|
OJHAS Vol. 9, Issue 3:
(Jul - Sep, 2010) |
|
|
| A study of factors
delaying hospital arrival and predictors of mortality in patients presenting
to emergency department with stroke: A developing state scenario |
|
Mudassir Azeez Khan,
Professor and Head,
Ganraj Bhat Sankapithilu, Research Assistant,
Vinayak Nagaraja, Research Assistant,,
Department of Community Medicine, Mysore Medical College and
Research Institute, Mysore,
Subhash Chandra, Post-doctoral Research Fellow, Department of Emergency
Medicine, Mayo Clinic, Rochester, MN-55905 |
|
|
| |
|
|
|
|
|
|
Address For Correspondence |
Professor and Head,
Department of Community
Medicine,
Mysore Medical College
and Research Institute,
Mysore, India.
E-mail:
mudkhan@gmail.com |
|
|
|
|
|
Khan MA, Sankapithilu
GB, Nagaraja V, Chandra S. A study of factors
delaying hospital arrival and predictors of mortality in patients presenting
to emergency department with stroke: A developing state scenario. Online J Health Allied Scs.
2010;9(3):2 |
|
|
|
|
Submitted: Sep 2, 2010;
Accepted:
Sep 27, 2010; Published: Oct 15, 2010 |
|
|
|
|
|
|
|
| |
|
| Abstract: |
|
Background: Thrombolytic therapy
for acute ischemic stroke has recently become available in India but
its success depends on initiating the treatment in the narrow therapeutic
time window. There is commonly a delay of several hours before patients
with acute stroke seek medical attention. Materials and Methods:
A prospective study was conducted to assess the factors influencing
this delay in admission of acute stroke cases. 134cases (101 males,
33 females) of acute stroke that arrived within 72 hours at our hospital
casualty were recruited. A standardized structured questionnaire was
given to patients or their attendants. Results: The median
time to casualty arrival was 9 hours with 13.4% cases arriving within
3 hours and 36.5 % cases within 6 hours. Distances from hospital, referral,
belief in myths and alternate medicine and low threat perception of
symptoms of stroke were independent factors associated with delay in
arrival. Living in city, day time onset, urgency shown by attendant,
availability of transport and presence of family history were associated
with early arrival. There was no correlation with patients' or attendants'
sex, educational status, history of previous stroke or transient ischemic
attack, subtype or severity of stroke, time of stroke and availability
of transport. 134 patients (65.7% were from rural population, 55.22%-smokers,
46.76%-alcoholics) with mean (SD) age of 53.83+/-18.02years [significantly
lower in females (mean difference=9.73years p=0.002)], were admitted
and diagnosed to have stroke. 87.3% had first episode of stroke and
12.7 had more than one episode of stroke. ICF rate was 26.1%. ICF rate
has no relation with age (p=0.516), sex (p=0.460), number of episodes
(0.795), underlying hypertension (p=0.905). Odds of diabetics dying
were 12 times higher than non-diabetics. Inpatient mortality was also
significantly higher in smokers compared with non-smokers (p=0.004),
in patients with right-sided compared with left-sided hemiplegic (p=0.029)
and who couldn’t afford computed tomography (CT) scan (p=0.007). Kaplan
Meier curve in Image-1 shows the survival following admission to emergency
ward. Conclusion: Adequate
measures need to be taken to improve the public awareness of stroke
and the role of local doctors. Our study has shown that active smokers,
involvement of the right side and non performance of CT were independent
predictors of mortality which have not been shown earlier. Also, we
found that diabetes mellitus is independent predictor of mortality in
stroke, which has been seen in earlier studies too.
Key Words: Epidemiology;
Stroke; Thrombolytic therapy
|
|
Stroke
is predicted as the second leading cause of death and disability in
developed nations.1 In India, the prevalence of stroke was
reported as 471.58 per 100,000 and (545.10 per 100,000 when age is standardized
to the world standard population) with the annual incidence rate of
123 per 100,000 (145 per 100,000 on standardization to the world stand
population).2 This is higher than in studies reported from
the developed nations.3-6
Indian studies have also reported 30-day case fatality rate of over
41%. Despite such high prevalence and fatality, in the year 2000, India
was ranked amongst the countries lacking sufficient research
data on stroke.7 With growing evidences of improved outcome
in stroke with timely thrombolytic therapy, reaching the hospital early
after stroke onset becomes an issue of high priority. Several studies
have emphasized on delay in reaching the hospital but evidences from
India are still lacking. We sought to determine this delay in reaching
the hospital after stroke onset and in-hospital mortality in South Indian
population.
