Abstract
Objectives
The primary objective was to report the 1-year all-cause mortality among patients with stroke. The secondary objectives were (1) to report the mortality stratified by type of stroke and sex and (2) to report predictors of 1-year mortality among patients with stroke.
Design
A prospective cohort study.
Setting
Institutional–stroke care unit of a tertiary care hospital
Participants
Patients who were treated in the study institution during 2016–2020 for acute stroke and were followed up for a period of 1 year after stroke in the same institution.
Main outcome measures
The main outcome measures were the mortality proportion of any stroke and first ever stroke cohorts at select time points, including in-hospital stay, along with 2 weeks, 2 months, 6 months and 1 year after index stroke. The secondary outcomes were (1) mortality proportions stratified by sex and type of stroke and (2) predictors of 1-year mortality for any stroke and first ever stroke.
Results
We recruited a total of 1336 patients. The mean age of participants was 61.6 years (13.5 years). The mortality figures for 2 weeks, 2 months, 6 months and 12 months after discharge were 79 (5.9%), 88 (6.7%), 101 (7.6%) and 114 (8.5%), respectively, in the full cohort. The in-hospital mortality was 45 (3.4%). The adjusted analysis revealed 3 predictors for 1-year mortality after first ever stroke—age, pre-treatment National Institutes of Health Stroke Scale (NIHSS) score and Modified Rankin Scale (mRS) score at baseline. The same for the full cohort had only two predictors—age and pre-treatment NIHSS score.
Conclusion
Mortality of stroke at 1-year follow-up in the study population is low in comparison to several studies published earlier. The predictors of 1-year mortality after stroke included age, NIHSS score at baseline and mRS score at baseline.
Keywords: Stroke, EPIDEMIOLOGY, STROKE MEDICINE
Strengths and limitations of this study.
The strengths of this study include a large sample size and minimal lost to follow up.
The analytical approach can significantly reduce residual confounding.
The single study setting may reduce the generalizability of study findings.
The extraction of data was from hospital information system and this might have resulted in low accuracy of the comorbid profile.
Introduction
Stroke is the leading cause of mortality, disability and economic loss across the globe. Patients with stroke require immediate care and long-term follow-up for better outcomes.1 2World stroke organisation estimated the global burden of new stroke to be 13.7 million per year.2 3 One in four persons above the age of 25 years will be affected with stroke in their life time.2 3
Globally, developing nations bear considerable burden of stroke (70%).4 Mortality and disability adjusted life years (DALY) due to stroke is huge (87%) in low-income and middle-income countries (LMICs).4 There are 4.85 million stroke deaths and 91.4 million DALYs annually, in LMICs compared to1.6 million deaths and 21.5 million DALYs in high-income countries.4 The incidence of stroke has declined by 42% in high-income countries but doubled in LMICs during the last 4 decades.5–7
The global burden of disease study puts the number of incident cases of stroke in India at 1.29 million (2019).8 The deaths due to stroke in India is approximately 699 000 per year.8
Several stroke cohorts from different studies across the globe have reported post stroke mortality at various time points including death during in-hospital treatment.9–20 They reported post-stroke mortality at 1 year ranging from as low as 2.1% to as high as 34.3%.9–20A recently published systematic review reported that the 1 month case fatality rate for stroke in India ranged between 18% and 42%.21
Previous studies have identified several predictors of post-stroke mortality and poor outcome at 1 year.18 22The Anglia Stroke Clinical Network Evaluation Study reported that increasing age, haemorrhagic stroke, total anterior circulation stroke type, higher pre-stroke frailty, history of hypertension and ischaemic heart disease and admission hyperglycaemia predicted 1-year mortality.18 The Prospective Cohort with Incident Stroke study reported that the independent predictors for poor outcome 1 year after first-ever ischaemic stroke were age, education, National Institutes of Health Stroke Scale (NIHSS) score, pre-stroke physical disability and diabetes mellitus.22
Hospital-based registries covering stroke and related disorders are rare in India. This is despite the fact that a properly executed hospital based registry can in all probability improve the clinical decision-making, improve patient care, predict future needs and identify areas of concern related to stroke management. All these factors can also improve the overall outcomes of patients with stroke in terms of reducing the disability, increasing the survival probability and improving the quality of life. Such a registry will also stimulate research initiatives in this area.23–25
There is a definite need for identifying the current mortality profile of acute stroke in the Indian context. Such data will identify the current lacunae in management of stroke as well as provide opportunities to improve the mortality outcome in stroke. The current paucity of data related to the predictors of mortality among patients with acute stroke in India appears to be a hindrance for appropriate interventions in this direction. The current study aims to address these two deficiencies.
