The incidence and associated risk factors for sudden unexplained death in psychiatric in-patients in England and Wales

National Confidential Inquiry into Suicide and Homicide by People with Mental Illness, Centre for Suicide Prevention, University of Manchester, Manchester, UK.
Journal of Psychopharmacology (Impact Factor: 3.59). 10/2010; 25(11):1533-42. DOI: 10.1177/0269881110379288
Source: PubMed
ABSTRACT
Clinical characteristics and risk factors associated with sudden unexplained death (SUD) in the psychiatric population are unclear. Psychiatric in-patients (England, Wales) who met criteria for SUD were identified (1 March 1999-31 December 2005). Cases were matched with controls (in-patients alive on the day a SUD occurred). Data were collected via questionnaires. Some 283 cases of SUD were identified (41 annually), with a rate of 2.33/10,000 mental health admissions (in England). Electrocardiograms were not routine, cardiopulmonary resuscitation equipment was sometimes unavailable, attempts to resuscitate patients were carried out on one-half of all patients and post mortems/inquiries were not routine. Restraint and seclusion were uncommon. Risk factors included: benzodiazepines (odds ratio (OR): 1.83); ≥ 2 antipsychotics (OR: 2.35); promazine (OR: 4.02); diazepam (OR: 1.71); clozapine (OR: 2.10); cardiovascular disease (OR: 2.00); respiratory disease (OR: 1.98); diagnosis of dementia (OR: 2.08). Venlafaxine and a diagnosis of affective disorder were associated with reduced ORs (OR: 0.42; OR: 0.65). SUD is relatively rare, although it is more common in older patients and males. Prevention measures may include safer prescribing of antipsychotics and improved physical health care. The contribution of restraint or seclusion to SUD in individual cases is unclear. A uniform definition of SUD may help to identify contributing factors.

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Available from: Clare Dixon, Apr 02, 2015
Original Paper
The incidence and associated risk factors for
sudden unexplained death in psychiatric
in-patients in England and Wales
Kirsten Windfuhr
1
, Pauline Turnbull
1
, David While
1
, Nicola Swinson
1
,
Hetal Mehta
1
, Kelly Hadfield
1
, Urara Hiroeh
1
, Helen Watkinson
2
,
Clare Dixon
1
, Sandra Flynn
1
, Simon Thomas
2
, Glyn Lewis
3
, IN Ferrier
4
,
Tim Amos
3
, Petros Skapinakis
3,5
, Jenny Shaw
1
, Nav Kapur
1
and
Louis Appleby
1
Abstract
Clinical characteristics and risk factors associated with sudden unexplained death (SUD) in the psychiatric population are unclear. Psychiatric in-
patients (England, Wales) who met criteria for SUD were identified (1 March 1999–31 December 2005). Cases were matched with controls (in-patients
alive on the day a SUD occurred). Data were collected via questionnaires. Some 283 cases of SUD were identified (41 annually), with a rate of
2.33/10,000 mental health admissions (in England). Electrocardiograms were not routine, cardiopulmonary resuscitation equipment was sometimes
unavailable, attempts to resuscitate patients were carried out on one-half of all patients and post mortems/inquiries were not routine. Restraint and
seclusion were uncommon. Risk factors included: benzodiazepines (odds ratio (OR): 1.83); 2 antipsychotics (OR: 2.35); promazine (OR: 4.02);
diazepam (OR: 1.71); clozapine (OR: 2.10); cardiovascular disease (OR: 2.00); respiratory disease (OR: 1.98); diagnosis of dementia (OR: 2.08).
Venlafaxine and a diagnosis of affective disorder were associated with reduced ORs (OR: 0.42; OR: 0.65). SUD is relatively rare, although it is more
common in older patients and males. Prevention measures may include safer prescribing of antipsychotics and improved physical health care. The
contribution of restraint or seclusion to SUD in individual cases is unclear. A uniform definition of SUD may help to identify contributing factors.
Keywords
Drug treatment, psychiatric in-patients, sudden death
Introduction
Over the past four decades there has been growing concern
over the incidence of sudden unexplained death (SUD) in
psychiatric patients (Royal College of Psychiatrists, 1997),
particularly in the context of pharmacological treatment.
However, a lack of systematic, national studies has led to a
gap in the literature regarding the number and rate of
SUD. Differences in study populations, data sources and def-
inition have led to substantial variations in the reported rate
of SUD (6.6/100,000 persons per year to 190/100,000 persons
per year) (Anderson et al., 1994; Bowker et al., 2003;
Glassman and Bigger, 2001; Ray et al., 2001; Shen et al.,
1995; Straus et al., 2004; Tungsanga and Sriboonlue, 1993;
Wannamethee et al., 1995).
There are relatively few controlled epidemiological stud-
ies addressing the issue of SUD in patients taking antipsy-
chotic drugs. Straus et al. (2004) reported a three-fold
increase in the risk of SUD among those using antipsychotics
in a community sample, while the risk of SUD in people with
a history of treatment for mental illness was increased five-
fold (Ruschena et al., 1998). Elevated risk of SUD has been
associated with a number of antipsychotic drugs (Morentin
et al., 2003; Ray et al., 2001; Straus et al., 2004), particularly
typical antipsychotics such as thioridazine (Glassman and
Bigger, 2001; Hennessy et al., 2002; Mehtonen et al., 1991;
1
National Confidential Inquiry into Suicide and Homicide by People with
Mental Illness, Centre for Suicide Prevention, University of Manchester,
Manchester, UK.
2
School of Clinical and Laboratory Sciences, University of Newcastle,
Newcastle, UK.
3
Academic Unit of Psychiatry, University of Bristol, Bristol, UK.
4
School of Neurology, Neurobiology and Psychiatry, University of
Newcastle, Newcastle, UK.
5
Department of Psychiatry, University of Ioannina School of Medicine,
Ioannina, Greece.