This prospective observational
hospital based study has been conducted in the emergency ward of Department
of Medicine, K. R. Hospital, Mysore, Karnataka, India. The study protocol
has received institutional ethical clearance. Our hospital is a 1,330-bed
hospital which includes 335 beds in General Medicine. It is a tertiary
care and academic center, located in Southern India. K. R. Hospital
serves as major referral center for middle to low socioeconomic strata
population. Its catchment area includes 5 districts, Mysore, Mandya,
Chamrajnagar, Hassan and Kodagu encompassing 5,467,316. Most patients
from rural area are being seen first at primary health centers and are
then referred to higher centers. The referral to government versus private
hospital mainly depends on financial affordability. Availability of
ambulance service in Indian sub-urban and rural area is very poor and
only 12% of patients reach hospital by ambulance.8
Acute care to all patients
is being provided at the emergency ward in department of medicine. Since,
our institution does not have neurologists, stroke cases are managed
under department of medicine. Thrombolytic therapy for stroke is being
administered in our hospital but in very low fraction as is the case
in majority of government hospitals in India which have patient input
form middle to low socio-economic strata.9
Subject selection:
Patients presenting
to the emergency ward with stroke over a period of one and half year,
December 2007 through May 2009, were selected. Stroke was defined as
a neurological deficit of cerebrovascular cause that persists beyond
24 hours or is interrupted by death within 24 hours. Diagnosis was made
by the physician on duty. Subject identification has been done by manual
search of emergency ward admission log. Case sheets of patients with
following diagnoses were screened to identify all the potentially eligible
subjects; stroke, transient ischemic attacks (TIA), cerebrovascular
accidents (CVA), cerebral or cerebellar or pontine or medullary or internal
nuclear or intracranial or infarction or ischemia or thrombosis or hemorrhage
and were reviewed further. Subject enrollment has been done for 1 day
a week, 9:00 AM to 5:00 PM, by the study investigators. Informed
consent was obtained from the all the subjects at the time of enrollment
to the study.
Data Collection
and Follow-up: Data collection has
been done using pre-determined data collection form. Demographic
and clinical characteristic of enrolled subjects were collected at the
time of admission; duration since onset of symptoms as noticed by the
patient or relatives, source of referral, state of patient at the time
of presentation, age, gender, socioeconomic status, smoking behavior,
alcohol intake, medications, previous stroke episodes, initial blood
pressure (mean of three readings), side of involvement and clinical
impression. All the patients were subsequently followed up till their
discharge or death, whichever came first, and notes were made regarding
hospital course and outcome. Primary outcome variable was death during
current hospitalization.
Data Analysis: Data was entered into
Microsoft excel-2003 from the data collection form. Distribution of
observation for individual has been described using percentage, mean
with standard deviation and median with range. Pearson’s’ chi-square
or Fishers exact test and independent sample t-test were used to see
the relation between categorical versus categorical and categorical
versus continuous, respectively. Survival was calculated using Kaplan-Meier
curve. Cox proportional hazards model was constructed to identify independent
predictors of inpatient mortality. All data analyses were performed
using SPSS (Statistical Package for the Social Sciences) for windows,
version 11.5
Over the period of
18 months, 164 patients were admitted to the emergency ward during the
specified recruitment time. 14 subjects denied consent, 16 were missed
and 134 subjects were enrolled in this study. Clinical and demographical
characteristics of studied subjects are shown in Table 1. More than
half of the patients (51.5%) presented to the hospital directly and
the rest were referred, majority from primary health centers (28.4%).