The primary objective of this study was to report the overall 1-year all-cause mortality among patients with stroke. The secondary objectives were (1) to report the mortality rate of stroke in general as well as the same stratified by type of stroke and sex and (2) to report the predictors of 1-year mortality among patients with stroke.
Methods
Selection and description of study participants
The current study is a hospital registry-based prospective cohort study. All subjects with confirmed stroke who underwent treatment from the comprehensive stroke care centre of the study institution (Amrita Institute of Medical Sciences, Kochi, Kerala, India) during the study period (January 2016–June 2020) were included in the registry. We included (1) patients with first-ever stroke and (2) patients with recurrent stroke if the index admission was due to a new stroke. We excluded (1) patients with no reliable medical record or neuroimaging studies, (2) patients with epidural or subdural haematomas, or intracerebral haemorrhage secondary to tumours or arteriovenous malformation and (3) lost to follow-up patients with stroke and patients with insufficient data related to study objectives.
We used the data from the Anglia Study to calculate the sample size for 1-year mortality after stroke.18This study reported a 1-year mortality of 31.8% for patients after an episode of acute stroke.18 We used 3% absolute precision and 5% α error giving us a minimum sample size of 913 patients. We included a total of 1336 considering incomplete data and lost to follow-up.
Technical information
All data were captured by an electronic database. A study questionnaire was predesigned in paper and tested on 50 patients. The same was validated as per response to individual questions under each domain. The validated questionnaire was cross checked by consultants and approved after consensus. This version was converted to an electronic database (MS Access). The electronic template was tested on 30 patients for data accuracy and ease of administration. Appropriate changes were made after analysing this preliminary data.
All information related to demographics, basic patient details, diagnostic/procedural information, treatment details and follow-up status were captured from the hospital information system by a research associate who was trained in stroke-related data capture before the start of the data collection. The data were entered in electronic data base (MS Access). Images (CT and MRI) were retrieved from the med-vision system of the institution and evaluated/scored according to standard protocols by research personnel under the supervision of the principal investigator (PI). The types of stroke were assigned by the PI (senior neurology consultant) using ICD codes. The subtypes of stroke were defined using universally accepted criteria: ischaemic stroke and intracerebral haemorrhage on the basis of clinical and neuroimaging findings (CT or MRI) and subarachnoid haemorrhage on the basis of clinical, neuroimaging or cerebrospinal fluid findings. Transient ischaemic attack (TIA) was defined as a transient episode of neurological dysfunction caused by focal brain, spinal cord or retinal ischaemia, without acute infarction, with symptoms usually lasting <24 hours. The patient status at specific time points were determined from Electronic Medical Records (EMR) in those who completed the follow-up visits. In the case of patients failing to visit the hospital during the scheduled visits, telephonic contact was established with the family by the registry personnel and patient status was extracted from the patient/caretaker.
The severity of stroke was assessed by NIHSS score.26 The Modified Rankin Scale (mRS) was used to measure the stroke outcome.27 We classified acute ischaemic stroke using the Trial of Org 10 172 in Acute Stroke Treatment (TOAST) classification.28
Patient and public involvement
Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.
Statistical analysis
Statistical analysis was performed using IBM SPSS V.20.0 (Chicago, IL, USA). We summarised continuous variables using mean (SD) and categorical variables using frequency and percentage. Univariate analyses of survival were carried out by Kaplan-Meier method and the evaluations of differences were performed using log rank test. We did multivariate survival analysis using the Cox Proportional hazard model. We report the adjusted HR with 95% CIs for factors independently associated with 1-year mortality after stroke. A two-sided p value of less than 0.05 was considered as statistically significant.
