Ischemic Stroke Mortality Is More Strongly Associated with Anemia on Admission Than with Underweight Status

The effect of body mass index on stroke prognosis: A systematic review and meta-analysis of 32 cohort studies with 330,353 patients

BACKGROUND

Many studies have explored the impact of body mass index (BMI) on stroke prognosis, yet findings remain inconsistent.

AIMS

The aims of this study were to conduct a systematic review and meta-analyses to summarize the existing evidence on BMI and stroke outcomes.

METHODS

PubMed, Web of Science, Embase, The Cochrane Library, CNKI, CBM, Wanfang Database, and VIP Database were systematically searched from inception to 1 January 2023. Cohort studies were included if they reported on a population of patients with stroke, evaluated BMI on stroke outcomes (mortality/recurrence/score of modified Rankin scale (mRs)), and reported original data. Data extraction and quality assessment were independently undertaken by two reviewers. Stata 16.0 software was used for meta-analysis.

RESULTS

Thirty-two studies involving 330,353 patients (5 Chinese language articles) were included in the analysis. The proportion of underweight, overweight, and obese patients was 1.85%, 18.2%, and 15.6%, respectively. Compared with normal weight, being underweight was associated with an increased risk of mortality (relative risk (RR) = 1.78, 95% confidence interval (CI) = 1.60-1.96), poor functional outcomes defined as modified Rankin scale ⩾ 3 (RR = 1.33, 95% CI = 1.22-1.45), and stroke recurrence (RR = 1.19, 95% CI = 1.04-1.37). Being overweight but not obese was associated with reduced mortality (RR = 0.81, 95% CI = 0.74-0.89) and better functional outcomes (RR = 0.92, 95% CI = 0.89-0.96), but did not alter the risk of stroke recurrence (RR = 1.03, 95% CI = 0.90-1.17). Obesity was associated with lower risk of mortality (RR = 0.76, 95% CI = 0.72-0.81) and better functional outcomes (RR = 0.89, 95% CI = 0.84-0.94).

CONCLUSIONS

Our findings indicate that in patients with stroke, being underweight is associated with an increased risk of mortality, poor functional outcomes, and stroke recurrence. In contrast, being overweight but not obese, or being obese, was associated with a decreased risk of mortality and better functional outcomes. This is consistent with the obesity paradox in stroke, whereby obesity increases stroke risk in the general population but is associated with improved outcome in patients suffering stroke.

Prevalence and Associated Factors of Anemia Among Hospital Admitted Patients in Eastern Ethiopia

Background

Anemia is one of the most common comorbidities frequently seen in admitted patients. However, there is a scarcity of evidence regarding anemia among hospital admitted patients in Ethiopia, particularly in the Harari Region. Therefore, this study aimed to assess the prevalence and associated factors of anemia among hospital admitted patients in Eastern Ethiopia.

Methods

A hospital-based cross-sectional study was conducted from October 25 to December 30, 2022. Four milliliters of venous blood were collected and complete blood count was done using the DxH 800 (Beckman Coulter, Inc, Miami, FL) hematology analyzer. The data were entered in Epi-data version 4 and exported to SPSS version 26 for statistical analysis. Bivariable and multivariable logistic regression models were fitted. The level of significance was declared at a p-value of < 0.05.

Results

Of the 381 hospital admitted patients, 64.8% (95% CI = 60.01, 69.65) of the participants were anemic. Admitted patients who drank standard alcohol daily (AOR = 3.78, 95% CI = 1.71, 8.30), underweight (AOR = 9.39, 95% CI = 2.90, 30.46), and undernourished patients (AOR = 2.59, 95% CI = 1.15, 5.84), patients admitted with chronic kidney disease (AOR = 11.16, 95% CI = 4.06, 30.64), chronic liver disease (AOR = 3.20, 95% CI = 1.21, 8.47), deep vein thrombosis (AOR = 6.22, 95% CI = 1.98, 19.52), infectious disease (AOR = 9.71, 95% CI = 2.77, 34.02), and chronic non-communicable disease (AOR = 7.01, 95% CI = 1.90, 25.99) were all significantly associated with anemia.

Conclusion

Anemia was common among hospital admitted patients and should prompt the focus on admission diagnoses that are likely to play leading roles in etiology. This information indicates a need for routine screening of anemia for all admitted patients to improve their health.

Predicting short and long-term mortality after acute ischemic stroke using EHR

OBJECTIVE

Despite improvements in treatment, stroke remains a leading cause of mortality and long-term disability. In this study, we leveraged administrative data to build predictive models of short- and long-term post-stroke all-cause-mortality.

METHODS

The study was conducted and reported according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guideline. We used patient-level data from electronic health records, three algorithms, and six prediction windows to develop models for post-stroke mortality.