Sixty eight percent were from rural areas and 78 (58.2%) patients never
attended school. CT scan in first 12 hours was performed in 48 patients
and 7 (5.2%) patients received thrombolytics, 31% received anti hypertensive and
all subjects received Aspirin. Only 7 subjects were thrombolysed by neurologists. All the patients who
received thrombolysis survived. All the patients were followed up till
their discharge or death.
|
Table 1: Demographical
and clinical characteristics of studied cohort |
|
Variables |
Observations (n=134) |
|
Age (mean ± SD*) |
53.8 ± 18.0 |
|
Gender |
|
Male |
101 (73.4%) |
|
Female |
33 (26.6%) |
|
Smokers (current smokers %) |
76 (90.1%) |
|
Alcoholics |
62 (46.3%) |
|
Referrals |
|
Came directly
|
69 (51.5%) |
|
PHCs
|
38 (28.4%) |
|
District Hospital
|
9 (6.7%) |
|
Nursing home/general practitioner
|
18 (13.4%) |
|
First ever episode of Stroke
|
117 (87.3%) |
|
Repeated episode of stroke |
17 (12.7%) |
|
Known Hypertensive |
52 (38.8%) |
|
Known Diabetics |
19 (6.7%) |
|
Side of involvement |
|
Right |
72 (53.7%) |
|
Left |
24 (17.9%) |
|
Bilateral |
38 (28.4%) |
|
*Standard Deviation |
|
Figure 1:
Kaplan Meir curve showing overall survival in stroke patients |
Median delay in reaching
to hospital from the time of onset of stroke was 9 hours, 18 (13.4%)
patients reached the hospital within 3 hours and 31 (23.1%) reached
within 6 hours. This delay was more in females compared to males
but the difference was not statistically significant (p = 0.71).
Of the 134 subjects,
67 had shown improvement in neurological deficits during hospitalization,
30 had stable deficits, 2 had shown worsening and 35 subjects expired.
Figure 1 shows the Kaplan–Meier curves for survival. Majority of deaths
occurred early during the course of hospitalization. Subjects who survived
till 9th day of hospitalization, in-hospital mortality was
nil. In univariant analysis, in-hospital mortality was found to have
no relation with age (p = 0.516), gender (p = 0.460), prior stroke episodes
(p = 0.528), underlying hypertension (p = 0.536), and involvement of
right side compared with left side (p= 0.4). There was no significant
difference in mortality between patients reaching hospital within 3
hours versus patients who reached hospital after three hours (p = 0.532).
Inpatient mortality was significantly higher in smokers compared with
non-smokers (p = 0.003), diabetics compared with non-diabetics (p =
0.001) and those who could not afford Computed Tomography (CT) scan
(p = 0.007). Table 2 shows result of Cox proportional hazards models
which identify smoking and diabetes as independent predictors of in-hospital
mortality.
Table 2: Independent Predictors of inpatient mortality |
|
Hazard ratio |
95.0% CI |
Significance |
|
Lower |
Upper |
|
Age |
2.066 |
.988 |
4.31 |
0.054 |
|
Gender |
1.752 |
0.627 |
4.896 |
0.285 |
|
DM |
4.661 |
1.406 |
15.458 |
0.012 |
|
HTN |
1.471 |
0.546 |
3.963 |
0.446 |
|
Smoking |
3.995 |
1.393 |
11.463 |
0.010 |
|
Delay in reaching hospital |
.999 |
0.994 |
1.005 |
0.797 |
|
Number of episode |
.990 |
0.339 |
2.890 |
0.986 |
|
CT scan |
.548 |
0.195 |
1.540 |
0.254 |
|
Side of involvement |
1.289 |
0.867 |
1.918 |
0.209 |
|
Table 3-Univariant
analysis of in- patient mortality |
|
Univariant analysis, In-hospital
mortality |
Significance (p value) |
|
Age |
0.516 |
|
Gender |
0.460 |
|
Before and after 3 hours |
0.532 |
|
Prior stroke episodes |
0.528 |
|
Hypertension |
0.536 |
|
DM |
0.001 |
|
Smoking |
0.003 |
|
Involvement of right side compared
with left side |
0.400 |
|
Patients who could not afford Computed Tomography (CT)
scan |
0.007 |
|
Early Arrival |
p value |
|
Living in city |
(0.027) |
|
Distance<10 km |
(0.03) |
|
Day time onset |
(0.01) |
|
Family history |
(0.01) |
|
Male attendant |
(0.56) |
|
Attendant's Relationship with the patient |
(0.34) |
|
Urgency shown by attendant |
(0.01) |
|
Prior stroke episodes |
(0.883) |
|
Availability of transport |
(0.01) |
|
GCS score |
(0303) |
|
Aphasia |
(0.338) |
|
H/O hypertension, diabetes, IHD |
(0.834) |
|
Late Arrival |
p value |
|
Female gender |
(0.71) |
|
Educational status of patient |
(0.84) |
|
Attendant's educational status |
(0.89) |
|
Lack of knowledge about stroke |
(0.83) |
|
Low threat perception |
(0.01) |
|
Belief in Myths and alternate medicine |
(0.01) |
|
Below Poverty Line |
(0.377) |
|
Referral |
(0.017) |
|
Table 4 Type of Intracranial lesion
among patients |
|
Thrombosis |
70 |
| Hemorrhage |
51 |
| Embolism |
3 |
| Trauma |
0 |
| Infection |
3 |
| SOL |
7 |
Summary
of Major Findings: Only thirteen
percent patients reached hospital within 3 hours of onset of symptoms
with median delay in reaching the hospital being 9 hours. Overall, in-hospital
mortality was 26.1% and all deaths occurred within first 8 days of hospitalization.
