Study Of Models And Associated Factors Of Mortality And Functional Outcome After Stroke

Case-mix stroke model for mortality prediction is one of the tools to monitor the difference of stroke care among the stroke centers.Mortality predicted by the model is compared with the actual mortality to assess the quality of the stroke centers.However,the existing case-mix models are limited,produced by databases of foreign population,and are too complex,not easy to acquired by searching the patients’ medical chart,and are also lack of enough external validation.Benjamin D.Bray et al developed and validated a model to predict the risk of death for patients with acute stroke within 30 days after admission.This model was derived from the Sentinel Stroke National Audit Program in England and Wales.The C statistics of model A and B are 0.87 and 0.86,respectively.The aim of our study was to evaluate the accuracy of both model A and model B using data from the China National Stroke Registry-1（CNSR-1）.Obesity is a modifiable risk factor for stroke.Stroke mobidity increases with the elevation of Body mass index（BMI）.But numerous studies have shown an inverse relationship between obesity（or being overweight）and post-stroke mortality.This phenomenon was called the “stroke obesity paradox”,the reason of which is still controversial.The proxy of most the studies previously conducted was BMI.It is an index of general obesity,not taking into account the distribution of body fat.However,people with regional accumulation of fat in abdominal area were more likely to have a worse metabolic profile than the general obese people.And studies showed abdominal obesity is correlated with the incidence of stroke,especially ischemic stroke.Therefore,it is necessary for us to further explore the relationship of the extent of abdominal fat accumulation and the mortality after ischemic stroke to see if the paradox still existed in this circumstance.Recent studies have found that the waist-to-height ratio（WHR）is a simple and applicable index of abdominal obesity.Our study aimed to investigate the prognostic value of the WHR on one-year mortality and functional outcomes after ischemic stroke using the data in the acute stroke across China trial（ACROSS-China）.Part one External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in ChinaObjective: Predicting 30-day stroke mortality rates of stroke patients plays an important role in evaluating the prognosis of stroke patients.Most previously published models have limited utility in clinical practice,as a result of being validated either in ischemic stroke only or in hemorrhagic stroke only,rather than in both.Although some models have been validated to accurately predict the mortality after ischemic stroke in Asian populations,they were not generalizable to both ischemic stroke and hemorrhagic stroke.As a result,these models cannot be used to compare the quality of care among different stroke treatment centers.Case-mix adjustment models have been developed to meet the need of reporting case mix adjusted mortality outcomes for stroke treatment services.However,most of these models included multiple variables,including the Oxfordshire community stroke project（OCSP）classification,plasma glucose levels,or those difficult to obtain,such as the GCS verbal score.These limitations may explain why none of these case-mix adjustment models have been incorporated into routine clinical practice.Recently,Benjamin D.Bray et al developed and validated a model to predict the risk of death for patients with acute stroke within 30 days after admission.This model was derived from a large,prospective national registry of unselected cases of acute stroke in hospitals in England and Wales.The model was relatively simple and easy to implement.Two final models were eventually developed.Model A included age（<60,60±69,70±79,80±89,and ₉0 years）,presence of atrial fibrillation on admission,National Institutes of Health Stroke Severity Scale（NIHSS）score on admission,and stroke type（ischemic versus primary intracerebral hemorrhage）.Model B was similar to Model A,but included only the consciousness component of the NIHSS score（NIHSS₁A）instead of all of the components comprising the NIHSS score.However,there were few data on whether the model was suitable to use for Asian patients with acute stroke.Research has consistently shown that the incidence of stroke hasbeen surging dramatically in low-to middle income countries.The average onset age for first stroke among individuals in China is approximately 10 years younger than among individuals in Western countries,and individuals in China have a higher percentage of hemorrhagic stroke.Therefore,heterogeneity exists among stroke patients in Asian and Western countries.The aim of our study was to evaluate the accuracy of both model A and model B using data from the China National Stroke Registry-1（CNSR-1）.Methods: 1 External validation cohort information: The CNSR-1 is a prospective,nationwide hospital-based stroke registry created between September 2007 and August 2008.Eligible patients were enrolled if they were₁8 years old and had ischemic stroke,transient ischemic attack,intracerebral hemorrhage,or subarachnoid hemorrhage within 14 days of the