Results
The stroke registry provided data from 1430 patients with a documented history of stroke who underwent initial care at the study institution. We excluded 94 patients who had no follow-up data after discharge providing us with a cohort of 1336 patients. The study flow chart is presented as figure 1 below. Details of excluded patients are presented as online supplemental appendix table 1. A total of 1046 (78.3%) patients completed their 1-year follow-up by visiting the study institution and the rest were followed up telephonically by study personnel. In this cohort, 1179 (88.2%) patients were admitted for first ever stroke and the remaining 157 (11.8%) were admitted for recurrent stroke. The baseline details of the cohorts are presented as table 1.
Figure 1.
Study flow chart.
Table 1.
Baseline characteristics of the study population—full cohort and first ever stroke cohort
| Full cohort | |||
| Variables | Total (n=1336) |
Male (n=949, 71%) |
Female (n=387, 29%) |
| Age in years | 61.25±13.5 | 60.86±12.9 | 62.2±14.7 |
| Risk factors | |||
| Diabetes mellitus | 627 (46.9) | 456 (48.1) | 171 (44.2) |
| Hypertension | 849 (63.5) | 611 (64.4) | 238 (61.5) |
| Dyslipidaemia | 426 (31.9) | 306 (32.2) | 120 (31) |
| CRF | 59 (4.4) | 50 (5.3) | 9 (2.3) |
| OLD TIA | 65 (4.5) | 55 (5.4) | 10 (2.5) |
| Stroke | 157 (11.8) | 116 (12.2) | 41 (10.6) |
| Hypothyroidism | 84 (6.3) | 37 (3.9) | 47 (12.1) |
| Coagulopathies | 46 (3.4) | 38 (4) | 8 (2.1) |
| Family history stroke | 29 (2.2) | 22 (2.3) | 7 (1.8) |
| Heart disease | |||
| RHD | 46 (3.4) | 27 (2.8) | 19 (4.9) |
| Prosthetic valve | 19 (3.4) | 7 (0.7) | 11 (2.8) |
| CAD | 184 (13.8) | 154 (16.2) | 30 (7.8) |
| AF | 61 (4.6) | 41 (4.3) | 20 (5.2) |
| First ever stroke cohort | |||
| Variables | Total (n=1179) |
Male (n=833, 70.7%) |
Female (n=346, 29.3%) |
| Age in years | 60.77±13.6 | 60.38±13 | 61.70±15 |
| Risk factors | |||
| Diabetes mellitus | 530 (44.9) | 384 (46.1) | 146 (42.2) |
| Hypertension | 732 (62.1) | 525 (63) | 207 (59.8) |
| Dyslipidaemia | 367 (31.1) | 261 (31.3) | 106 (30.6) |
| CRF | 51 (4.3) | 43 (5.2) | 8 (2.3) |
| OLD TIA | 51 (4.5) | 41 (4.9) | 10 (2.9) |
| Hypothyroidism | 73 (6.3) | 30 (3.6) | 43 (12.4) |
| Coagulopathies | 38 (3.2) | 30 (3.6) | 8 (2.3) |
| Family history stroke | 27 (2.3) | 20 (2.4) | 7 (2) |
| Heart disease | |||
| RHD | 43 (3.7) | 26 (3.1) | 17 (4.9) |
| Prosthetic valve | 14 (1.2) | 6 (0.7) | 8 (2.3) |
| CAD | 139 (11.8) | 116 (13.9) | 23 (6.7) |
| AF | 52 (4.4) | 35 (4.2) | 17 (4.9) |
Values are mean (SD) or frequency (%).
AF, atrial fibrillation; CAD, coronary artery disease; CRF, chronic renal failure; RHD, rheumatic heart disease; TIA, transient ischaemic attack.
bmjopen-2022-061258supp001.pdf (95KB, pdf)
The mean age of the study patients was61.3 years (13.5 years). Diabetes, hypertension and dyslipidaemia were present in 627 patients (46.9%), 849 patients (63.5%) and 4 26 patients (31.9%), respectively. A total of 157 patients (11.8% patients) were admitted with a recurrence of stroke. The baseline details stratified by the type of stroke are presented as online supplemental appendix table 2.