Corresponding author:
Kirsten Windfuhr, National Confidential Inquiry into Suicide and Homicide
by People with Mental Illness, Centre for Suicide Prevention, Jean
McFarlane Building, Oxford Road, University of Manchester, Manchester
M13 9PL, UK
Email: kirsten.windfuhr@manchester.ac.uk
Journal of Psychopharmacology
25(11) 1533–1542
! The Author(s) 2011
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Reilly et al., 2002) and droperidol (Reilly et al., 2002). More
recently, Ray et al. showed that the risk of SUD is also
increased following exposure to atypical antipsychotics in a
community sample of current users of antipsychotics (Ray
et al., 2009).
One mechanism by which some antipsychotics are
thought to contribute to an increased risk of SUD is through
the lengthening of the QT interval (an electrocardiogram
(ECG) measure of cardiac repolarization), leading to fatal
ventricular arrhythmia (e.g. torsade de pointes) (Glassman
and Bigger, 2001; Hennessy et al., 2002; Reilly et al., 2002).
However, not all antipsychotic drugs carry a high risk of QT
prolongation and it may be that the mechanism by which indi-
vidual or classes of drugs are associated with an increased risk
of SUD differs. Non-drug factors may also contribute to SUD
in psychiatric patients, including poor physical health (Ray
et al., 2001; Reilly et al., 2002) and restraint (Banerjee et al.,
1995), although these factors have not been studied in detail.
We sought to overcome some of the limitations of previous
research by carrying out a national study of sudden and unex-
plained death in a psychiatric in-patient population. The spe-
cific objectives of the study were to: (1) determine the number
and rate of SUD in mental health in-patients; (2) describe the
socio-demographic and clinical antecedents of SUD; and
(3) carry out a national case-control study identifying inde-
pendent risk factors for SUD. Specifically, we examined the
hypotheses that SUD cases would be associated with:
polypharmacy, higher doses of antipsychotic drugs, and drugs
known to be associated with QT prolongation (e.g. thio-
ridazine, droperidol)
pre-existing cardiac disease
restraint and seclusion.
Method
Cases
People aged 15–75 years (inclusive) who died on a psychiatric
in-patient ward in England and Wales between 1 March 1999
and 31 December 2005 (6 years and 10 months) were identi-
fied from national datasets of all in-patients provided by
Hospital Episode Statistics (HES) for England, and Health
Solutions for Wales (HSW). These datasets record anon-
ymized patient details, medical specialty, admission dates,
type of discharge (including death), and hospital and consul-
tant codes. Cases were also notified to us from additional
sources (i.e. psychiatrists registered with the Royal College
of Psychiatrists, independent hospitals, secure units, the
Mental Health Act Commission, and the voluntary organiza-
tions Rethink and Inquest).
Cases of SUD were those in-patients who were confirmed
by the treating clinician to have died from an unknown cause
or a cardiac cause unrelated to myocardial infarction (con-
firmed by ECG, cardiac enzymes or post-mortem) within 1 h
of the patient being observed in their usual state of health.
Death occurring within 60 min of the onset of symptoms is an
internationally recognized criterion for SUD (World Health
Organization, 1993) and has been used in previous studies
(Reilly et al., 2002). All potential SUD cases notified to us
by the respondent were cross-checked against our national
suicide database (Appleby et al., 2006) and any cases of sui-
cide removed from the current study.
Patients over the age of 75 years were excluded because the
study was primarily designed to examine care and drug fac-
tors contributing to SUD. The rate of sudden death from
natural causes in the elderly is high, complicating a detailed
examination of specific treatment-related factors (Reilly et al.,
2002).
Case validation
Case notes for every SUD case were requested for review.
The decision on whether a death met the SUD criteria was
confirmed by a clinical member of the research team.
Controls
For the case-control study, up to four individually matched
controls per case were selected from HES and HSW datasets.
There were four matching criteria: a) alive on a mental health
ward on the same day that the death of the case occurred;
b) date of admission the same as the case; c) gender; and d)
age. If fewer than four suitable controls were identified, the
analysis was carried out using the available controls. If more
than four controls of equal suitability were available, the con-
trol subject with the closest date of birth to the case was
selected. Matching closely for age was difficult for a small
number of subjects, e.g. long-term in-patients, recently admit-
ted patients, but cases and controls were matched to within
3 years on average. We did not match on the in-patient unit of
death, as overmatching could have obscured the effects of
important differences in clinical care.
Data collection
For each in-patient death identified through HES, HSW,
or other sources, the treating consultant was sent a study
questionnaire. Consultants were identified through TRUD
(Terminology Reference-date Up Distribution service, for-
merly the National Administrative Code Service (NACS)),
which provided trust and consultant codes for identification
purposes. The first section of the questionnaire determined
whether the person died by SUD according to the above cri-
teria. Where cases met the criteria the consultant was asked to
complete the remaining nine sections, covering demographic
information, psychiatric history, diagnoses, physical health,
substances taken prior to death including psychotropic med-
ication, details of final admission, circumstances of death,
additional information, and respondent details.
Statistical analyses
We aimed to investigate the rate of SUD overall, and by
calendar year. Due to the availability of admissions denomi-
nator data (i.e. number of NHS mental health and learning
disability admissions) this was only possible for SUD cases in
England aged 15–74. Cases aged 75 years (N ¼ 12) and cases
occurring in Wales (N ¼ 20) were excluded from the analysis
of rates. An incidence rate ratio (IRR) was calculated to
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investigate longitudinal trends in the rate of suicide across the
time period of the study. An IRR of less than 1 indicates a
decrease in the trend across the study period.
All SUD cases are included in the descriptive analysis
(N ¼ 283). Descriptive analyses are presented as the number
and proportion of valid cases for each variable. For the case-
control analyses, only data from cases and controls notified
to us via HES and HSW data sources (N ¼ 242) were used,
to ensure consistent ascertainment for cases and controls.
Conditional logistic regression was used to calculate odds
ratios (OR) for the association between the key variables of
interest and SUD. The reported p-values relate to the z-values,
which are calculated by dividing the predictor coefficient by its
standard error. Analyses of drug exposures refer to the 24 h
before death or index date. Initially, an unadjusted univariate
analysis was carried out. This was repeated after adjusting for
the following likely confounding variables: smoking, history of
cardiovascular (CV) disease, and history of respiratory disease.
