4.0) 83 (1.3) Hypothyroidism 38 (6.1) 139 (2.2) Ischemic stroke 11 (1.8) 51 (0.8) Obesity 15 (2.4) 70 (1.1) Asthma 90 (14.5) 462 (7.4) Irritable bowel syndrome 10 (1.6) 49 (0.8) Gallbladder calculus 12 (1.9) 60 (1.0) Gastritis 14 (2.3) 75 (1.2) Type-2 diabetes mellitus 78 (12.6) 499 (8.0)

17.7 [12.1–26.0]nnn 17.7 [12.2–25.8]nnn 5.6 [2.6–12.3]nnn 5.4 [2.2–13.7]nnn 5.1 [2.5–10.2]nnn 5.1 [2.8–9.4]nnn 5.1 [3.5–7.5]nnn 4.6 [2.9–7.4]nnn 3.9 [2.8–5.4]nnn 3.8 [2.2–7.0]nnn 3.8 [1.5–9.7]nn 3.4 [2.1–5.5]nnn 3.2 [1.4–7.5]nn 3.1 [2.2–4.3]nnn 3.1 [2.0–4.9]nnn 2.9 [2.0–4.1]nnn 2.2 [1.1–4.2]n 2.2 [1.2–3.8]nn 2.1 [1.7–2.7]nnn 2.1 [1.0–4.1]n 2.0 [1.1–3.8]n 1.9 [1.1–3.4]n 1.6 [1.3–2.1]nnn

Decreased prevalences of comorbid diseases in individuals with bipolar disorder Cataract

30 (4.8)

496 (8.0)

0.6 [0.4–0.9]nn

No difference of prevalence of comorbid diseases Alcoholic liver disease Angina Atrial fibrillation Chronic kidney disease Chronic pancreatitis Constipation Diverticular disease Gastro-oesophageal reflux disease Heart failure Hyperlipidaemia Hypertension Iron deficiency anemia Lung cancer Myocardial infarction Peripheral vascular disease Phobic disorders Previous myocardial infarction Renal failure Rheumatoid arthritis Type-1 diabetes mellitus

6 (1.0) 40 (6.4) 15 (2.4) 10 (1.6) 6 (1.0) 9 (1.4) 10 (1.6) 14 (2.3) 21 (3.4) 57 (9.2) 120 (19.3) 10 (1.6) 6 (1.0) 17 (2.7) 12 (1.9) 8 (1.3) 10 (1.6) 8 (1.3) 8 (1.3) 11 (1.8)

29 (0.5) 523 (8.4) 219 (3.5) 58 (0.9) 26 (0.4) 57 (0.9) 65 (1.0) 107 (1.7) 135 (2.2) 543 (8.7) 1188 (19.1) 62 (1.0) 31 (0.5) 193 (3.1) 81 (1.3) 40 (0.6) 115 (1.9) 47 (0.8) 42 (0.7) 112 (1.8)

2.1 [0.9–5.0] 0.8 [0.5–1.0] 0.7 [0.4–1.2] 1.7 [0.9–3.4] 2.3 [1.0–5.7] 1.6 [0.8–3.2] 1.6 [0.8–3.0] 1.3 [0.8–2.3] 1.6 [1.0–2.5] 1.1 [0.8–1.4] 1.0 [0.8–1.3] 1.6 [0.8–3.2] 2.0 [0.9–4.7] 0.9 [0.5–1.5] 1.5 [0.8–2.8] 2.0 [0.9–4.3] 0.9 [0.5–1.7] 1.7 [0.8–3.6] 1.9 [0.9–4.1] 1.0 [0.5–1.8]