The profile of symptoms at presentation are presented in table 2.
Table 2.
Symptom profile—full cohort and first ever stroke cohort
| Full cohort | |||
| Variables | Total (n=1336) (%) | Male (n=949) (%) | Female (n=387) (%) |
| Aphasia | 156 (11.7) | 105 (11.1) | 51 (13.2) |
| Hemiplegia | 214(16) | 145 (15.3) | 69 (17.8) |
| Ataxia | 141 (10.6) | 108 (11.4) | 33 (8.5) |
| Dysarthria | 452 (33.8) | 318 (33.5) | 134 (34.6) |
| Loss of consciousness | 66 (4.9) | 39 (4.1) | 27 (7.0) |
| Facial palsy | 229 (17.1) | 163 (17.2) | 66 (17.1) |
| Loss of vision | 49 (3.7) | 33 (3.5) | 16 (4.1) |
| First ever stroke cohort | |||
| Total (n=1179) (%) | Male (n=833) (%) | Female (n=346) (%) | |
| Aphasia | 127 (10.8) | 84 (10.1) | 43 (12.4) |
| Hemiplegia | 177 (15.0) | 114 (13.7) | 63 (18.2) |
| Ataxia | 117 (9.9) | 91 (10.9) | 26 (7.5) |
| Dysarthria | 402 (34.1) | 281 (33.7) | 121 (35.0) |
| Loss of consciousness | 62 (5.3) | 38 (4.6) | 24 (6.9) |
| Facial palsy | 197 (16.7) | 139 (16.7) | 58 (16.8) |
| Loss of vision | 38 (3.2) | 26 (3.1) | 12 (3.5) |
The symptom profile in the full cohort was dominated by dysarthria (452 patients, 33.8%), facial palsy (229 patients, 17.1%), hemiplegia (214 patients, 16.0%), aphasia (156 patients, 11.7%) and ataxia (141 patients, 10.6%). The pre-treatment NIHSS was low (<4) in 581 patients (43.5%), intermediate (4–10) in 458 patients (34.3%) and high (>10) in 297 patients (22.2%) in the full cohort.
The details of the subtypes of stroke for both cohorts are presented as table 3.
Table 3.
Stroke subtypes for the entire cohort and for first ever stroke cohort
| Over all cohort | |||
| Type of stroke | Total (n=1336) |
Male (n=949) |
Female (n=387) |
| n (%) | n (%) | n (%) | |
| Stroke–TIA | 196 (14.7) | 137 (14.43) | 59 (15.24) |
| Stroke–AIS | 907 (67.9) | 650 (68.49) | 257 (66.40) |
| Stroke–ICH | 132 (9.9) | 93 (9.7) | 39 (10.07) |
| Stroke–SAH | 12 (0.9) | 8 (0.84) | 4 (1.03) |
| UD | 89 (6.7) | 61 (6.4) | 28 (7.2) |
| First ever stroke cohort | |||
| Type of Stroke | Total (n=1179) |
Male (n=833) |
Female (n=346) |
| n (%) | n (%) | n (%) | |
| Stroke–TIA | 172 (14.5) | 120 (14.40) | 52 (15.02) |
| Stroke–AIS | 795 (67.4) | 567 (68.06) | 228 (65.89) |
| Stroke–ICH | 121 (10.2) | 86 (10.32) | 35 (10.1) |
| Stroke–SAH | 12 (1.01) | 8 (0.96) | 4 (1.15) |
| UD | 79 (6.7) | 52(6.2) | 27(7.8) |
AIS, acute ischaemic stroke; ICH, intracerebral haemorrhage; SAH, subarachnoid haemorrhage; TIA, transient ischaemic stroke; UD, undifferentiated.
Acute ischaemic stroke (AIS) was seen in 907 patients (67.9%). Stroke due to intracerebral haemorrhage (ICH) was seen in 132 patients (9.9%). Stroke presenting as TIA was reported by 196 patients (14.7%) subjects. These patients presented with TIA but were proven to have stroke on further evaluation. We were unable to classify 89 patients (6.7%) patients for the type of stroke in this cohort.