Smoking and diabetes were independent predictors of in-hospital mortality.
Delay in the
Management: As per recommendations
made by American Academy of Neurology in 1996, thrombolytics were not
shown to be effective beyond 3 hours after onset of stroke.10
In a pooled analysis of 6 randomized placebo-controlled trials of intravenous
r-tPA by ATLANTIS, ECASS, and NINDS r-tPA study group investigators,
beneficial effect of r-tPA was proved beyond 3 hours since the
odds ratio for a favorable outcome was 1·40 (1·05–1·85) for those
treated within 181–270 minutes.11 However, the beneficial
effect did not extend beyond 6 hours11. This was further
supported by systematic review conducted by Wardlaw et al., and randomized
controlled trial by ECASS Investigators,12.13 On putting
all these together, thrombolytic therapy within 3 hours of onset of
stroke has advantage in terms of mortality and functional out come.
Its use between 3 to 4.5 hours does not reduce the mortality but increases
functional outcome at discharge and at 3 months.
To be able
to benefit from thrombolytic therapy, patients need to reach hospital
within the above mentioned duration. In our cohort, only 13.4% reached
the hospital within duration of definitive benefit and 23.1% could reach
in duration where use of thrombolytics could have improved the functional
outcome. In other studies, percentage of patients reaching hospital
within 3 hours have ranged between 28.0 to 61.4 with average delay in
reaching to hospital ranging from 5.1 to 5.6 hours.14-18
The maximum number of patients (61.4%) reaching the hospital within
3 hours were reported by Turin et al., from Takashima Stroke Registry,
Japan. They perceived that higher stroke severity was associated with
shorter delay in reaching hospital which is supported by other studies
too.15-18 Other factors reported to be associated with
shorter duration of hospital arrival are use of Emergency Medical Services
(EMS) or ambulance, time of stroke onset, female sex, perceived adequacy
of income, whereas advanced age and living alone were associated with
longer delay.14-18
In our cohort,
majority of patients had low educational status and were from rural
areas where transportation is not good and health facilities are located
far away. Also, this population is not well aware of stroke symptoms.
These factors were potential contributors in delay to reach the hospital.
In addition, female gender had higher delay in our study which could
be the result of females using health services less frequently than
men, even when they are available. This could be because
they do not recognize the need to seek medical attention or cannot overcome
social and cultural barriers.19
In-hospital
Mortality: Several studies
have been reported on in-hospital mortality from across the globe. This
was significantly lower in the western world when compared with developing
nations.4,20 There is only limited data available on stroke
related mortality in India. The overall 30-day case fatality noted in
the Kolkata study was 41.08% (men, 38.18%; women, 43.24%) which is significantly
higher than Western countries (17 to 33%).3-6,20 Our
study results support higher in-hospital mortality associated with stroke
in India.
In
recent years, several factors have been described to independently predict
in-hospital mortality in stroke which are advancing age, female gender,
severity of stroke, associated co-morbid conditions, atrial fibrillation,
previous stroke/transient ischemic attack.20-22 Our study
supports DM and smoking to be independent predictors of in-hospital
mortality in stroke.
One of the
few limitations of this study was smaller sample size. Small number
of subjects in each group decreased the strength of association. Stroke
severity at the time of presentation which is well proven to have impact
on mortality, was not recorded. Also, we had calculated delay in reaching
hospital from the time of recognition of symptoms by patient or patient
relatives. This may have underestimated the actual delay in reaching
the hospital from the time of onset of stroke as many patients could
have had stroke in sleep. We did not enroll patients over weekends and
nights where delay may be substantially different.