In the first and the second section the ranking of comorbidities is carried out in descending order of ORs in the bipolar sample. In the third section comorbidities are ranked in alphabetic order. Stars indicate comparisons among individuals with bipolar disorder and controls. COPD¼ chronic obstructive pulmonary disease, GAD ¼generalized anxiety disorder, PD ¼ panic disorder. n

pr 0.05. p r0.01. nnn p r 0.001. nn

vascular disease, heart failure, myocardial infarction) contributed to hospital-based mortality in deceased individuals with BD, many of them with highly elevated ORs. Noticeably, suicidal and parasuicidal events did not contribute to hospital-based mortality in individuals with BD, indicating that suicidal individuals with BD may have been transferred earlier to sufficient treatment. 3.4. Risk factors for hospital-based mortality (multivariate comparisons) Table 4 represents the risk factors for hospital-based mortality according to multivariate analyses, i.e. specific diseases that explain

the outcome of in-hospital deaths. Risk factors for hospital-based mortality in the BD sample were ischemic stroke, pneumonia, bronchitis, COPD, T2DM, and hypertension. In agreement with our fourth hypothesis, T2DM had a greater impact on hospital-based mortality in the BD sample than in the control sample: (i) in the 60 deceased individuals with BD, the prevalence of T2DM was significantly elevated (25.0%) compared to the prevalence of T2DM in those 561 individuals with BD that did not die in the hospitals (11.2%); (ii) deceased individuals with BD had significantly more suffered from T2DM (25%) than deceased controls (14.6%); (iii) in controls T2DM did not contribute to explain the outcome of in-hospital deaths in multivariate analyses. The other five mortality risk factors had an equal

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Table 3 Disease contributors to hospital-based mortality. Each prevalence of a comorbid disease (%) and of suicidal and parasuicidal events (%) is compared between the subsample of deceased individuals and its respective subsample of survivors, i.e. individuals that did not die in any of the three hospitals during the observation period. Odd ratios (ORs) and 95%-CIs are univariate and not controlled for the various comorbidities to allow comparisons with other studies. In the first section, comorbidities are ranked in descending order of ORs with regard to the bipolar sample, in the second section with regard to the control sample. In the third section non-contributing comorbidities to hospital-based mortality are ranked in alphabetic order. Univariate comparisons

Initial sample Bipolar sample N/621 (100%) Survivors N/561, (90.3%)

Deceased N/60, (9.7%)

Control sample N/6210 (100%) Odds ratio [95%-CI], p

Survivors N/5690, (91.6%)

Deceased N/520, (8.4%)