We sub-classified patients with AIS (n=907) to report the subtype of AIS using TOAST classification.28 AIS due to large artery atherosclerosis was seen in 202 (22.3%), cardio-embolism in 64 (7.1%), small vessel occlusion in 268 (29.5%), other determined aetiology in 196 (21.6%) and undetermined aetiology in 177 (19.5%).
Among patients, 74 (5.5%) received thrombolytic therapy, 16 (1.2%) received endovascular therapy and 53 (4%) received neurosurgical interventions.
The mortality profile in general as well as the same stratified by type of stroke is presented as table 4.
Table 4.
Mortality profile—entire cohort and first ever stroke
| Full cohort | ||||||
| AIS (n=907) |
ICH (n=132) |
SAH (n=12) |
TIA (n=196) |
UD (n=89) |
Total (n=1336) |
|
| In-hospital | 27 (2.9%) | 15 (11.36%) | 0 (0%) | 0 (0%) | 3 (4.49%) | 45 (3.36%) |
| 2 weeks | 45 (4.96%) | 19 (14.39%) | 3 (25%) | 1 (0.51%) | 11 (11.35%) | 79 (5.91%) |
| 2 months | 54 (5.95%) | 19 (14.39%) | 3 (25%) | 1 (0.51%) | 11 (12.35%) | 88 (6.66%) |
| 6 months | 62 (6.8%) | 21 (15.90%) | 3 (25%) | 3 (1.53%) | 12 (13.48%) | 101 (7.63%) |
| 12 months | 71 (7.82%) | 23 (17.42%) | 3 (25%) | 3 (1.53%) | 14 (15.73%) | 114 (8.53%) |
| First ever stroke cohort | ||||||
| AIS (n=795) |
ICH (n=121) |
SAH (n=12) |
TIA (n=172) |
UD (n=79) |
Total (n=1179) |
|
| In-hospital | 23 (2.89%) | 15 (12.39%) | 0 (0%) | 0 (0%) | 1 (2.53%) | 39 (3.30%) |
| 2 weeks | 39 (4.90%) | 18 (14.87%) | 3 (25%) | 1 (0.58%) | 9 (10.12%) | 70 (5.85%) |
| 2 months | 48 (6.03%) | 18 (14.87%) | 3 (25%) | 1 (0.58%) | 9 (11.39%) | 79 (6.70%) |
| 6 months | 55 (6.91%) | 19 (15.70%) | 3 (25%) | 3 (1.74%) | 10 (12.65%) | 90 (7.63%) |
| 12 months | 64 (8.05%) | 21 (17.35%) | 3 (25%) | 3 (1.74%) | 12 (15.18%) | 103 (8.73%) |
The time points mentioned are after discharge for the first admission.
AIS, acute ischaemic stroke; ICH, Intracerebral haemorrhage; SAH, subarachnoid haemorrhage; TIA, transient ischaemic stroke; UD, undifferentiated.
A total of 114 patients (8.5%) in the full cohort expired after hospital admission for the index stroke till the end of 1-year follow-up. A total of 45 (3.4%) patients from the full cohort died during the first admission. The mortality figures for 2 weeks, 2 months, 6 months and 12 months after discharge were 79 (5.9%), 88 (6.7%), 101 (7.6%) and 114 (8.5%), respectively, in the full cohort. Similar figures were reported for the first ever cohort (table 4).
We calculated the stroke mortality rate per 1000 follow-up years for the two cohorts. The overall mortality rate at the end of 1 year follow-up after discharge for the full cohort was 91.8 per 1000 person years (95% CI 76.3 to 109.2). The corresponding figures for male and female patients were 84.5 (95% CI 67.0 to 104.7) and 110.2 (95% CI 79.5 to 147.5), respectively (online supplemental appendix table 3). The stroke type stratified figures for mortality rate in the full cohort showed the highest mortality rate for SAH (333.3 per 1000 person years, 95% CI 74.9 to 700.7) followed by ICH (203.5, 95% CI 133.6 to 289.6) and AIS (83.5, 95% CI 65.8 to 104.2). Similar figures were reported for the first ever cohort (online supplemental appendix table 3).