We also included age as a covariate because the controls were
found to be younger than the cases, despite matching.
Polypharmacy was defined as the concurrent exposure to
two or more drugs. Dosage for antipsychotic drugs was cal-
culated in two ways. First, the median chlorpromazine equiv-
alent doses for antipsychotic drug exposures were calculated
for typical and atypical antipsychotic drugs (Atkins et al.,
1997; Yorston and Pinney, 2000; Woods, 2003). Second,
drugs were grouped into low dose (<100 mg), moderate
dose (100–299 mg) and high dose (300 mg) exposures of
chlorpromazine equivalent doses for typical and atypical anti-
psychotics (Ray et al., 2009).
We present both unadjusted and adjusted analyses in the
results section but we discuss only the adjusted analyses in
detail. The level of statistical significance for an association
between SUD and individual variables was set at p 0.05.
Significance levels were two-tailed.
In order to investigate which treatment-related variables
were independently associated with SUD, psychiatric drug
and care variables (found to be associated with SUD in the
unadjusted analysis) were entered into a multivariate predic-
tor model. The model was then adjusted for age, smoking,
history of CV disease and history of respiratory disease.
When both an individual drug and the drug class to which
it belonged were independently associated with SUD we
included the drug class. Psychiatric diagnosis was not
included in the multivariate predictor model because of col-
linearity with the pharmaceutical variables. To allow for risk
factors that might be important, particularly in combination
with other risk factors, variables with a p-value of <0.10 from
the univariate analysis were included in the multivariate pre-
dictor modelling procedure (see Dupont, 2002).
Intercooled STATA 10.0 for Windows 98/95/NT (Stata
Corporation, 2003) was used to carry out all analyses.
Results
Case ascertainment
Figure 1 summarizes recruitment to the study. During the
study period, 4495 in-patient deaths in mental health units
were recorded (a rate of 342 per 100,000 mental health
admissions). In 229 (5%) cases, a questionnaire could not
be sent or completed because the patient, consultant or case
notes could not be identified or located. Questionnaires were
sent out for 4266 (95%) individuals and were returned for
4026 individuals (a response rate of 94%). Of these, 324
(8%) respondents identified a case of SUD.
Of the 324 cases identified by the respondent, 294 (91%)
cases were validated by the SUD research team. Of these,
there was agreement between the respondent and the SUD
team on 253 (86%) cases. Forty-one (14%) cases were
removed following validation as the cases did not meet
SUD criteria. In total, 283 SUD cases were included in the
descriptive study.
Of all SUD cases included in the study (N ¼ 283), 252
(89%) were notified to the research team from our primary
sources (i.e. HSW, HES). Thirty-one (11%) were notified to
us via other reporting routes (e.g. individual clinicians,
Rethink).
Number and rate of SUD
The annual number and rate of SUD in England is shown in
Table 1. There were on average 41 SUD cases notified to the
research team per year (range: 30–47). On average, SUD cases
accounted for 7% of all psychiatric in-patient deaths (range:
5–8%). Of the 283 SUD cases, rates of SUD per 10,000 NHS
mental health and learning disability admissions were calcu-
lated for the 251 SUD cases occurring in England who were
under 75 years of age. The overall rate was 2.33 per 10,000
NHS admissions (95% CI: 2.05–2.64) with no significant
increase in SUD across the time period of the study (IRR:
1.05, 95% CI: 0.99–1.12, p ¼ 0.13). Overall, rates of SUD per
10,000 admissions were higher in males (2.67 per 10,000
admissions) than females (1.97 per 10,000 admissions) and
increased with increasing age (15–44 years: 1.00 per 10,000
admissions; 65–74 years: 7.95 per 10,000 admissions).
Characteristics of all SUD cases
The median age of the sample was 61 years, of whom 50 (18%)
were under 40 years of age. Overall, SUD cases were predom-
inately white (N ¼ 251, 90%) and male (N ¼ 168, 59%).
Patients were in poor mental and physical health characterized
by: a primary diagnosis of schizophrenia (N ¼ 102, 36%),
affective disorders (N ¼ 78, 28%) or dementia (N ¼ 55, 20%)
and multiple admissions (>5 previous admissions: N ¼ 94,
34%). Just under half of all patients had a history of CV dis-
ease (N ¼ 128, 46%), and had experienced symptoms of CV
disease in the month prior to death (N ¼ 119, 45%).
It is possible that some patients may not have been opti-
mally managed. For example, although a full physical exam
had been carried out during the final admission in nearly all
cases (N ¼ 257, 92%), an ECG had been carried out in less
than half of all patients (N ¼ 105, 42%) in the year prior to
death. Cardiopulmonary resuscitation (CPR) was attempted
in only 148 (55%) cases, although in 136 (87%) cases staff had
been trained in CPR and CPR equipment was available on
161 (70%) of all wards. Following a death, the majority of
cases were discussed with the team who had been caring for
the patient (N ¼ 231, 90%) and relatives of the patient
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(N ¼ 216, 88%). However, a post-mortem took place in 161
(69%) of all cases while an inquiry (either internal or external)
was carried out in 56 (22%) cases.
In total, there were nine cases who had been restrained and/
or secluded in the 24 h prior to death. Seven cases had been
restrained in the 24 h prior to death (of whom five were from an
ethnic minority background and five were under 40 years of
age). Seven cases had been secluded in the 24 h prior to death.
Of these seven cases, five were from an ethnic minority back-
ground and four were under 40 years of age. Of all nine cases
who had been restrained and/or secluded in the 24 h prior to
death, five had been both restrained and secluded.