RESULTS

We included 7144 patients from which 5347 had survived their ischemic stroke after two years. The proportion of mortality was between 8%(605/7144) within 1-month, to 25%(1797/7144) for the 2-years window. The three most common comorbidities were hypertension, dyslipidemia, and diabetes. The best Area Under the ROC curve(AUROC) was reached with the Random Forest model at 0.82 for the 1-month prediction window. The negative predictive value (NPV) was highest for the shorter prediction windows - 0.91 for the 1-month - and the best positive predictive value (PPV) was reached for the 6-months prediction window at 0.92. Age, hemoglobin levels, and body mass index were the top associated factors. Laboratory variables had higher importance when compared to past medical history and comorbidities. Hypercoagulation state, smoking, and end-stage renal disease were more strongly associated with long-term mortality.

CONCLUSION

All the selected algorithms could be trained to predict the short and long-term mortality after stroke. The factors associated with mortality differed depending on the prediction window. Our classifier highlighted the importance of controlling risk factors, as indicated by laboratory measures.

Predictors of Stroke Outcome Extracted from Multivariate Linear Discriminant Analysis or Neural Network Analysis

Aim: The prediction of functional outcome is essential in the management of acute ischemic stroke patients. We aimed to explore the various prognostic factors with multivariate linear discriminant analysis or neural network analysis and evaluate the associations between candidate factors, baseline characteristics, and outcome.

Methods: Acute ischemic stroke patients ( n =1,916) with premorbid modified Rankin Scale (mRS) scores of 0–2 were analyzed. The prediction models with multivariate linear discriminant analysis (quantification theory type II) and neural network analysis (log-linearized Gaussian mixture network) were used to predict poor functional outcome (mRS 3–6 at 3 months) with various prognostic factors added to age, sex, and initial neurological severity at admission.

Results: Both models revealed that several nutritional statuses and serum alkaline phosphatase (ALP) levels at admission improved the predictive ability. Of the 1,484 patients without missing data, 560 patients (37.7%) had poor outcomes. The patients with poor outcomes had higher ALP levels than those without (294.3±259.5 vs. 246.3±92.5 U/l, P ＜0.001). Multivariable logistic analyses revealed that higher ALP levels (1-SD increase) were independently associated with poor stroke outcomes after adjusting for several confounding factors, including the neurological severity, malnutrition status, and inflammation (odds ratio 1.21, 95% confidence interval 1.02–1.49). Several nutritional indicators extracted from prediction models were also associated with poor outcome.

Conclusion: Both the multivariate linear discriminant and neural network analyses identified the same indicators, such as nutritional status and serum ALP levels. These indicators were independently associated with functional stroke outcome.

Prognostic Nutritional Index for Predicting 3-Month Outcomes in Ischemic Stroke Patients Undergoing Thrombolysis

Objective: Malnutrition has been reported to be related to adverse prognosis in acute ischemic stroke (AIS) patients. Unfortunately, traditional nutritional assessment tools usually increase the workload of neurologists, which makes them unfeasible in the daily clinic work. We aimed to elucidate the association between the prognostic nutritional index (PNI), an easily obtainable baseline nutritional marker, and 3-month outcomes in AIS patients receiving intravenous thrombolysis (IVT).

Research methods and procedures: The present study retrospectively included 405 patients. PNI was calculated as 5^*lymphocyte count (10⁹ /L) + serum albumin concentration (g/L), and the good prognosis was defined as modified Rankin Scale score of 0–3. The relationship between PNI and clinical parameters was evaluated. The multiple logistic regression model was performed to find out independent predictors of the 3-month outcomes.

Results: We found that the patients in the low PNI group had a higher frequency of anemia (12.9 vs. 2.3%, P < 0.001) and a higher level of the Controlling nutritional status (CONUT) score (P < 0.001). The relationship between PNI and nutrition-related factors, such as body mass index (r = 0.208, P = 0.001), age (r = −0.329, P < 0.001), total cholesterol (r = 0.268, P < 0.001) and hemoglobin concentration (r = 0.328, P < 0.001), was significant. Low PNI value (adjusted odds ratio: 2.250, confidence interval: 1.192–4.249, p = 0.012) stayed as an independent predictor for the poor outcome at three months, after adjustment for potential confounders.

Conclusions: The PNI was independently associated with 3-month outcomes in AIS patients undergoing IVT. As an easily obtainable nutritional marker, PNI may be a useful nutritional assessment tool in the clinic work.