The final adjusted model for mortality at 1-year follow-up after an episode of stroke is presented as table 5.
Table 5.
Prediction model for stroke mortality at 1-year follow-up from baseline variables—full cohort and first ever stroke cohort
| B | SE | Wald | Sig. | Exp(B) | 95.0% CI for exp(B) | ||
| Lower | Upper | ||||||
| A.stroke mortality prediction model—full cohort | |||||||
| Age <45 years | Ref. | ||||||
| Age >45 years | 1.246 | 0.511 | 5.950 | 0.015 | 3.48 | 1.28 | 9.46 |
| NIHSS preTx_R (<4) | REF | ||||||
| NIHSS preTx_R (4–10) | 1.295 | 0.410 | 9.971 | 0.002 | 3.65 | 1.64 | 8.16 |
| NIHSS preTx_R (>10) | 2.698 | 0.387 | 48.634 | <0.001 | 14.85 | 6.96 | 31.69 |
| B.Stroke mortality prediction model—first ever stroke cohort | |||||||
| Age <45 years | REF | ||||||
| Age >45 Years | 1.144 | 0.512 | 4.997 | 0.025 | 3.14 | 1.15 | 8.55 |
| NIHSS_preTx_R (<4) | REF | ||||||
| NIHSS_preTx_R (4–10) | 1.024 | 0.431 | 5.632 | 0.018 | 2.78 | 1.20 | 6.48 |
| NIHSS_preTx_R (>10) | 2.412 | 0.411 | 34.508 | <0.001 | 11.16 | 4.99 | 24.96 |
| MRS_Admission (1–3) | REF | ||||||
| MRS_Admission (>3) | 0.922 | 0.460 | 4.015 | 0.045 | 2.51 | 1.02 | 6.19 |
Only two predictors—age and pre-treatment NIHSS score—showed significant associations with post stroke mortality in the full cohort. Patients older than 45 years at the time of the primary event (stroke) had a much higher mortality compared with patients younger than them (HR: 3.48, 95% CI 1.28 to 9.46, p=0.015). Similarly, those patients with pre-treatment NIHSS score in the range of 4–10 (HR: 3.65, 95% CI 1.64 to 8.16, p=0.002) as well as those with score >10 (HR: 14.85, 95% CI 6.96 to 31.69, p<0.001) had higher mortality compared with those with scores <4 (reference category).
The same analysis was repeated for the first ever stroke cohort. The analysis revealed three predictors for 1 year mortality after first ever stroke—age, pre-treatment NIHSS score and MRS score at baseline. Patients older than 45 years had a much higher mortality (HR: 3.14, 95% CI 1.15 to 8.55, p=0.025) compared with younger patients similar to that seen for the full cohort. Similarly, those patients with pre-treatment NIHSS score in the range of 4–10 (HR: 2.78, 95% CI 1.20 to 6.48, p=0.018) as well as those with score >10 (HR: 11.16, 95% CI 4.99 to 24.96, p<0.001) had higher mortality compared with those with scores <4 (reference category). In addition, those patients with MRS score more than 3 at baseline (HR: 2.51, 95% CI 1.02 to 6.19, p=0.0145) had higher mortality compared with those with scores <3 (reference category).
Discussion
The current registry provides detailed information related to prevalence of risk factors, comorbidities, profile of symptoms at presentation, mortality rates as well as predictors of mortality related to stroke from Kerala, India. A total of 114 patients from the full cohort expired during the follow-up period providing us with a 1-year stroke mortality of 8.5%. The stroke mortality rate per 1000 person years for the full cohort was 91.8. The adjusted analysis revealed three predictors for 1-year mortality after first ever stroke—age, pre-treatment NIHSS score and MRS score at baseline. The same for the full cohort had only two predictors—age and pre-treatment NIHSS score. Risk factors like diabetes, hypertension and dyslipidaemia failed to show any significant association with 1-year mortality after stroke.