In total, there were seven patients who had been restrained
and/or secluded in the 1 h prior to death. Five patients had been
4495
in-patient deaths
4026 (94%)
completed questionnaires
4266 (95%)
questionnaires sent out
240 (6%)
not completed
324 (8%)
SUD cases identified by clinician
30 (9%)
not validated
283 total SUD cases
(7% of 4266 questionnaires sent)
41 (14%)
removed after validation;
did not meet SUD criteria
294 (91%)
validated SUD cases
253 (86%)
agreement on SUD cases
between clinician and SUD
team
267 (94%)
cases with matched control data
16 (6%) excluded from case-
control study;
control data not available
242 (91%)
notification via national sources;
cases included in case-control analyses
(224 (93%) of these SUD cases had been validated)
25 (9%) excluded from case-
control study;
data not from national sources
229 (5%) excluded:
patient, consultant or
case notes not
identified/located
Figure 1. Case ascertainment for sudden unexplained death (SUD).
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restrained in the 1 h prior to death (of whom three were from an
ethnic minority). Six patients had been secluded in the hour
prior to death (of whom four were from an ethnic minority).
Of all seven patients who had been restrained and/or secluded
only, four were under 40 years of age. Out of the seven cases that
had been restrained and/or secluded in the hour prior to death,
four patients had been both restrained and secluded.
SUD cases from national sources versus other sources
Thirty-one cases were not notified to the SUD team from
national sources (e.g. HES). These cases were different from
nationally notified cases on some variables. These cases were
more likely to have longstanding and severe mental illness
(duration of final admission 1–5 years: N ¼ 21 (8%) vs.
N ¼ 7 (23%), p ¼ 0.02; primary diagnosis of schizophrenia:
N ¼ 85 (34%) vs. N ¼ 17 (55%), p ¼ 0.02). They were more
likely to have been detained for treatment (N ¼ 46 (18%) vs.
N ¼ 13 (43%), p < 0.01), and to have been physically
restrained (N ¼ 3 (1%) vs. N ¼ 4 (14%), p < 0.01) or been in
seclusion (N ¼ 3 (1%) vs. N ¼ 4 (13%), p < 0.01) in the time
period prior to death; an inquiry into the death of these indi-
viduals was more common ( N ¼ 43 (19%) vs. N ¼ 13 (46%),
p < 0.01).
Case–control study
Of the 283 SUD cases identified during the study period, we
were able to obtain valid controls for 267 (94%). Of these,
242 (91%) were notified to us via national sources (i.e. HES,
HSW), and 25 (9%) were notified to us from other sources
(i.e. psychiatrists registered with the Royal College of
Psychiatrists, independent hospitals, secure units, the
Mental Health Act Commission, and the voluntary organiza-
tions Rethink and Inquest). Of the 242 cases included in the
case-control study, 224 (93%) cases had been validated by the
SUD research team.
Only data relating to the 242 cases and matched controls
from national sources are presented in the remainder of the
paper. Descriptive analyses indicated some differences
between cases notified from national (e.g. HES) and non-
national sources. Further, omission of SUD cases notified
from other sources ensured consistent ascertainment of
cases and controls.
The 242 cases were matched with 823 controls. Of these,
138 cases were matched with four controls, 70 cases were
matched with three controls, 27 cases were matched with
two controls and seven cases were matched with one control.
Types and classes of drugs
The association between SUD and types and classes of drugs
is shown in Table 2. Exposure to benzodiazepines was signif-
icantly associated with an increased OR which remained after
controlling for confounding variables (age, smoking, CV dis-
ease, respiratory disease). Chlorpromazine equivalent dosages
of typical and atypical antipsychotic drugs were not signifi-
cantly associated with SUD when examined as median chlor-
promazine equivalent doses, or low, moderate or high dose
exposures, in either unadjusted or adjusted analyses.
Individual psychotropic drugs
There was a low exposure rate to most individual drugs, result-
ing in wide confidence intervals. However, some individual
drugs were significantly associated with SUD. Promazine (typ-
ical antipsychotic) was associated with an increased OR (cases:
8 (3%), controls: 6 (1%); OR: 4.79; 95% CI: 1.65–13.87,
p < 0.01) as was diazepam (benzodiazepine) (cases: 32 (13%),
controls: 67 (8%); OR: 1.69; 95% CI: 1.07–2.68, p ¼ 0.02).
Venlafaxine (serotonin-norepinephrine reuptake inhibitor,
SNRI) was associated with a reduced OR (cases: 9 (4%), con-
trols: 62 (8%); OR: 0.47; 95% CI: 0.23–0.97, p ¼ 0.04). After
adjusting for potential confounding variables (age, history of
CV disease, history of respiratory disease, smoking) promazine
(OR: 4.02; 95% CI: 1.33–12.14, p < 0.01), diazepam (OR: 1.71;
95% CI: 1.05–2.79, p ¼ 0.03) and venlafaxine (OR: 0.42; 95%
CI: 0.19–0.92, p ¼ 0.03) all remained significantly associated
with SUD. In addition, clozapine (atypical antipsychotic)
(cases: 16 (7%), controls: 35 (4%); OR: 2.10; 95% CI:
1.03–4.31, p ¼ 0.04) was significantly associated with an
increased risk of SUD in the adjusted analyses. Further, expo-
sure to two or more antipsychotics (i.e. polypharmacy) was
associated with an increased OR (cases: 21 (9%), controls: 36
(4%); OR: 2.40; 95% CI: 1.34–4.31, p < 0.01). This association
remained significant after adjusting for confounding variables
(i.e. age, smoking, CV disease, respiratory disease) (OR: 2.35;
95% CI: 1.28–4.32, p ¼ 0.01).
Table 1. Annual rates of sudden unexplained death in England per 10,000 NHS mental health and learning disability admissions, by gender
Males Females All
Calendar Year N Rate (95% CI) N Rate (95% CI) N Rate (95% CI)
*1999 16 2.08 (1.19–3.39) 15 2.12 (1.19–3.50) 31 2.10 (1.43–2.99)
2000 26 2.99 (1.96–4.39) 9 1.11 (0.51–2.10) 35 2.08 (1.45–2.90)
2001 14 1.61 (0.88–2.70) 9 1.11 (0.51–2.10) 23 1.37 (0.87–2.05)
2002 21 2.47 (1.53–3.77) 18 2.30 (1.37–3.64) 39 2.39 (1.70–3.27)
2003 23 2.87 (1.82–4.31) 23 3.17 (2.01–4.76) 46 3.01 (2.21–4.02)
2004 27 3.54 (2.33–5.15) 16 2.35 (1.34–3.81) 43 2.98 (2.16–4.01)
2005 23 3.30 (2.09–4.95) 11 1.78 (0.89–3.19) 34 2.58 (1.79–3.61)
Total 150 2.67 (2.26–3.13) 101 1.97 (1.60–2.39) 251 2.33 (2.05–2.64)
*1 March 1999–31 December 1999.