Odds ratio [95%-CI], p

Disease contributors to hospital-based mortality in individuals with bipolar disorder (that also significantly contributed to in-hospital death in controls) Ischemic stroke 5 (0.9) 6 (10.0) 12.4 [3.7–41.8]nnn 28 (0.5) 23 (4.4) 9.4 [5.4–16.4]nnn Lung cancer 3 (0.5) 3 (5.0) 9.9 [1.9–49.6]nnn 11 (0.2) 20 (3.8) 20.7 [9.8–43.3]nnn Pneumonia 14 (2.5) 10 (16.7) 7.8 [3.3–18.5]nnn 44 (0.8) 28 (5.4) 7.3 [4.5–11.8]nnn Respiratory failure 7 (1.2) 5 (8.3) 7.2 [2.2–23.4]nnn 10 (0.2) 14 (2.7) 15.7 [7.0–35.6]nnn Non-specifc dementia 6 (1.1) 4 (6.7) 6.6 [1.8–24.1]nnn 9 (0.2) 9 (1.7) 11.1 [4.4–28.1]nnn Bronchitis 16 (2.9) 9 (15.0) 6.0 [2.5–14.3]nnn 56 (1.0) 27 (5.2) 5.5 [3.5–8.8]nnn Atrial fibrillation 10 (1.8) 5 (8.3) 5.0 [1.7–15.2]nn 164 (2.9) 55 (10.6) 4.0 [2.9–5.5]nnn Peripheral vascular disease 8 (1.4) 4 (6.7) 4.9 [1.4–16.9]nn 54 (0.9) 27 (5.2) 5.7 [3.6–9.2]n COPD 34 (6.1) 13 (21.7) 4.3 [2.1–8.7]nnn 104 (1.8) 58 (11.2) 6.7 [4.8–9.4]nnn Iron deficiency anemia 7 (1.2) 3 (5.0) 4.2 [1.5–16.6]n 52 (0.9) 10 (1.9) 2.1 [1.1–4.2]n Heart failure 16 (2.9) 5 (8.3) 3.1 [1.1–8.8]n 76 (1.3) 59 (11.3) 9.5 [6.6–13.5]nnn Myocardial infarction 13 (2.3) 4 (6.7) 3.0 [1.0–9.6]n 156 (2.7) 37 (7.1) 2.7 [1.9–3.9]nnn T2DM 63 (11.2) 15 (25.0) 2.6 [1.4–5.0]nn 423 (7.4) 76 (14.6) 2.1 [1.6–2.8]nnn Hypertension 99 (17.6) 21 (35.0) 2.5 [1.4–4.6]nnn 1017 (17.9) 171 (32.9) 2.3 [1.9–2.7]nnn Disease contributors to hospital-based mortality in controls (that did not significantly contribute to in-hospital death in individuals with bipolar disorder) Alcoholic liver disease 5 (0.9) 1 (1.7) 1.9 [0.2–16.4] 17 (0.3) 12 (2.3) 7.9 [3.7–16.6]nnn Renal failure 7 (1.2) 1 (1.7) 1.3 [0.2–11.1] 29 (0.5) 18 (3.5) 7.0 [3.9–12.7]nnn Chronic kidney disease 8 (1.4) 2 (3.3) 2.4 [0.5–11.5] 39 (0.7) 19 (3.7) 5.5 [3.2–9.6]nnn Duodenal ulcer 6 (1.1) 0 (0.0) – 11 (0.2) 5 (1.0) 5.0 [1.7–14.5]nnn Rheumatoid arthritis 7 (1.2) 1 (1.7) 1.3 [0.2–11.1] 30 (0.5) 12 (2.3) 4.5 [2.3–8.8]nnn Cellulitis 14 (2.5) 2 (3.3) 1.4 [0.3–6.1] 33 (0.6) 9 (1.7) 3.0 [1.4–6.3]nn Previous myocardial infarction 9 (1.6) 1 (1.7) 1.0 [0.1–8.4] 92 (1.6) 23 (4.4) 2.8 [1.8–4.5]nnn Constipation 7 (1.2) 2 (3.3) 2.7 [0.6–13.4] 46 (0.8) 11 (2.1) 2.7 [1.4–5.2]nn Cataract 26 (4.6) 4 (6.7) 1.5 [0.5–4.4] 415 (7.3) 81 (15.6) 2.5 [1.8–3.0]nnn T1DM 10 (1.8) 1 (1.7) 0.9 [0.1–7.4] 92 (1.6) 20 (3.8) 2.4 [1.5–4.0]nnn Angina 38 (6.8) 2 (3.3) 0.5 [0.1–2.0] 443 (7.8) 80 (15.4) 2.2 [1.7–2.8]nnn Comorbidities that did not significantly contribute to hospital–based mortality Alcohol dependence 47 (8.4) 3 (5.0) 0.6 [0.2–1.9] Anxiety disorder (GAD or PD) 26 (4.6) 0 (0.0) – Asthma 83 (4.8) 7 (11.7) 0.8 [0.3–1.7] Chronic pancreatitis 6 (1.1) 0 (0.0) – Diverticular disease 8 (1.4) 2 (3.3) 2.4 [0.5–11.5] Duodenitis 6 (1.1) 1 (1.7) 1.6 [0.2–13.3] Epilepsy 37 (6.6) 3 (5.0) 0.8 [0.2–2.5] Gallbladder calculus 11 (2.0) 1 (1.7) 0.9 [0.1–6.7] Gastritis 14 (2.5) 0 (0.0) – Gastro-oesophogeal reflux 14 (2.5) 0 (0.0) – Hyperlipidaemia 55 (9.8) 2 (3.3) 0.3 [0.1–1.3] Hypothyroidism 33 (5.9) 5 (8.3) 1.5 [0.6–3.9] Irritable bowel syndrome 10 (1.8) 0 (0.0) – Obesity 15 (2.7) 0 (0.0) – Opioid dependence 16 (2.9) 0 (0.0) – Parkinsonism 5 (0.9) 2 (3.3) 3.8 [0.7–20.2] Phobic disorder 8 (1.4) 0 (0.0) – Overdose with suicidal intent 69 (12.3) 2 (3.3) 0.3 [0.1–1.0]n Parasuicide 72 (12.8) 2 (3.3) 0.2 [0.1–1.0]n