Non-communicable neurological disorders are showing a rising trend in India.8 The contribution of non-communicable neurological disorders to total DALYs in the country doubled from 4·0% in 1990 to 8.2% in 2019.8 The GBD study reported a national level incidence of 93 per 100 000 population for stroke and Kerala topped the metric at 152 per 100 000 population.8
The Shiga cohort from Japan suggests that our study population gets stroke at least a decade earlier than the Japanese cohort.13 The current study reported younger mean ages for any stroke (61.3 vs 72.9), AIS (61.6 vs 74.7), ICH (60.0 vs 71.0) and SAH (53.2 vs 64.6) in comparison to the Japanese cohort.13
The current study identified three predictors for 1-year mortality in first ever stroke which were age, pre-treatment NIHSS score and MRS score at baseline. The same for any stroke were age and pre-treatment NIHSS score. Patients older than 45 years appear to have thrice the risk for 1-year mortality after stroke compared with their younger counterparts. Similar findings of increased risk of post stroke mortality with increasing age were reported by several studies published earlier.13 18 19 29The Anglia study demonstrated an age related increase in stroke mortality with the lowest mortality shown by 18–64 years (11.7%), followed by 65–75 years (20%), 76–81 years (27.1%) and 82–86 years (41.4%). The maximum mortality was seen in the age group of 86–100 years (54.8%). Chen et al reported that the HR for 1-year mortality after ischaemic stroke was 3.35 for patients older than 65 years compared with those below 45 years.29 All these studies confirm that age is strongly associated with post stroke mortality.
The association of NIHSS score at admission and 1-year mortality seen in the current study appears to be very strong. Compared with those with NIHSS score <4 at baseline, those with score 4–10 (HR: 3.65, 95% CI 1.64 to 8.16) and >10 (HR: 14.85, 95% CI 6.96 to 31.69) had much higher mortality at 1 year for the any stroke cohort. This is similar to that reported by the Mashhad stroke incidence study from Iran (HR: 1.14, 95% CI 1.10 to 1.17).19
Our study demonstrated a significant association between baseline mRS and 1-year mortality in the first ever cohort. Patients with baseline mRS score >3 had more than double the risk of mortality at 1-year follow-up compared with those with mRS ≤3 (HR: 2.51, 95% CI 1.02 to 6.19). A similar association between early mRS score (day 7) and later mortality was demonstrated by Hallevi et al.30 The 90-day mortality in patients with ischaemic stroke increased from 2.5% (mRS 3 group) to 7.2% (mRS 4 group) and to 31% (mRS 5 group).30
Our study did not find any significant association between diabetes and 1-year mortality after stroke. Similar findings were reported by the Taiwan cohort separately for cerebral haemorrhage (HR: 0.99, 95% CI 0.84 to 1.18) and cerebral infarction (HR: 1.06, 95% CI 0.97 to 1.17).29 On the contrary, the Shiga cohort reported a positive association between 2-year mortality and diabetes among patients with stroke (HR: 1.40, 95% CI 1.17 to 1.68).13 The current study failed to demonstrate any significant association between hypertension or dyslipidaemia with 1-year mortality after stroke. Similar findings were reported for 2-year mortality after stroke by the Shiga cohort.13
The in-hospital death for stroke reported in the current study is 3.4% for entire cohort and 2.9% for AIS. This is comparable to the recently published data by Gattringer et al and lower than that reported by Heuschmann et al.31 32 Gattringer et al reported an in-hospital mortality of 2% for 77 653 patients with AIS treated in the Austrian stroke unit registry. The German stroke registers cohort reported a 4.9% in-hospital mortality from 13 440 patients admitted with a diagnosis of AIS.32 These three studies are in contrast to the very high in-hospital mortality for AIS reported from Nepal (21%) by Shah et al in 2017.33
The study suggests that threefourths of the deaths due to stroke during 1-year follow-up happen during the first 2 months after discharge in the study population. The mortality rate for AIS at 2 months follow-up in the current study (6%) is comparable to a large cohort of 7144 patients with AIS published recently by Abadi et al.34 They reported a 1-month mortality rate of 8% for AIS from the USA.34
The current study reported the lowest 1-year mortality after stroke compared with the studies mentioned earlier except Deleu et al.9–20 Deleu et al reported a 1-year mortality of 2.1% for a stroke cohort (AIS and TIA) from Arabian peninsula.20 This cohort was much younger than the current study population (mean age 58.9 vs 61.3 years).
