Risk Factors for In-Hospital Mortality among Ischemic Stroke Patients in Southern Taiwan

Resistin and In-Hospital Mortality in Patients with Acute Ischemic Stroke: A Prospective Study

Background/Objectives: Understanding the prognostic factors of acute ischemic stroke (AIS) is essential for improving patient outcomes. The aim of this study was to establish the predictive role of plasmatic resistin and leptin on short-term mortality in adult patients with a first episode of AIS. Methods: This study enrolled 277 patients who were consecutively hospitalized for AIS. Demographic data, cardiovascular risk, comorbidities, and laboratory tests were collected. Death was noted if it occurred during hospitalization. Results: Death was recorded in 33 (11.9%) patients. Conducting multivariate analysis, the following variables were independent variables associated with in-hospital mortality: a resistin value of >11 ng/mL (OR 10.81 (95%CI 2.31;50.57), p = 0.002), a lesion volume of >18.8 mL (OR 4.87 (95%CI 1.87;12.67), p = 0.001), a NIHSS score of >7 (OR 5.88 (95%CI 2.01;17.16), p = 0.001), and the presence of IHD (OR 4.33 (95%CI 1.66;11.27), p = 0.003). This study has some limitations: single-center design (which may affect the generalizability of the results) and the potential impact of the COVID-19 pandemic on patient outcomes. Conclusions: This study demonstrated that resistin is a significant predictor of in-hospital mortality in AIS patients. Other established factors, such as a high NIHSS score, large lesion volume, and the presence of IHD, were reaffirmed as important predictors.

Prognostic model of in-hospital ischemic stroke mortality based on an electronic health record cohort in Indonesia

Stroke patients rarely have satisfactory survival, which worsens further if comorbidities develop in such patients. Limited data availability from Southeast Asian countries, especially Indonesia, has impeded the disentanglement of post-stroke mortality determinants. This study aimed to investigate predictors of in-hospital mortality in patients with ischemic stroke (IS). This retrospective observational study used IS medical records from the National Brain Centre Hospital, Jakarta, Indonesia. A theoretically driven Cox's regression and Fine-Gray models were established by controlling for age and sex to calculate the hazard ratio of each plausible risk factor for predicting in-hospital stroke mortality and addressing competing risks if they existed. This study finally included 3,278 patients with IS, 917 (28%) of whom had cardiovascular disease and 376 (11.5%) suffered renal disease. Bivariate exploratory analysis revealed lower blood levels of triglycerides, low density lipoprotein, and total cholesterol associated with in-hospital-stroke mortality. The average age of patients with post-stroke mortality was 64.06 ± 11.32 years, with a mean body mass index (BMI) of 23.77 kg/m2 and a median Glasgow Coma Scale (GCS) score of 12 and an IQR of 5. Cardiovascular disease was significantly associated with IS mortality risk. NIHSS score at admission (hazard ratio [HR] = 1.04; 95% confidence interval [CI]: 1.00-1.07), male sex (HR = 1.51[1.01-2.26] and uric acid level (HR = 1.02 [1.00-1.03]) predicted survivability. Comorbidities, such as cardiovascular disease (HR = 2.16 [1.37-3.40], pneumonia (HR = 2.43 [1.42-4.15] and sepsis (HR = 2.07 [1.09-3.94, had higher hazards for post-stroke mortality. Contrarily, the factors contributing to a lower hazard of mortality were BMI (HR = 0.94 [0.89-0.99]) and GCS (HReye = 0.66 [0.48-0.89]. In summary, our study reported that male sex, NIHSS, uric acid level, cardiovascular diseases, pneumonia, sepsis. BMI, and GCS on admission were strong determinants of in-hospital mortality in patients with IS.

Predictors of 30-day mortality following the first episode of stroke among patients admitted at referral hospitals in Dodoma, central Tanzania: A prospective longitudinal observational study

Background and Aims

Stroke is the leading cause of disability and the second most common cause of death after ischemic heart disease worldwide. Understanding predictors of early poststroke mortality provides opportunities for interventions and favorable outcomes. This study aimed to determine the incidence and predictors of 30-day mortality among patients admitted with the first stroke at referral hospitals in Dodoma.

Methods

A prospective longitudinal observational design enrolled patients with acute stroke confirmed by CT scan or MRI admitted at referral hospitals in Dodoma. The National Institute of Health Stroke Scale was used to assess stroke severity at baseline. A comparison of risk factors, clinical profiles, and mortality was done using the Chi-square test. A logistic regression model was used to determine the predictors of 30-day mortality in patients with the stroke while the 30-day probability of survival was estimated using Kaplan-Meier analysis.