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Social and clinical factors
The association between SUD and social and clinical vari-
ables is shown in Table 3. A history of CV disease was asso-
ciated with a significantly increased risk of SUD, as was a
history of respiratory disease in both unadjusted and adjusted
analyses. There were no associations with smoking, drug and
alcohol misuse (separately or combined). A primary diagnosis
of dementia was significantly associated with an increased risk
of SUD, even after adjusting for confounding variables.
Affective disorder was associated with a reduced risk of
SUD, which remained after adjustment for confounding
variables.
Restraint and seclusion were not significantly associated
with an increased risk of SUD. There was no association with
ethnicity.
Multivariate predictor model
The multivariate predictor model is shown in Table 4.
Variables that remained significantly associated with an
increased risk of SUD were: promazine, clozapine, and benzo-
diazepines, as a class of drug. SNRIs and paroxetine were asso-
ciated with a significantly reduced risk of SUD. Further,
although trazodone remained in the multivariate predictor
model the association with SUD did not reach significance.
Discussion
During the study period, 283 cases of SUD were identified
(7% of all deaths on psychiatric in-patient wards), equating to
approximately 41 cases per year. The incidence rate of SUD
(in England) was 2.33 per 10,000 mental health admissions
with no significant increase in the rate of SUD across the time
period of the study; rates were higher in older people and
males. Patients were predominately male and 10% were
from an ethnic minority. Patients were characterized by
severe mental illness and poor physical health (i.e. CV and
respiratory problems). It may be that some patients did not
receive optimal care (i.e. ECGs were not routinely carried out,
CPR equipment was not readily available on all wards,
attempts to resuscitate patients were carried out on only
half of all patients). Post-mortem examinations were carried
out in two-thirds of all cases, and an inquiry in only one-
fifth of cases. Restraint and seclusion were used in very
few cases, although their contribution to SUD is unclear.
In the case-control analysis an increased risk of SUD was
associated with drugs (i.e. benzodiazepines, promazine,
Table 2. The number, percentage and unadjusted and adjusted odds ratios (OR) (95% CI) for types and classes of psychotropic drugs
Variable
Cases
(N ¼ 242) N (%)
Controls
(N ¼ 823) N (%)
Unadjusted OR
OR* (95% CI) p-value
Adjusted OR**
OR* (95% CI) p-value
Drug types and classes
Atypical antipsychotics 91 (38%) 279 (34%) 1.29 (0.95–1.77) 0.11 1.28 (0.92–1.80) 0.15
Typical antipsychotics 51 (21%) 149 (18%) 1.18 (0.82–1.71) 0.38 1.30 (0.88–1.92) 0.18
Tricyclic antidepressant 24 (10%) 70 (9%) 1.13 (0.69–1.86) 0.62 1.03 (0.60–1.77) 0.92
Depot antipsychotics 33 (14%) 104 (13%) 1.11 (0.72–1.71) 0.64 1.19 (0.74–1.90) 0.48
QT-prolonging antipsychotics
1
10 (4%) 22 (3%) 1.55 (0.67–3.58) 0.31 1.92 (0.79–4.67) 0.15
SSRIs 34 (14%) 143 (17%) 0.78 (0.52–1.19) 0.25 0.70 (0.45–1.08) 0.11
SNRI/other 10 (4%) 62 (8%) 0.52 (0.26–1.04) 0.07 0.46 (0.22–0.97) 0.04
Mood stabilizers 58 (24%) 206 (25%) 0.97 (0.69–1.36) 0.85 0.97 (0.68–1.39) 0.87
Benzodiazepines 73 (31%) 168 (20%) 1.74 (1.25–2.42) <0.01 1.83 (1.29–2.58) <0.01
Non-benzodiazepine hypnotic 41 (17%) 116 (14%) 1.29 (0.87–1.91) 0.20 1.31 (0.87–1.98) 0.20
Anti-parkinsonian 36 (15%) 102 (12%) 1.27 (0.84–1.93) 0.26 1.48 (0.95–2.30) 0.09
Median chlorpromazine equivalent doses
y
Typical antipsychotics 300 (range: 10–2500) 200 (range: 20–4000) 1.00 (0.99–1.00) 0.19 1.00 (0.99–1.00) 0.22
Atypical antipsychotics 250 (range: 12.5–1450) 200 (range: 13–1750) 1.00 (0.99–1.00) 0.25 1.00 (0.99–1.00) 0.08
Chlorpromazine equivalent doses
y
Typical antipsychotics
Low dose 13 (26%) 40 (29%) 1.00 1.00
Moderate dose 11 (22%) 56 (41%) 0.12 (0.01–1.59) 0.11 0.09 (0.01–3.30) 0.19
High dose 26 (52%) 40 (29%) 1.40 (0.17–11.67) 0.75 0.51 (0.04–7.09) 0.62
Atypical antipsychotics
Low dose 10 (13%) 38 (14%) 1.00 1.00
Moderate dose 31 (39%) 114 (43%) 1.25 (0.43–3.66) 0.69 0.73 (0.20–2.66) 0.63
High dose 38 (48%) 112 (42%) 1.29 (0.43–3.85) 0.64 0.78 (0.20–2.94) 0.71
1
Droperidol, IM Droperidol, Pimozide, Thioridazine.
*Non-exposure was used as the index category unless otherwise stated (e.g. schizophrenia).
**Adjusted for age, history of cardiovascular disease, history of respiratory disease and smoking history.
y
Excluded all individuals with no exposure to atypical or typical antipsychotic drugs.