index event from 132 hospitals across China.The stroke events were confirmed by brain CT or MRI within 14 days after the onset of symptoms.The design,rationale and baseline characteristics of the CNSR-1 have been reported elsewhere.The registry was approved by the central Institutional Review Board at Beijing Tiantan Hospital.Informed written consent was obtained from all patients or their designated relatives.Authors had no access to identifying participant information during or after data collection.Our present study included only patients with acute ischemic stroke or primary intracerebral hemorrhagic stroke.2 Risk factors definition: The baseline severity of neurological impairment was evaluated by the National Institute of Health Stroke Scale（NIHSS）within 24 h after admission.These data were collected via an interview conducted by trained research coordinators.Other data,including patient demographics（e.g.,gender,age）and vascular risk factors,were extracted from the medical records.Baseline vascular risk factors included history of hypertension（history of hypertension or antihypertensive drug use）,stroke or TIA（defined as being confirmed in a medical chart）,dyslipidemia（history of dyslipidemia or lipid-lowering drug use）,diabetes mellitus（history of diabetes mellitus or hypoglycemic drug use）,atrial fibrillation（history of atrial fibrillation confirmed by at least one electrocardiogram or presence of this type of arrhythmia during hospitalization）and history of coronary heart disease,current or previous smoking,etc.3 Outcome measures: The main outcome of interest was all-cause mortality rate within 30 days after admission,which was confirmed via telephone by trained research personnel at Beijing Tiantan Hospital.4 Statistical analyses Age and NIHSS scores were reported as medians（interquartile range）;all the other values were percentages.Significance testing of age and NIHSS was performed via t-test for continuous variables and the others were by χ 2 test for categorical variables.Discrimination of the case-mix adjustment model in our study was assessed by receiver operating curve analysis and estimation of the area under the receiver operator curve（c-statistic）and by calibration by plot of observed versus predicted mortality with 10 deciles of predicted risk.The case-mix adjustment model on which our analysis was based has been published elsewhere.The final two models（Model A and Model B）produced from Bray were both used directly and validated in our study.Comparison between the observed and predicted mortality was assessed by Pearson’s correlation coefficient.Given the large sample size used in our study,we did not use Hosmer and Lemeshow goodness-of-fit test,which is known to be sensitive to sample size,to assess calibration.All analyses above were conducted using SAS（version 9.4;SAS Institute,Cary,NC）.Results: Among the 22,216 patients enrolled in the CNSR-1,there were 12,415 patients with ischemic stroke and 3,255 patients with primary intracerebral hemorrhagic stroke who consented to participate in follow-up.After excluding 1,722 patients without NIHSS₁A information,a total of 13,948 patients with complete 30-day mortality information were included in our study.Comparing the demographics of CNSR-1 patients with stroke with those in the Sentinel Stroke National Audit Program,CNSR-1 patients were younger（median,67 versus 77 years of age）,more likely to be women（68.0% versus 50.2%）,were more likely to have had hemorrhagic stroke（20.7% versus 10.5%）,and had a lower mortality rate at 30 days（10.9%versus 13.2%）.There were no clinically significant differences in baseline characteristics between patients included and those excluded;however,there was a slightly higher proportion of history of stroke or TIA and dyslipidemia among the patients included.Based on the case-mix adjustment model A with full NIHSS score,the c-statistic of our external validation cohort was 0.80（95% confidence interval,0.79±0.82）.For the case-mix adjustment model B,which included only the NIHSS₁A rather than the full NIHSS,the c-statistic of our external validation cohort was 0.82（95% confidence interval,0.81±0.84）.Excellent calibration was reported in the plot of observed versus predicted mortality rates in model A（Pearson correlation coefficient 0.892;P = 0.0005）and model B（Pearson correlation coefficient 0.927;P = 0.008）.Conclusions: In our study,the results showed that the case-mix adjustment model could be used to accurately predict 30-day mortality in Chinese patients with acute stroke.Part two Association of high waist-to-height ratio with mortality outcomes in patients with acute ischemic stroke-Objective: Obesity is a major public health issue and is a modifiable risk factor for stroke.But numerous studies have shown an inverse relationship between obesity（or being overweight）and post-stroke mortality.This phenomenon was called the “stroke obesity paradox”,the reason of which is still controversial.The proxy of most the studies previously conducted was body mass index（BMI）.It is an index of general obesity,not taking into account the distribution of body fat.However,people with regional accumulation of fat in abdominal area were more likely to have a worse metabolic profile than the