123 (2.2) 53 (0.9) 420 (7.4) 22 (0.4) 63 (1.1) 21 (0.4) 78 (1.4) 53 (0.9) 65 (1.1) 99 (1.7) 488 (8.6) 124 (2.2) 49 (0.9) 65 (1.1) 30 (0.5) 11 (0.2) 37 (0.7) 44 (0.8) 46 (0.8)

14 (2.7) 5 (1.0) 42 (8.1) 4 (0.8) 2 (0.4) 1 (0.2) 5 (1.0) 7 (1.3) 10 (1.9) 8 (1.5) 55 (10.6) 15 (2.9) 0 (0.0) 5 (1.0) 2 (0.4) 2 (0.4) 3 (0.6) 1 (0.2) 1 (0.2)

1.3 [0.7–2.2] 1.0 [0.4–2.6] 1.1 [0.8–1.5] 2.0 [0.7–5.8] 0.4 [0.1–1.4] 0.5 [0.1–3.9] 0.7 [0.3–1.7] 1.5 [0.7–3.2] 1. 7 [0.7–3.3] 0.9 [0.4–1.8] 1.3 [0.9–1.7] 1.3 [0.8–2.3] – 0.8 [0.3–2.1] 0.7 [0.2–3.1] 2.0 [0.4–9.0] 0.9 [0.3–2.9] 0.3 [0.0–1.8] 0.2 [0.0–1.7]

COPD¼chronic obstructive pulmonary disease, T2DM ¼type-2diabetes mellitus, T1DM ¼ type-1 diabetes mellitus, GAD ¼ generalized anxiety disorder, PD¼ panic disorder. n

pr 0.05. p r0.01. nnn p r0.001. nn

impact on hospital-based mortality in individuals with BD and controls, i.e. the confidence intervals of the ORs for hospital-based mortality in deceased individuals with BD always included the corresponding ORs of deceased controls, thus p40.05. Eleven diseases were additional mortality risk factors in the control sample (partially due to increased statistic power as a consequence of higher sample sizes in the control sample).

4. Discussion This retrospective case-control study with a 12.5 year observation period in general hospital admissions investigates the impact of comorbidity in individuals with BD on general hospital-based mortality. In agreement with our hypotheses we observed that: (1) individuals with BD compared to controls had a more severe

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Table 4 Risk factors for hospital-based mortality. Indicated odds ratios (ORs) and 95%-CIs are multivariate using the various comorbid diseases as covariates. In the second section comorbidities are ranked in descending order of prevalences in deceased individuals with bipolar disorder. In the third section comorbidities are ranked in descending order of prevalences in deceased controls. Multivariate comparisons

Initial sample Bipolar sample Survivors Prevalence (%)

Control sample Deceased Prevalence (%)

Odds ratio [95%-CI], p

Survivors Prevalence (%)

Deceased Prevalence (%)

Odds ratio [95%-CI], p

Major risk factor for hospital-based mortality in individuals with bipolar disorder T2DM 11.2 25.0 2.1 [1.0–3.8]n