SNRI: serotonin-norepinephrine reuptake inhibitor, SSRI: selective serotonin reuptake inhibitor.
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clozapine, diazepam) and clinical variables (i.e. primary
diagnosis of dementia, CV and respiratory disease). There
was no dose-related increased risk of SUD following expo-
sure to antipsychotics. SNRIs (venlafaxine) and a primary
diagnosis of affective disorder were associated with a
decreased risk of SUD.
Methodological issues
The findings of this paper should be viewed within the meth-
odological limitations of the study. Although we aimed to
validate all cases of SUD this was not possible for practical
and resource reasons. A clinician on the SUD team reviewed
the case notes for 294 of 324 (91%) consultant-identified SUD
cases. Psychiatric case notes sent by the treating clinician were
used to validate cases of consultant-identified SUD. The SUD
team did not have access to other sources of patient informa-
tion (i.e. primary care records). Of the 294 case notes
reviewed, there was agreement on the status of the cases as
a SUD between the treating consultant and the SUD clinician
in 253 of 294 (86%) SUD cases reviewed. If the overall level
of agreement is applied to the 30 cases that were not validated
we estimate that 26 cases would have been confirmed and four
cases would have been excluded. Therefore, the total number
of cases included in the study would have fallen to 279 (283),
or 40 per year. Of course, it is also possible that our method-
ology missed some cases. A preliminary validation of a
selected sample of non-cases by the research team suggested
an error rate (that is, proportion of non-cases that were
Table 3. Associations between social and clinical factors and sudden unexplained death
Variable
Cases
(N ¼ 242) N (%)
Controls
(N ¼ 823) N (%)
Unadjusted OR
OR* (95% CI) p-value
Adjusted OR**
OR* (95% CI) p-value
Age in years (median and range) 63 (17–75) 60 (15–75)
Male 140 (58%) 458 (56%)
Ethnicity
White 216 (91%) 728 (90%) 1.00 1.00
Non–white 22 (9%) 77 (10%) 1.12 (0.66–1.88) 0.68 1.31 (0.75–2.27) 0.35
Civil status
Married 77 (32%) 228 (28%) 1.00 1.00
Single 90 (38%) 314 (38%) 0.79 (0.53–1.18) 0.24 0.90 (0.58–1.39) 0.63
Divorced/widowed 72 (30%) 274 (34%) 0.79 (0.54–1.15) 0.22 0.74 (0.49–1.12) 0.15
Smoking
1
Never smoked 71 (29%) 250 (30%) 1.00 1.00
Ex–smoker 36 (15%) 110 (13%) 1.14 (0.72–1.82) 0.58 0.93 (0.57–1.52) 0.77
Current smoker 99 (41%) 348 (42%) 1.00 (0.70–1.42) 1.00 0.84 (0.57–1.24) 0.38
Missing data 36 (15%) 115 (14%) 1.12 (0.71–1.78) 0.62 1.04 (0.62–1.73) 0.89
History of cardiovascular disease (CV) 111 (47%) 251 (31%) 2.27 (1.63–3.15) <0.01 2.00 (1.42–2.82) <0.01
History of respiratory disease 65 (28%) 127 (16%) 2.07 (1.45–2.94) <0.01 1.98 (1.36–2.90) <0.01
History of alcohol misuse in lifetime 57 (24%) 219 (27%) 0.81 (0.57–1.15) 0.24 0.94 (0.64–1.37) 0.73
History of drug misuse in lifetime 34 (15%) 121 (15%) 1.01 (0.62–1.66) 0.95 1.32 (0.77–2.26) 0.32
Psychiatric diagnosis
Schizophrenia 83 (34%) 280 (34%) 1.02 (0.73–1.42) 0.91 1.06 (0.74–1.51) 0.76
Affective disorder 68 (28%) 298 (36%) 0.67 (0.48–0.93) 0.02 0.65 (0.45–0.92) 0.02
Dementia 49 (20%) 95 (12%) 2.27 (1.48–3.48) <0.01 2.08 (1.29–3.34) <0.01
Learning disabilities 10 (4%) 38 (5%) 0.79 (0.36–1.76) 0.57 0.90 (0.38–2.15) 0.82
Other diagnosis 31 (13%) 109 (13%) 0.95 (0.62–1.47) 0.83 1.02 (0.65–1.61) 0.93
Patient physically restrained 24 hours prior to
index date
3 (1%) 3 (0.5%) 3.09 (0.62–15.46) 0.17 3.50 (0.68–18.15) 0.14
Patient in seclusion 24 hours prior to index date 3 (1%) 3 (0.5%) 3.30 (0.66–16.42) 0.14 4.71 (0.90–24.70) 0.07
*Non-exposure was used as the index category unless otherwise stated (e.g. schizophrenia).
**Adjusted for age, history of cardiovascular disease, history of respiratory disease and smoking history.
1
The group of patients with missing data on history of smoking had a higher OR compared with the other categories and were therefore included in the analysis as a
separate category.
Table 4. Multivariate predictor models including drug and care variables
within 24 h of death
Variable OR 95% CI p-value
Promazine 5.46 (1.68–17.79) 0.01
Clozapine 2.16 (1.03–4.55) 0.04
Paroxetine 0.35 (0.13–0.97) 0.04
Trazodone 2.17 (0.94–4.98) 0.07
Benzodiazepines 1.87 (1.32–2.67) <0.01
SNRIs 0.42 (0.19–0.89) 0.03
Note. Adjusted for age, history of cardiovascular disease, history of respiratory
disease and smoking history.
SNRI: serotonin-norepinephrine reuptake inhibitor.
Windfuhr et al. 1539
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judged by the research team to be cases) of only 2%. Further,
the clinicians who completed questionnaires used case notes
as their main source of information, thereby reducing recall
bias. However, patient records were often incomplete on
important variables (i.e. smoking, weight, family history of
premature death, post-mortem information).