general obese people.And studies showed abdominal obesity is correlated with the incidence of stroke,especially ischemic stroke.In the Kailuan study,which was a prospective population-based cohort study in the Kailuan community in China,we observed that every measurement of adiposity was only associated with the risk for total stroke and ischemic stroke,but not for hemorrhagic stroke.This is possibly explained by associations between obesity measures and ischemic stroke incidence were largely explained by mediators related to obesity,for example,diabetes mellitus and dyslipidemia.Therefore,it is necessary for us to further explore the relationship of the extent of abdominal fat accumulation and the mortality after ischemic stroke to see if the paradox still existed in this circumstance.Recent studies have found that the waist-to-height ratio（WHR）is a simple and applicable index of abdominal obesity.And it displayed some advantages over other indexes such as waist circumference and the waist-tohip ratio（WHp R）.The acute stroke across China trial（ACROSS-China）was a nationwide multicenter prospective stroke registry conducted between 2007-2008.Our study aimed to investigate the prognostic value of the WHR on one-year mortality outcome after ischemic stroke using the patients in this registry.Methods: 1 Study population The study patients in the study were from the ACROSS-China trial.The ACROSS-China was a nationwide,prospective,multicenter cohort study to determine the prevalence of glucose metabolism abnormality in patients with first ever stroke.The inclusion and exclusion criteria for ACROSS-China have been published elsewhere.Patients were excluded if they had the following conditions: intracerebral or subarachnoid hemorrhage;lack of baseline waist circumference or body height information;lack of one-year follow-up modified Rankin scale（m RS）score information.Approval was obtained from the ethics committee of all participating centers,and all patients or their designated family members gave written informed consent.2 Data collection All of the baseline data were obtained within 24 hours after admission.Demographics such as age,gender and traditional vascular risk factors,including history of atrial fibrillation,coronary heart disease,heart failure,hypertension,hyperlipidemia,and diabetes mellitus as well as current smoking and moderate and heavy drinking,were recorded.“Current smoking”was defined as an individual who smoked at the time of stroke.“Moderate and heavy drinking” means ≥2 standard alcoholic beverages consumed per day.Other variables included in our study were as follows: systolic blood pressure（SBP）,diastolic blood pressure（DBP）,fasting blood glucose and Hb A1 C level,serum triglycerides,total cholesterol,low-density lipoprotein cholesterol,high-density lipoprotein cholesterol,and creatinine.The severity of neurological impairment was evaluated at admission using the National Institutes of Health Stroke Scale（NIHSS）.After the index event,secondary prevention treatments were administered,including antiplatelet,anticoagulant,antihypertensive,and lipid-lowering therapies.So in-hospital oral hypoglycemic and insulin drugs,anti-thrombotic drugs,anti-hypertension drugs,and lipid-lowering drugs were recorded.Twelve months after admission,follow-up interviews were conducted via telephone by trained research personnel at Beijing Tiantan Hospital using a standardized script.The caregiver was contacted and interviewed when the information provided by the patient was insufficient. All participants were shoeless when their body heights were measured,and waist circumference was measured at the level of the umbilicus.Both were measured to the nearest 0.1 cm and were assessed by trained medical staff.The WHR was calculated as waist circumference divided by body height.3 Outcome measures The acute ischemic stroke patients were classified according to the Trial of Org 10172 Acute Stroke Treatment system and were assessed 365±7 days after stroke onset to obtain the functional outcomes.Modified Rankin Scale（m RS）scores obtained via telephone were used to determine the functional outcomes of the patients,and these scores were graded from 0 to 6.Patients who died were given a m RS score of 6,while the m RS scores of surviving patients ranged from 0 to 5.4 Statistical methods We used SAS software,version 9.4（SAS Institute,Inc.,Cary,NC,USA）for analysis.Chi square,T-tests or rank sum tests were used to determine differences in clinical characteristics among patients with survival outcomes and mortality outcomes.We identified predictors for mortality outcomes using Cox proportional hazards model analysis which incorporated covariates with p value of <0.2 in the univariate analysis and those of clinical importance.The WHR was classified into quartiles and included in the Cox proportional hazards model for further investigation.In addition,sex-and age-based subgroup studies were conducted.Two-sided P values were reported for all analyses.Values of P<0.05 were considered statistically significant.Result: The ACROSS-China study included 3450 Chinese patients between 2008 and 2009.According to our inclusion and exclusion criteria,we excluded 811 participants who had hemorrhagic strokes,472 