Not included in model

Risk factors for hospital-based mortality in both individuals with bipolar disorder and controls Hypertension 17.5 35.0 2.0 [1.0–3.8]n COPD 6.1 21.7 3.1 [1.4–6.8]nn Pneumonia 2.5 16.7 5.8 [2.3–15.0]nnn Bronchitis 2.9 15.0 3.4 [1.3–9.2]n Ischemic stroke 0.9 10.0 12.3 [3.2–46.7]nnn

17.9 1.8 0.8 1.0 0.5

32.9 11.2 5.4 5.2 4.4

1.5 [1.2–1.8]nnn 3.8 [2.6–5.6]nnn 4.4 [2.5–7.8]nnn 2.5 [1.4–4.5]nnn 5.9 [3.1–11.1]nnn

Risk factors for hospital-based Cataract Heart failure Atrial fibrillation Peripheral vascular disease Lung cancer Chronic kidney disease Renal failure Respiratory failure Rheumatoid arthritis Alcoholic liver disease Non-specific dementia

7.3 1.3 2.9 0.9 0.2 0.7 0.5 0.2 0.5 0.3 0.2

15.6 11.3 10.6 5.2 3.8 3.7 3.5 2.7 2.3 2.3 1.7

2.5 [1.9–3.3]nnn 5.9 [3.9–8.7]nnn 1.5 [1.1–2.3]n 3.9 [2.2–6.6]nnn 21.1 [9.5–46.8]nnn 2.4 [1.2–4.6]nnn 2.2 [1.1–4.6]n 3.5 [1.3–9.7]n 4.8 [2.3–10.0]nnn 8.1 [3.6–18.1]nnn 8.3 [2.9–24.0]nnn

mortality in controls alone Not included in model Not included in model Not included in model Not included in model Not included in model Not included in model Not included in model Not included in model Not included in model Not included in model Not included in model

T2DM ¼ type-2 diabetes mellitus, COPD¼chronic obstructive pulmonary disease. n

pr 0.05. p r0.01. nnn p r 0.001. nn

course of disease between January 1, 2000, and June 30, 2012, that was associated with an increased total number of in-hospital deaths. (2) Individuals with BD compared to controls had a substantial excess comorbidity of 21 diseases, i.e. the highest prevalences were found for asthma, T2DM, and alcohol dependence. Subsequently, 18 other comorbidities were increased in individuals with BD compared to controls, many of them linked to T2DM. In contrast, only cataract was less prevalent in individuals with BD compared to controls. In univariate analyses, 14 diseases contributed to the prediction of hospital-based mortality in individuals with BD. Risk factors for hospital-based mortality in individuals with BD in multivariate analyses were ischemic stroke, pneumonia, bronchitis, COPD, T2DM, and hypertension. The impact of T2DM on hospital-based mortality was higher in the BD sample than in the control sample. The other mortality riskfactors had an equal impact on hospital-based mortality in comparisons between individuals with BD and controls. In simple terms, individuals with BD had more and additionally died more from T2DM and its complications. 4.1. Age at initial hospitalization and clinical course characteristics Individuals with BD have higher prevalences of psychiatric and physical comorbidities compared to the general population (McElroy et al., 2001; Vieta et al., 2001; Krishnan, 2005; Carney and Jones, 2006; Crump et al., 2013). Correspondingly, the first finding of this study is that the average age of individuals with BD at initial admission was 47.3 years, indicating that serious health conditions are highly prevalent at middle age in individuals with BD. Herewith consistent, individuals with BD compared to controls were more likely admitted as emergencies at their initial hospitalization, had an extended length of hospital stay at initial hospitalization, had an increased total number of readmissions, and had a higher total number of in-hospital deaths.