Results

Out of 226 patients with first-ever stroke, 121(54%) were males, and the population mean age was 63(15) years. The 140(62%) had Ischemic stroke, and 154(68%) survived at the 30th day. Patients with a history of smoking 2.4 [95% confidence interval (CI) (1.0-5.6), p = 0.048], loss of consciousness 2.7 [95% CI (1.2-6.4; p = 0.019] and unequal pupil size 13.7 [95% CI (4.1-58.1, p < 0.001 were significantly more associated with mortality within 30 days. The median survival was 7 (3-9) days, whereas alcohol drinkers and those aged above 60 years had a shorter time to mortality compared to non-alcohol drinkers and those aged <60 years.

Conclusion

The study showed a high incidence of mortality within 30 days after the first stroke episode, with the highest proportion dying within 7 days of being hospitalized. Advanced age of ≥60 years, smoking, alcohol use, and severe stroke at admission warrant special attention.

The Effect of the Charlson Comorbidity Index On In-Hospital Complications, Hospital Length of Stay, Mortality, and Readmissions Among Patients Hospitalized for Acute Stroke

Aim A notable number of people who develop stroke have comorbid medical conditions. The aim of this study is to evaluate the use of the Charlson Comorbidity Index (CCI) to predict in-hospital complications, mortality, length of stay, and readmission rates in stroke patients. Method It is a retrospective study that analyzed patients who were admitted for stroke in a six-month time duration. Stroke was classified into ischemic, hemorrhagic, or undetermined; hospital complications were classified into medical or neurological. Data regarding comorbidities, complications, length of stay, mortality, and readmissions were documented. Comorbidities were then classified by the CCI and split into four categories: zero, mild (1-2), moderate (3-4) and severe (5+). The data was analyzed using SPSS (IBM, Inc., Armonk, US). Results Four hundred and seventy-three adults aged above 18 were hospitalized for acute stroke. There was no correlation between the severity of the CCI score and mortality. Patients with ischemic stroke had a higher CCI correlated with readmission rate (p=0.026) and hospital complications (p=0.054). The two groups with the highest intensive care unit admission rate were mild, followed by the severe group (p=0.001). Our study also revealed that the patients with severe CCI scores had an increased readmission rate (p=0.001). Conclusion There is a correlation between a high CCI score and readmission rate, as well as CCI score with hospital complications in ischemic stroke. Further prospective studies of a longer duration can be undertaken to find further associations with the potential for this score to be used as a predictor in patients hospitalized for stroke.

Temporal trend of comorbidity and increasing impacts on mortality, length of stay, and hospital costs of first stroke in Tianjin, North of China

BACKGROUND

Stroke patients have a high incidence of comorbidity. Previous studies have shown that comorbidity can impact on the short-term and long-term mortality after stroke.

METHODS

Our study aimed to explore the trend of comorbidity among patients with first stroke from 2010 to 2020, and the influence of comorbidity on admission mortality, length of stay and hospitalization costs. 5988 eligible patients were enrolled in our study, and divided into 4 comorbidity burden groups according to Charlson comorbidity index (CCI): none, moderate, severe, very severe. Survival analysis was expressed by Kaplan-Meier curve. Cox regression model was used to analyze the effect of comorbidity on 7-day and in-hospital mortality. Generalized linear model (GLM) was used to analyze the association between comorbidity and hospitalization days and cost.

RESULTS

Compared to patients without comorbidity, those with very severe comorbidity were more likely to be male (342, 57.7%), suffer from ischemic stroke (565, 95.3%), afford higher expense (Midian, 19339.3RMB, IQR13020.7-27485.9RMB), and have a higher in-hospital mortality (60, 10.1%). From 2010 to 2020, proportion of patients with severe and very severe comorbidity increased 12.9%. The heaviest comorbidity burden increased the risk of 7-day mortality (adjusted hazard ratio, 3.51, 95% CI 2.22-5.53) and in-hospital mortality (adjusted hazard ratio, 3.83, 95% CI 2.70-5.45). Patients with very severe comorbidity had a 12% longer LOS and extra 27% expense than those without comorbidity.

CONCLUSIONS

Comorbidity burden showed an increasing trend year in past eleven years. The heavy comorbidity burden increased in-hospital mortality, LOS, and hospitalization cost, especially in patients aged 55 years or more. The findings also provide some reference on improvement of health care reform policies and allocation of resources.

Magnitude of risk factors and in-hospital mortality of stroke in Ethiopia: a systematic review and meta-analysis

Background

The morbidity and mortality of stroke is disproportionately high in developing countries owing to the poor health care system and poor neurologic interventions. Though a number of studies were conducted to estimate the in-hospital mortality rate of stroke in Ethiopia, the lack of a nationwide study that determines the overall magnitude of risk factors and in-hospital mortality rate of stroke is an important research gap. Meta-analysis is key to improve the accuracy of estimates through the use of more data sets. Thus, this study was aimed to determine the overall magnitude of risk factors and in-hospital mortality rate of stroke in Ethiopia.