The 1 year mortality for first ever stroke is significantly lower in the current study compared with the Shiga cohort for any stroke (8.7% vs 24.6%), AIS (8.1% vs 19.1%), ICH (17.4 vs 29.2%) and SAH (25% vs 40.8%).13 The gradient in stroke mortality across the globe is well demonstrated by the more than triple mortality seen for stroke in a recent study from Chile in comparison to the current study at 6 months (30% vs 7.6%) and 1 year (32.7% vs 8.7%) after a first ever stroke.15
The very low rates for in-hospital mortality, case fatality rate at 1 month and mortality at 1 year seen in the current study could be due to several reasons. The probable reasons could be region specific as well as those related to the study centre. One major reason could be the excellent healthcare indices for the state of Kerala. The state has the lowest infant mortality, lowest under five mortality, lowest maternal mortality and highest life expectancy in India.35
Another major reason could be the steady decline in mortality following stroke seen on a global basis as suggested by a recent systematic review.6 A third probable reason could be the stroke care facilities available at the study centre. The current institution is a tertiary comprehensive care centre with a comprehensive stroke unit led by a stroke care specialist. The centre receives patients from all districts in the state. A multidisciplinary team, including specialists from stroke medicine, neuroradiology, stroke neurosurgery and neurophysiotherapy, is available for managing patients with stroke. A dedicated stroke unit based care can prevent complications and reduce mortality in patients with stroke as suggested by earlier studies.36 37
A fourth reason could be due to the design of the current study. Hospital-based stroke registries are likely to report relatively less proportion of stroke mortality compared with community based registries. This is due to the fact that a subset of patients with severe stroke may expire before reaching a stroke treatment facility and will never be captured in such registries. Another probable reason could be the fact that the cohort has a higher proportion of less severe stroke as suggested by the low pre-treatment NIHSS score in a larger subset (<4 in in 43.5%) and lower proportion of hemiplegia (16%) during index admission. The higher proportion of less severe stroke on admission seen in the current study could probably be due to early referral from peripheral centres as well as increased awareness in the community about the need for immediate treatment in patients with acute stroke.
The current study findings confirm the fact that good mortality outcomes are possible after acute stroke even in low resource settings like India when care is delivered through a well-equipped comprehensive stroke care unit.
Conclusions
Mortality of stroke at 1-year follow-up in the study population is low in comparison to several studies from different parts of the world. The predictors of 1-year mortality included age, NIHSS score at baseline and mRS score at baseline. This study demonstrates that a comprehensive stroke centre based care for acute stroke can significantly reduce the post stroke mortality in low resource countries like India. Establishment of affordable multidisciplinary stroke care centres should be promoted to improve stroke care quality and to reduce stroke mortality in low resource countries.
Supplementary Material
Acknowledgments
The authors thank Dr Drisya Rajan, Dr Karthika Rani and Mr Libin Antony for data collection and patient care.
Footnotes
Twitter: @doc_manu
Contributors: VN, MR and RS conceived the idea. RS and VN are the guarantors of the study. VN, RS, DV and MR supervised the collection of the data and drafted the manuscript. RS and MR participated in data collection. RS, MR and RB carried out data management and analysed the data. VN, RS, DV, MR and RB read the drafts and provided feedback. All authors read and approved the final manuscript.
Funding: All the study expenses were covered by the study institution via internal funding.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This study involves human participants and was approved by ethics committee of Amrita School of Medicine (EC/NEW/INST/2020/1254). The study information was collected from a prospective hospital registry and not directly from patients. The institutional ethics committee has approved a waiver of informed consent for this study due to the nature of data collection.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2022-061258supp001.pdf (95KB, pdf)
Data Availability Statement
Data are available upon reasonable request.