Multiple underlying mechanisms may be responsible for the increased prevalences of physical comorbidities in individuals with BD compared to controls. Individuals with BD have high prevalences of unhealthy life-style factors such as tobacco use, alcohol consumption, and obesity (Gonzales-Pinto et al., 1998; Heffner et al., 2011, 2012; Crump et al., 2013; Calkin et al., 2013). In addition, several pathophysiological mechanisms have been hypothesized to contribute to T2DM and CVD in BD, including proinflammatory cytokines, oxidative stress, and hypothalamic-pituitary-adrenal axis dysfunction (Crump et al., 2013; Calkin et al., 2013). Finally, medication may also be associated with T2DM, and hypoglycemia is associated with an increased length of hospital stay as well as an increased number of readmissions (Nirantharakumar et al., 2012). 4.2. Excess comorbidity of psychiatric and neurological diseases The second finding of this study is that individuals with BD had a substantial excess comorbidity of psychiatric and neurological diseases. Regarding the excess comorbidity of psychiatric diseases in this BD sample, the increased prevalence of alcohol dependence in individuals with BD compared to controls is in agreement with most community based studies that report alcohol dependence more likely to occur with BD than with all other psychiatric disorders except antisocial personality disorder (Shabani et al., 2010). The prevalence of anxiety disorder in this BD sample was found to be noticeably lower than indicated in other studies, possibly because anxiety did not represent the focus of treatment (Stein et al., 1999; Goodwin and Hoven, 2002; Simon et al., 2003, 2005; Krishnan, 2005). Third, opioid dependence was found to be more than five times prevalent in individuals with BD compared to controls. The finding is in line with a US study that found higher rates of BD and anxiety disorder in the subgroup of polydrug abusers compared with single substance abusers in an inpatient

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sample of substance abusers (Skinstad and Swain, 2001). In summary, individuals with BD in general hospitals represent a group that is highly loaded with dual diagnoses of BD and substance use disorders, less likely loaded with dual diagnoses of BD and anxiety disorders, as well as of the simultaneous occurrence of these comorbidities. The coexistence of substance use disorders and of anxiety disorder in BD is important because both comorbidities often precede attempted or completed suicide (Tsai et al., 2002). Correspondingly, the ORs for suicidal and parasuicidal events were highly increased in this BD sample compared to this control sample. Our study did not find further psychiatric comorbidities with BD. A possible explanation is that in older individuals with BD, personality, attentional, and conduct disorders are of low intensity and that there may be only a minority of these individuals being admitted for general hospital treatment. Regarding the excess comorbidity of neurological diseases in this BD sample, the prevalence of epilepsy was found to be more than fivefold elevated in individuals with BD compared to controls. This finding was not expected against the background that antiepileptic drugs are usually applied as mood stabilizers in BD. The reason for this finding remains unclear as we do not have data available about other clinical entities such as interictal dysphoric disorder misdiagnosed as BD, behavioral changes that may occur around an ictus, and about side effects of antiepileptic drug therapy. However, it has to be pointed out that in one large US survey 12.2% of epileptic patients with positively screened symptoms of BD, nearly 6% were subsequently rated by a physician as having BD (Ettinger et al., 2005). In addition, the prevalences of non-specific dementia, Parkinsonism, and ischemic stroke were significantly increased in individuals with BD compared to controls (Mendez, 2000). 4.3. Excess comorbidity of physical diseases The third finding of this study is that individuals with BD had a different pattern of physical comorbidity than hospital controls. First, the prevalence of asthma was increased in individuals with BD compared to controls. The result confirms a strong association between BD and asthma (Chen et al., 2014) as well as between BD, asthma and anxiety disorder (Goodwin and Hoven, 2002; Simon et al., 2005). Asthma may increase the level of anxiety and may trigger panic responses during exacerbations in asthma attacks that may lead to increase in the level of anxiety up to exacerbation of anxious mania like or of excited depression like syndromes. Furthermore, use of prednisone, a corticosteroid, is found to be associated with increased affective symptoms (Brown et al., 2002). The association between asthma and BD is also consistent with clinical findings of an elevated level of respiratory diseases and of panic attacks in BD in the community (Goodwin and Hoven, 2002). Second, we report the prevalence of T2DM increased in individuals with BD compared to controls, as well as a surplus of diabetes related comorbidity such as respiratory and gastrointestinal diseases, obesity, cellulitis, gallbladder calculus, and ischemic stroke. There is ample of evidence that individuals with BD have both a higher genetic predisposition and an excess of environmental factors to develop T2DM compared to the general population (Calkin et al., 2013). Antipsychotics and mood stabilizers are also associated with T2DM due to metabolic pathways that include drug induced weight gain, development of the metabolic syndrome, antagonism of serotonin receptors, drug induced leptin resistance, dyslipidaemia, mediated pancreatic beta cell damage, and hepatocyte transcription factor deregulations (Schoepf et al., 2012, 2014a, 2014b). Of importance, neither CVDs nor common risk factors of CVD differed in their prevalences between the BD sample and the control sample, indirectly emphasizing T2DM to be