participants who were lost at the one-year follow-up,11 participants who lacked one-year follow-up m RS scores,and 80 participants without baseline waist circumference or body height information.A total of 2076 patients were included in the study.The baseline characteristics of the participants without one-year follow-up and those included in our study were similar,except a higher proportion of diabetes mellitus in the past history among the participants included in our study.Among the patients who had survived to the one-year follow-up,the mean age was 61.8 years old,and 63.8% were male.Among the patients who had died before the one-year follow-up,the mean age was 70.0 years old,and 58.9% were male.The patients with mortality outcomes were more likely than the patients with survival outcomes to have the following characteristics: older,higher NIHSS score,less moderate and heavy drinking as well as history of atrial fibrillation,coronary heart disease,heart failure,diabetes mellitus,as well as more oral hypoglycemic,insulin and diuretics usage,less antithrombotic agent usage.After multivariate adjustment,only older age,history of diabetes mellitus,higher systolic and diastolic blood pressure,in-hospital diuretics usage,and higher NIHSS score at admission was associated with mortality outcomes.The WHR was not found to be correlated with mortality outcomes（second quartile,HR=0.69,CI: 0.46-1.04;third quartile,HR=0.79,CI: 0.53-1.18;fourth quartile,HR=0.85,CI: 0.58-1.25）.In the subgroup analysis of different sex-and age-based groups,the WHR remained a non-significant predictor of mortality outcomes.Conclusions: Our study indicated that abdominal fat accumulation may be not associated with mortality after stroke.We did not observe the “obesity parodox” in our analysis.Providing instructions to help patients manage not only their traditional risk factors but also their WHR is of clinical value.Unlike age or disease severity at admission,the WHR is a controllable prognostic factor and should not be neglected by physicians.Part three Association of high waist-to-height ratio with functional outcomes in patients with acute ischemic strokeObjective: Obesity is a major public health issue and is a modifiable risk factor for stroke.But numerous studies have shown an inverse relationship between obesity（or being overweight）and post-stroke mortality.This phenomenon was called the “stroke obesity paradox”,the reason of which is still controversial.The proxy of most the studies previously conducted was body mass index（BMI）.It is an index of general obesity,not taking into account the distribution of body fat.However,people with regional accumulation of fat in abdominal area were more likely to have a worse metabolic profile than the general obese people.And studies showed abdominal obesity is correlated with the incidence of stroke,especially ischemic stroke.In the Kailuan study,which was a prospective population-based cohort study in the Kailuan community in China,we observed that every measurement of adiposity was only associated with the risk for total stroke and ischemic stroke,but not for hemorrhagic stroke.This is possibly explained by associations between obesity measures and ischemic stroke incidence were largely explained by mediators related to obesity,for example,diabetes mellitus and dyslipidemia.Therefore,it is necessary for us to further explore the relationship of the extent of abdominal fat accumulation and the mortality after ischemic stroke to see if the paradox still existed in this circumstance.Recent studies have found that the waist-to-height ratio（WHR）is a simple and applicable index of abdominal obesity.And it displayed some advantages over other indexes such as waist circumference and the waist-tohip ratio（WHp R）.The acute stroke across China trial（ACROSS-China）was a nationwide multicenter prospective stroke registry conducted between 2007-2008.Our study aimed to investigate the prognostic value of the WHR on one-year functional outcome after ischemic stroke using the patients in this registry.Methods: 1 Study population The study patients in the study were from the ACROSS-China trial.The ACROSS-China was a nationwide,prospective,multicenter cohort study to determine the prevalence of glucose metabolism abnormality in patients with first ever stroke.The inclusion and exclusion criteria for ACROSS-China have been published elsewhere.Patients were excluded if they had the following conditions: intracerebral or subarachnoid hemorrhage;lack of baseline waist circumference or body height information;lack of one-year follow-up modified Rankin scale（m RS）score information.Approval was obtained from the ethics committee of all participating centers,and all patients or their designated family members gave written informed consent.2 Data collection All of the baseline data were obtained within 24 hours after admission.Demographics such as age,gender and traditional vascular risk factors,including history of atrial fibrillation,coronary heart disease,heart failure,hypertension,hyperlipidemia,and diabetes mellitus as well as current smoking and moderate and heavy drinking,were recorded.“Current smoking”was defined as an individual who smoked at the time of stroke.