There are three additional methodological limitations
specific to the case-control study. First, the association
between drug factors and SUD may have been confounded
by psychiatric diagnosis. Future research should focus on elu-
cidating the independent associations between psychiatric
diagnoses and treatment variables, particularly drug treat-
ment. Second, cases identified to us from other sources (e.g.
independent hospitals) were excluded from the current study.
Although this had the effect of reducing the power of the
study, it ensured consistent ascertainment of cases and
controls and eliminated potential bias. Third, there were sig-
nificant differences between the validated (N ¼ 253) and non-
validated (N ¼ 30) samples on two variables: duration of
admission 1–5 years (N ¼ 21; 8% vs. N ¼ 7; 23%, p > 0.01)
and physical restraint in the 24 h prior to SUD (N ¼ 4; 2%
vs. N ¼ 3; 11%, p < 0.03). However, numbers of non-vali-
dated cases were small and interpretation of these data are
unclear.
Interpretation of results
Despite the limitations, this study is the first national study to
report the number, rates and characteristics of SUD in the
psychiatric in-patient population, and the findings of this
study have several implications for clinical practice and
future research.
First, although SUD is relatively uncommon, services
should be aware that SUD is more likely to occur in those
who are male, older and physically ill. Monitoring physical
health factors includes the appropriate management of mod-
ifiable risk factors for heart disease such as lifestyle factors
(e.g. smoking, obesity), particularly for older patients and
those with pre-existing physical health problems (Cormac
et al., 2004). Although our study does not provide direct evi-
dence for the utility of ECG measurement in psychiatric in-
patients, it would seem clinically prudent that an ECG should
be carried out when physical health is being evaluated. In this
study under half of cases had an ECG in the year prior to
death, and this proportion was 57% in those with a history of
CV disease.
Second, services might improve the response to and treat-
ment of cardiac arrest. In the current study, we found CPR
equipment was not available on nearly one-third of wards, and
CPR was attempted in just over half of all cases, although
nearly 90% of staff had been trained in CPR. The management
of cardiac arrest or other collapse requires appropriate equip-
ment to be available and adequate numbers of staff with the
necessary training to provide CPR. Response times for cardiac
arrest teams trained in advanced life support should be as short
as possible and local arrangements should be justifiable, taking
into account the numbers and types of patients in a unit, and
the possible dispersal of in-patients within a multi-site trust.
Third, the use of restraint and seclusion were uncommon
in the current study and we cannot say whether these factors
contributed to SUD in these cases. Further monitoring of
patients who die in the context of restraint or seclusion is
required. Fourth, there is currently no uniform definition of
SUD (Bowker et al., 2003) and SUD is not systematically
identified by coroners. The development of a uniform practice
of identifying SUD would help identify factors contributing
to SUD. Post-mortem examinations and clinical reviews of all
SUD occurring on psychiatric in-patient wards are
encouraged.
Further, the findings from the case-control study make an
important contribution to our understanding of risk factors
for SUD in a psychiatric in-patient population. Clozapine, an
atypical antipsychotic, was associated with an increased risk
of SUD. Some studies have shown that atypical antipsy-
chotics may be associated with an increased risk of QT pro-
longation as with typical antipsychotics (Ray et al., 2009).
However, it may be that the mechanism underlying the asso-
ciation with SUD is not always related to the QT interval
(Coulter et al., 2001; Glassman, 2005; Ha
¨
gg et al., 2001;
Kang et al., 2000; Killian et al., 1999; Titier et al., 2005;
Wetterling, 2001). Although treatment with antipsychotic
drugs particularly atypical antipsychotics is an important
therapeutic option, clinicians should carefully weigh up the
benefits of drug treatments with the risks to the individual
patient.
Promazine, a typical antipsychotic, was also associated
with an increased risk of SUD. QT prolongation resulting in
torsade de pointes has been proposed as the mechanism under-
pinning sudden death in patients prescribed some typical anti-
psychotics. Generally, there was careful prescribing of drugs
known to carry a high risk of QT prolongation, with few expo-
sures to these drugs. However, there have been changes in pre-
scription practices during the time period of the study (e.g.
removal of droperidol; black box warning for thioridazine).
The small number of exposures to drugs with a high risk of
QT prolongation may reflect careful prescribing of these drugs
specifically, and drugs known to increase the risk of QT pro-
longation more generally. However, the known association
between some typical antipsychotics and SUD suggests con-
tinued cautious prescribing of psychotropic drugs, particularly
in patients with pre-existing CV problems.
The risk of SUD increased after exposure to benzodiaze-
pines. Benzodiazepines are used to manage acute agitation or
behavioural disturbances. Although these are an important
therapeutic option, one side effect of benzodiazepines is respi-
ratory depression and cautious prescribing of these drugs to
patients with respiratory disease is indicated (British National
Formulary, 2007).
Concurrent exposure to two or more antipsychotic drugs
was significantly associated with an increased risk of SUD.
Polypharmacy is not uncommon in people with mental illness,
particularly in older patients and those with co-morbid phys-
ical health problems. There may be a higher risk of SUD in
users of multiple medications because of drug interactions or
the additive risks of drugs. Further, it may be that patients
with current exposure to two or more drugs were more
severely ill than other patients.
Venlafaxine (and SNRIs more broadly) was associated
with a reduced risk of SUD. This finding is interesting given
the known association between cardiac toxicity and exposure
1540 Journal of Psychopharmacology 25(11)
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to venlafaxine (Howell et al., 2007), (although Isbister (2009)
showed that cardiotoxicity was not a common feature of ven-
lafaxine overdose except where exposure exceeded 8 g). It may
be that guidance suggesting the careful prescription of SNRIs
for depressed patients, particularly patients with pre-existing
cardiac disease, may have affected its use during the study
period (National Institute for Clinical Excellence, 2004).
Alternatively, it may be that the association is due to uniden-
tified confounding (e.g. more recently diagnosed psychiatric
illness). Further, the weak association between selective sero-
tonin reuptake inhibitors (SSRIs) and SUD is interesting.