Methods

This study was conducted following the PRISMA checklist. We searched from Google Scholar, PubMed, Science Direct, Web of Science, CINAHL, and Cochrane Library databases for studies. Each of the original studies was assessed using a tool for the risk of bias adapted for cross-sectional studies. Data were pooled and a random effect meta-analysis model was fitted to provide the overall magnitude of risk factors and in-hospital mortality rate of stroke. Also, the subgroup analyses were performed to examine how the in-hospital mortality rate varies across different groups of studies.

Results

In this study, the overall magnitude of hypertension, diabetes mellitus, and atrial fibrillation among stroke patients were 47% (95%CI: 40–54), 8% (95CI%:6–12), and 10% (95%CI: 5–19), respectively. The overall in-hospital mortality of stroke in Ethiopia was 18% (95%:14–22). The highest magnitude of in-hospital mortality of stroke was observed in SNNPR and the lowest was noted in Tigray region. In addition, the magnitude of the in-hospital mortality rate of stroke was 15.1% (95%CI: 11.3–19.4), and 19.6%(95%CI: 14.1–25.7), among studies published before and after 2016, respectively.

Conclusions

Our pooled result showed that nearly one-fifth of stroke patients have died during hospitalization. The most common risk factor of stroke among the included studies was hypertension followed by atrial fibrillation and diabetes mellitus. There is a need for a better understanding of the factors associated with high blood pressure, especially in countries with a high risk of stroke.

Cost-effectiveness of statin therapy for secondary prevention among patients with coronary artery disease and baseline LDL-C 70-100 mg/dL in Taiwan

BACKGROUND

The recommended target low-density lipoprotein cholesterol (LDL-C) level for coronary artery disease (CAD) patients has been lowered from 100 to 70 mg/dL in several clinical guidelines for secondary prevention. We aimed to assess whether initiating statin treatment in CAD patients with baseline LDL-C 70-100 mg/dL in Taiwan could be cost-effective.

METHODS

A Markov model was developed to simulate a hypothetical cohort of CAD patients with a baseline LDL-C level of 90 mg/dL. The incidence and recurrence of MI and stroke related to specific LDL-C levels as well as the statin effect, mortality rate, and health state utilities were obtained from the literature. The direct medical costs and rate of fatal events were derived from the national claims database. The incremental cost-effectiveness ratio (ICER) per quality-adjusted life years (QALYs) was calculated, and sensitivity analyses were performed.

RESULTS

Moderate-intensity statin use, a treatment regimen expected to achieve LDL <70 mg/dL in the base case, resulted in a net gain of 562 QALYs but with an additional expenditure of $11.4 million per 10,000 patients over ten years. The ICER was $20,288 per QALY gained. The probabilities of being cost-effective at willingness-to-pay thresholds of one and three gross domestic product per capita ($24,329 in 2017) per QALY were 51.1% and 94.2%, respectively. Annual drug cost was the most influential factor on the ICER.

CONCLUSION

Lowering the target LDL-C level from 100 to 70 mg/dL among treatment-naïve CAD patients could be cost-effective given the health benefits of preventing cardiovascular events and deaths.

Effect of Comorbidity Assessed by the Charlson Comorbidity Index on the Length of Stay, Costs and Mortality among Older Adults Hospitalised for Acute Stroke

The burden of comorbidity among stroke patients is high. The aim of this study was to examine the effect of comorbidity on the length of stay (LOS), costs, and mortality among older adults hospitalised for acute stroke. Among 776 older adults (mean age 80.1 ± 8.3 years; 46.7% female) hospitalised for acute stroke during July 2013 to December 2015 at a tertiary hospital in Melbourne, Australia, we collected data on LOS, costs, and discharge outcomes. Comorbidity was assessed via the Charlson Comorbidity Index (CCI), where a CCI score of 0⁻1 was considered low and a CCI ≥ 2 was high. Negative binomial regression and quantile regression were applied to examine the association between CCI and LOS and cost, respectively. Survival was evaluated with the Kaplan⁻Meier and Cox regression analyses. The median LOS was 1.1 days longer for patients with high CCI than for those with low CCI. In-hospital mortality rate was 18.2% (22.1% for high CCI versus 11.8% for low CCI, p < 0.0001). After controlling for confounders, high CCI was associated with longer LOS (incidence rate ratio [IRR]; 1.35, p < 0.0001) and increased likelihood of in-hospital death (hazard ratio [HR]; 1.91, p = 0.003). The adjusted median, 25th, and 75th percentile costs were AUD$2483 (26.1%), AUD$1446 (28.1%), and AUD$3140 (27.9%) higher for patients with high CCI than for those with low CCI. Among older adults hospitalised for acute stroke, higher global comorbidity (CCI ≥ 2) was associated adverse clinical outcomes. Measures to better manage comorbidities should be considered as part of wider strategies towards mitigating the social and economic impacts of stroke.