Even with these
limitations, we believe these findings enhance our current knowledge
regarding the epidemiology of stroke among South Indian population and
provide an initial departure point for potential strategies for better
management of stroke like strengthening EMS/ambulance service, increasing
awareness about stroke symptoms and seeking health care.
- Murray CJ, Lopez
AD. Alternative projections of mortality and disability by cause 1990-2020:
Global Burden of Disease Study. Lancet. 1997;349(9064):1498-1504.
- Das SK, Banerjee
TK et al. A prospective community-based study of stroke in Kolkata,
India. Stroke. Epub 2007 Feb 1;38(3):906-910.
- Brown RD, Whisnant
JP et al. Stroke incidence, prevalence, and survival: secular trends
in Rochester, Minnesota, through 1989. Stroke. 1996;27(3):373-380.
- Kolominsky R, Sarti
C et al. A prospective community-based study of stroke in Germany--the
Erlangen Stroke Project (ESPro): incidence and case fatality at 1, 3,
and 12 months. Stroke 1998;29(12):2501-2506.
- Rothwell PM, Coull
AJ et al. Change in stroke incidence, mortality, case-fatality, severity,
and risk factors in Oxford shire, UK from 1981 to 2004 (Oxford Vascular
Study). Lancet 2004;63(9425):1925-1933.
- Syme PD, Byrne AW
et al. Community-based stroke incidence in a Scottish population: the
Scottish Borders Stroke Study. Stroke. Epub 2005 Aug 4;36(9):1837-1843.
- Stroke epidemiological
data of nine Asian countries. Asian Acute Stroke Advisory Panel (AASAP).
J Med Assoc Thai. 2000;83(1):1-7.
- Pandian JD, Srikanth
V et al. Poverty and stroke in India: a time to act. Stroke. Epub 2007
Oct 22;38(11):3063-3069.
- Durai PJ, Padma
V et al. Stroke and thrombolysis in developing countries. Int J Stroke 2007;2(1):17-26.
- Practice
advisory: thrombolytic therapy for acute ischemic stroke--summary statement.
Report of the Quality Standards Subcommittee of the American Academy
of Neurology. Neurology 1996;47(3):835-839.
- Hacke W, Donnan
G et al. Association of outcome with early stroke treatment: pooled
analysis of ATLANTIS, ECASS, and NINDS r-tPA stroke trials. Lancet.
2004;363(9411):768-774.
- Hacke W, Kaste
M et al. Thrombolysis with alteplase 3 to 4.5 hours after acute ischemic
stroke. N Engl J Med 2008;359(13):1317-1329.
- Wardlaw JM, Murray
V et al. Thrombolysis for acute ischemic stroke. Cochrane Database Syst
Rev 2009(4):CD000213.
- Derex L, Adeleine
P et al. Factors influencing early admission in a French stroke unit.
Stroke 2002;33(1):153-159.
- Chang KC, Tseng
MC et al. Pre hospital delay after acute stroke in Kaohsiung, Taiwan.
Stroke. Epub 2004 Feb 12;35(3):700-704.
- Maze LM, Bakas
T. Factors associated with hospital arrival time for stroke patients.
J Neurosci Nurs 2004;36(3):136-141, 155.
- Maestroni A, Mandelli
C et al. Factors influencing delay in presentation for acute stroke
in an emergency department in Milan, Italy. Emerg Med J. 2008;25(6):340-345.
- Turin TC, Kita
Y et al. The time interval window between stroke onset and hospitalization
and its related factors. Neuroepidemiology Epub 2009 Jul 27;33(3):240-246.
- Key P. Women, health
and development, with special reference to Indian women. Health Policy
and Planning. 1987;2(1):58-69.
- Sweileh WM, Sawalha
AF et al. Predictors of in-Hospital Mortality after Acute Stroke: Impact
of Gender. Int J Clin Exp Med. Epub 2009 Jan 30;2(1):41-47.
- Heuschmann PU,
Kolominsky PL et al. Predictors of in-hospital mortality and attributable
risks of death after ischemic stroke: the German Stroke Registers Study
Group. Arch Intern Med. 2004;164(16):1761-1768.
- Carter AM, Catto
AJ et al. Predictive variables for mortality after acute ischemic stroke.
Stroke. Epub 2007 Apr 19;38(6):1873-1880
|