the most important risk factor of CVD in individuals with BD. Third, we report the prevalence of COPD increased in individuals with BD compared to controls. The result points to a linkage between BD and tobacco use as cigarette smoking influences COPD in its development and progression as well as mixed forms of allergic and non-allergic asthma (Gonzales-Pinto et al., 1998; Goodwin; Hoven, 2002 and Heffner et al., 2011, 2012). Finally, we report the prevalence of hypothyroidism to be nearly threefold increased in individuals with BD compared to controls. Hypothyroidism often is an important consequence of treatment with lithium, or it could be related to autoimmune thyroiditis. Overall, the data highlight the importance of T2DM and diabetic related conditions in individuals with BD who are treated in general hospitals. 4.4. Risk factors for hospital-based mortality The fourth and major finding of this study is that individuals with BD had more and additionally died more from T2DM than controls. In this hospitalized sample, 15/60 (25%) of deceased individuals with BD had suffered T2DM, whereas only 63/561 (11.2%) of the individuals with BD that did not die in any of the hospitals had suffered T2DM. In comparison, 76/520 (14.6%) of deceased controls had suffered T2DM, whereas 423/5690 (7.4%) of the controls that did not die in any of the hospitals had suffered T2DM. However, in deceased controls T2DM did not contribute to explain the outcome of in-hospital deaths in multivariate analyses. Therefore T2DM was a major risk factor for hospital-based mortality in this BD sample. The spectrum of further mortality risk factors in this BD sample included hypertension, COPD, pneumonia, bronchitis, and ischemic stroke. Only few studies report of an elevated frequency of hypertension in individuals with BD compared to the general population, perhaps because CVD is a multiconditional disorder (Angst et al., 2002; Klumpers et al., 2004; Goldstein et al., 2009; Crump et al., 2013). In contrast, respiratory conditions such as COPD, pneumonia and bronchitis are said to be often fatal in middle aged and older individuals (Corrales-Medina et al., 2012). Several pathophysiological mechanisms may explain the relevance of respiratory diseases for hospital-based mortality in this BD sample: decreased leukocyte function and harmful effects of hyperglycemia; increased susceptibility to opportunistic infections due to multimorbidity; increased likelihood of CVD related complications; drug treatment induced effects that raise the risk of aspiration pneumonia; increased risk of older individuals for future episodes of recurrent pneumonia; and less stringent prescription of multiple pharmacologic drugs with effects on unexpected CVD related and respiratory dysfunction related deaths (Corrales-Medina et al., 2012). Ischemic stroke was another risk factor for hospital-based mortality with a more than 12 times higher prevalence in deceased individuals with BD compared to individuals that did not die in any of the hospitals. The risk of ischemic stroke increases 3% each year with the duration of T2DM, and triples with T2DMZ 10 years (Banerjee et al., 2012). However, hyperglycemia is insufficient to explain the increased prevalence of ischemic stroke in diabetes alone. Further risk factors for ischemic stroke include features of the metabolic syndrome, CVD, respiratory diseases with impaired peak expiratory flow, physical inactivity, poor diet, cardiac conduct abnormalities, lipid disorders, and substance abuse related vessel constrictions. In summary, our findings are in full agreement with a recent Swedish cohort study with seven year follow-up that reports increased mortality in adults with BD from multiple causes, including diabetes, COPD, influenza and pneumonia, as well as from CVD related mortality such as ischemic stroke (Crump et al., 2013). More specifically, this study indicates that in individuals with BD who are treated in general hospitals T2DM and