Although paroxetine (an SSRI) was associated with a reduced
OR in the multivariate predictor model, SSRIs were not asso-
ciated with SUD in any other analyses. Similarly, trazodone
(a tricyclic-related drug) was associated with an increased risk
of SUD in the multivariate predictor model, although the
association did not reach significance in the unadjusted or
adjusted analyses. Further investigation of the association
between SUD and antidepressants is warranted.
Physical health problems, specifically a history of CV
disease and respiratory disease, resulted in approximately a
two-fold increase in the risk of SUD. To help reduce the
occurrence of SUD on psychiatric in-patient wards, mental
health services should seek to improve the physical health
care of mental health patients, with a particular emphasis
on patients with pre-existing CV and respiratory problems.
The association between primary diagnosis and SUD merits
discussion. The increased risk of SUD in patients with a
primary diagnosis of dementia may be the result of poorer
physical health of older patients.
Acknowledgements
We gratefully acknowledge the support of consultant psychiatrists,
members of the medical teams, and representatives from user and
carer organizations. We thank clinician Dr Phalaksh Walishetty for
his contribution to the validation of SUD cases.
Funding
This study was funded by the Department of Health, England and the
National Institute for Clinical Excellence, England. The National
Patient Safety Agency (NPSA) has funded the study since April 2005.
Declaration of interest
Louis Appleby was the National Director of Mental Health for
England and is now the National Director for Health and Criminal
Justice.
Contributors
The study was principally designed by L Appleby, J Shaw, T Amos,
G Lewis, S Thomas and N Ferrier, but all authors had input into
aspects of study design. Procurement of data from the NWCS and
HES and collection of questionnaire data was carried out by P
Turnbull, K Hadfield, K Windfuhr, U Hiroeh, C Dixon, S Flynn,
and H Watkinson, supported by T Amos. Initial data manipulation
was carried out by P Turnbull, D While, K Windfuhr, U Hiroeh, C
Dixon, and S Flynn. Case validation was carried out by N Swinson,
H Mehta and H Watkinson, with supervision from N Kapur, S
Thomas, and N Ferrier. Data analysis was carried out by P
Turnbull, D While, U Hiroeh, and P Skapinakis with supervision
from N Kapur, G Lewis, and L Appleby. The manuscript was
prepared by K Windfuhr, P Turnbull, D While, and U Hiroeh with
supervision from N Kapur. All authors commented on drafts of the
paper and contributed to the final version.
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    • "Although previous research has shown both decreased (Honkola et al., 2012; Leonard et al., 2011) and increased incidences (Weeke et al., 2012; Windfuhr et al., 2011) of SCD in association with benzodiazepine or antidepressant use, we found that the SCD incidence did not differ between patients in the case and control groups that used flunitrazepam and antidepressants. Therefore, we believe that benzodiazepine and antidepressant use are not direct causes of SCD. "
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    • "The utilisation and high consumption of benzodiazepines is of the utmost importance, as it has been demonstrated that prolonged consumption in the elderly population is associated with a risk for dementia (OR = 2.71, CI: 2.46-2.99) [28] [29] in addition to being a risk factor for sudden death (OR: 1.83) [30] and for hip fracture, without it being clear whether long half-life or long-acting benzodiazepines present a greater risk [31]. "
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    • "The prescribing frequency of antipsychotic drugs in geriatric patients is commonly overestimated particularly with respect to the administration of benzodiazepines, which are not recommended (DEGAM, DGN/DGPPN) [44] due to higher mortality and a higher tendency to fall. Thus, both conventional and atypical neuroleptics should only be administered for a short period of time (DEGAM, DGN/DGPPN) [18,19]. "
    [Show abstract] [Hide abstract] ABSTRACT: Dementia is a major and increasing health problem worldwide. This study aims to investigate dementia treatment strategies among physicians specialised in complementary and alternative medicine (CAM) by analysing prescribing patterns and comparing them to current treatment guidelines in Germany. Twenty-two primary care physicians in Germany participated in this prospective, multicentre observational study. Prescriptions and diagnoses were reported for each consecutive patient. Data were included if patients had at least one diagnosis of dementia according to the 10th revision of the International Classification of Diseases during the study period. Multiple logistic regression was used to determine factors associated with a prescription of any anti-dementia drug including Ginkgo biloba. During the 5-year study period (2004-2008), 577 patients with dementia were included (median age: 81 years (IQR: 74-87); 69% female). Dementia was classified as unspecified dementia (57.2%), vascular dementia (25.1%), dementia in Alzheimer's disease (10.4%), and dementia in Parkinson's disease (7.3%). The prevalence of anti-dementia drugs was 25.6%. The phytopharmaceutical Ginkgo biloba was the most frequently prescribed anti-dementia drug overall (67.6% of all) followed by cholinesterase inhibitors (17.6%). The adjusted odds ratio (AOR) for receiving any anti-dementia drug was greater than 1 for neurologists (AOR = 2.34; CI: 1.59-3.47), the diagnosis of Alzheimer's disease (AOR = 3.28; CI: 1.96-5.50), neuroleptic therapy (AOR = 1.87; CI: 1.22-2.88), co-morbidities hypertension (AOR = 2.03; CI: 1.41-2.90), and heart failure (AOR = 4.85; CI: 3.42-6.88). The chance for a prescription of any anti-dementia drug decreased with the diagnosis of vascular dementia (AOR = 0.64; CI: 0.43-0.95) and diabetes mellitus (AOR = 0.55; CI: 0.36-0.86). The prescription of Ginkgo biloba was associated with sex (female: AOR = 0.41; CI: 0.19-0.89), patient age (AOR = 1.06; CI: 1.02-1.10), treatment by a neurologist (AOR = 0.09; CI: 0.03-0.23), and the diagnosis of Alzheimer's disease (AOR = 0.07; CI: 0.04-0.16). This study provides a comprehensive analysis of everyday practice for treatment of dementia in primary care in physicians with a focus on CAM. The prescribing frequency for anti-dementia drugs is equivalent to those found in other German studies, while the administration of Ginkgo biloba is significantly higher.
    Full-text · Article · Aug 2011 · BMC Neurology
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