“Moderate and heavy drinking” means ≥2 standard alcoholic beverages consumed per day.Other variables included in our study were as follows: systolic blood pressure（SBP）,diastolic blood pressure（DBP）,fasting blood glucose and Hb A1 C level,serum triglycerides,total cholesterol,low-density lipoprotein cholesterol,high-density lipoprotein cholesterol,and creatinine.The severity of neurological impairment was evaluated at admission using the National Institutes of Health Stroke Scale（NIHSS）.After the index event,secondary prevention treatments were administered,including antiplatelet,anticoagulant,antihypertensive,and lipid-lowering therapies.So in-hospital oral hypoglycemic and insulin drugs,anti-thrombotic drugs,anti-hypertension drugs,and lipid-lowering drugs were recorded.Twelve months after admission,follow-up interviews were conducted via telephone by trained research personnel at Beijing Tiantan Hospital using a standardized script.The caregiver was contacted and interviewed when the information provided by the patient was insufficient. All participants were shoeless when their body heights were measured,and waist circumference was measured at the level of the umbilicus.Both were measured to the nearest 0.1 cm and were assessed by trained medical staff.The WHR was calculated as waist circumference divided by body height.3 Outcome measures The acute ischemic stroke patients were classified according to the Trial of Org 10172 Acute Stroke Treatment system and were assessed 365±7 days after stroke onset to obtain the functional outcomes.Modified Rankin Scale（m RS）scores obtained via telephone were used to determine the functional outcomes of the patients,and these scores were graded from 0 to 6.Patients who died were given a m RS score of 6,while the m RS scores of surviving patients ranged from 0 to 5.4 Statistical methods We used SAS software,version 9.4（SAS Institute,Inc.,Cary,NC,USA）for analysis.Chi square,T-tests or rank sum tests were used to determine differences in clinical characteristics among patients with different grades of functional outcomes,or with survival outcomes and death outcomes.We identified predictors for functional outcomes using logistic regression analysis which incorporated covariates with P value of <0.2 in the univariate analysis and those of clinical importance.The WHR was classified into quartiles and included in the logistic regression model for further investigation.In addition,sex-and age-based subgroup studies were conducted.Two-sided P values were reported for all analyses.Values of P<0.05 were considered statistically significant.Result: The ACROSS-China study included 3450 Chinese patients between 2008 and 2009.According to our inclusion and exclusion criteria,we excluded 811 participants who had hemorrhagic strokes,472 participants who were lost at the one-year follow-up,11 participants who lacked a one-year follow-up m RS score,and 80 participants without baseline waist circumference or body height information.A total of 2076 patients were included in the study.The baseline characteristics of the participants without one-year follow-up and those included in our study were similar,except a higher proportion of diabetes mellitus in the past history among the participants included in our study.Among the patients with higher grades of functional outcomes,it appeared that the mean age was older,and the percentage of male was lower,the percentages of history of atrial fibrillation,coronary heart disease and diabetes mellitus were higher.The patients with different functional outcomes were also different in the following characteristics: smoking status,NIHSS score,WHR and serum triglyceride level and high density lipoprotein level,as well as a history of heart failure as well as more in-hospital insulin usage,less anti-thrombotic and lipid-lowering agent usage.After multivariate adjustment,we found that,compared with the first WHR quartile,the fourth quartile was associated with higher grades of m RS scores（second quartile,OR=1.05,CI: 0.83-1.33;third quartile,OR=1.10,CI: 0.86-1.40;fourth quartile,OR=1.38,CI: 1.08-1.77）.The subgroup analysis revealed that in the male subgroup,compared with the first quartile,the fourth WHR quartile was significantly associated with higher grades of m RS scores（fourth quartile,OR=1.45,CI: 1.06-1.98,P=0.02）.However,this association was not observed in the female subgroup.We also did observe in the younger age（<65）subgroup,compared with the first quartile,the fourth WHR quartile was significantly associated with higher grades of m RS scores（fourth quartile,OR=1.44,CI: 1.00-2.07,P=0.05）.Conclusions: Our study showed that abdominal fat accumulation may be associated with functional recovery after stroke.Compare with the lowest quartile,the highest quartile of WHR at admission was possibly associated with worse post-acute ischemic stroke functional recovery.Providing instructions to help patients manage not only their traditional risk factors but also their WHR is of clinical value.Unlike age or disease severity at admission,the WHR is a controllable prognostic factor and should not be neglected by physicians.Our finding agrees to some extent with the public health slogan “Make your waist less than half of your height”.