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diabetes related complications are the most relevant risk factors for hospital-based mortality. 4.5. Limitations The study was designed to assess a representative sample of adult individuals with BD who were admitted to general hospital treatment in United Kingdom‘s second most populous urban area Greater Manchester. Regional variations were controlled by the inclusion of three general hospitals that were uniformly distributed throughout Manchester. However, as a restriction, only a minority of individuals with BD as observed in the general population seeks physical treatment and an unknown proportion of individuals with BD ever are admitted to a general hospital. In addition, other alternatives to hospitalizations such as private hospital structure or other hospitals may have marginally influenced the admission rate to the three general hospitals under investigation. The study design was not assigned to assess the type of BD or the bipolar status. This is assumed to be an underestimation of individuals with BD as sub-threshold individuals with BD were not recognized (Young and Klerman, 1992; Akiskal, 1996). Furthermore, the bipolar status in the BD sample may have influenced the type of admission and the length of hospital stay. It was also impossible to test the moderating effect of bipolarity on the relationship between each physical condition and the risk of in-hospital death with the applied statistical model. As a further limitation, there were no data available about and if individuals with BD were treated with psychotropic medication. It was neither possible to compare drug effects, nor to compare the adherence to treatment between samples. No further data were available about how new onsets of physical comorbidities during the observation period were treated in the bipolar sample, i.e. it is said that there exists a positive correlation between the cumulative number of diseases and the duration of illness in individuals with bipolar I disorder even after correction of age (Soreca et al., 2008) as well as that treatment seeking behaviour is associated with higher rates of physical comorbidities and poor longitudinal continuity of care (Hoertel et al., 2013a), and that poor longitudinal continuity of care is associated with an increased mortality rate among subjects with mental disorders (Hoertel et al., 2013b). Further limitations are that it was not possible to increase the size of the control sample without changing the matching criteria and it was not possible to monitor for differences of ethnicity and marital status. No further data were available about the survival status of the hospital survivors at the end of the observation period. The use of discharge diagnoses and mortality data of the NHS did not permit to differentiate between primary or secondary diagnoses. However, we want to emphasize the good quality of the data because they were clearly able to differentiate the mortality risk factors in individuals with BD. The validity of our major finding is corroborated by a recently published Swedish cohort study with seven year follow-up that reported T2DM, CVD, and respiratory diseases to be relevant mortality risk factors in BD. In summary, even though we accept possible awareness and hospitalization biases we assume that these biases would have worked against our hypotheses and would not have completely changed our results.

5. Conclusions In one of the largest samples of individuals with BD in general hospitals, individuals with BD compared to controls have a higher burden of psychiatric and physical comorbidities that is associated with a more severe course of disease over a 12.5 year observation period. The excess comorbidity in individuals with BD compared to controls is in particular caused by asthma and T2DM. In

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addition, T2DM in BD represents a major risk factor for general hospital-based mortality with excess mortality of acute T2DM, as well as of other diabetes related complications. The study gives support for an aggressive multidisciplinary approach to identify and treat T2DM to prevent diabetic, respiratory and vascular complications in all individuals with BD.

Role of funding source This research received no specific grant from a funding agency, commercial or not-for-profit sectors.

Conflict of interest None.

Acknowledgments We are extremely grateful to R. Potluri and H. Uppal for their support in provision, preparing of the data, and its analysis.

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