Trajectories of Haemoglobin and incident stroke risk: a longitudinal cohort study

Background

Studies have demonstrated that high or low haemoglobin increases the risk of stroke. Previous studies, however, performed only a limited number of haemoglobin measurements, while there are dynamic haemoglobin changes over the course of a lifetime. This longitudinal cohort study aimed to classify the long-term trajectory of haemoglobin and examine its association with stroke incidence.

Methods

The cohort consisted of 11,431 participants (6549 men) aged 20 to 50 years whose haemoglobin was repeatedly measured 3–9 times during 2004–2015. A latent class growth mixture model (LCGMM) was used to classify the long-term trajectory of haemoglobin concentrations, and hazard ratios (HRs) and 95% confidence intervals (95% CI) according to the Cox proportional hazard model were used to investigate the association of haemoglobin trajectory types with the risk of stroke.

Results

Three distinct trajectory types, high-stable (n = 5395), normal-stable (n = 5310), and decreasing (n = 726), were identified, with stroke incidence rates of 2.7, 1.9 and 3.2 per 1000 person-years, respectively. Compared to the normal-stable group, after adjusting for the baseline covariates, the decreasing group had a 2.94-fold (95% CI 1.22 to 7.06) increased risk of developing stroke. Strong evidence was observed in men, with an HR (95% CI) of 4.12 (1.50, 11.28), but not in women (HR = 1.66, 95% CI 0.34, 8.19). Individuals in the high-stable group had increased values of baseline covariates, but the adjusted HR (95% CI), at 1.23 (0.77, 1.97), was not significant for the study cohort or for men and women separately.

Conclusions

This study revealed that a decreasing haemoglobin trajectory was associated with an increased risk of stroke in men. These findings suggest that long-term decreasing haemoglobin levels might increase the risk of stroke.

Effect of tooth loss and nutritional status on outcomes after ischemic stroke

OBJECTIVES

Tooth loss, closely associated with malnutrition, increases the risk for cardiovascular disease. The aim of this study was to examine the link between tooth loss, nutritional status, and stroke outcomes.

METHODS

We retrospectively analyzed 195 consecutive patients with acute ischemic stroke who were evaluated for tooth loss. Tooth loss was classified as mild or severe. Nutritional status was evaluated using the Controlling Nutritional Status (CONUT) score. A poor neurologic outcome was defined as a score of 3 to 6 on the modified Rankin Scale at 3 mo post-stroke onset; a score of 0 to 2 was defined as a good outcome.

RESULTS

A significant correlation was observed between tooth loss and the CONUT score at admission (ρ = 0.156; P = 0.034). Patients with poor outcomes had higher CONUT scores (P < 0.001) and a greater frequency of severe tooth loss (P = 0.025). On multivariate analysis, severe tooth loss (odds ratio [OR], 3.93; 95% confidence interval [CI], 1.31-11.8) and the CONUT score (OR, 1.33; 95% CI, 1.02-1.74) were independently associated with poor stroke outcomes.

CONCLUSIONS

Nutritional status was associated with tooth loss among patients with acute ischemic stroke. Severe tooth loss and a higher CONUT score were independently associated with poor stroke outcomes.

The Methylenetetrahydrofolate Reductase C677T (rs1801133) and Apolipoprotein A5-1131T>C (rs662799) Polymorphisms, and Anemia Are Independent Risk Factors for Ischemic Stroke

BACKGROUND

Although there is adequate knowledge as to the role of traditional cardiovascular risk factors on stroke incidence, knowledge of other risk factors, particularly genetic ones, is still incomplete.

METHODS

To assess the participation of some polymorphisms, along with other modifiable risk factors, a case-control study was conducted. A total of 253 cases were identified in the emergency room of a general regional hospital, with a clinical trait of stroke confirmed by a skull computerized axial tomography scan. In the surgery ward, 253 controls were identified, gender and age (±5 years) matched. Biochemical parameters were measured, and 4 polymorphisms were genotyped by polymerase chain reaction, rs1801133 (methylenetetrahydrofolate reductase [MTHFR]), rs1498373 (dimethylarginine dimethylaminohydrolase type 1 [DDAH1]), rs662799 (apolipoprotein A5 [APOA5]), and rs1799983 (endothelial nitric oxide). Odds ratios were estimated to assess the strength of association, with 95% confidence intervals, both in a matched case-control analysis and in a conditional regression analysis.

RESULTS

Cases had higher mean blood pressure and triglycerides and lower hemoglobin levels. Heterozygous and homozygous subjects to the rs1801133 variant of the MTHFR gene had a 3-fold higher risk of stroke. In the dominant model, those with the polymorphism rs662799 of the promoter region for APOA5 had twice the risk of stroke. Anemia increased the risk of stroke 4-fold.

CONCLUSIONS

Polymorphisms of the genes MTHFR (rs1801133) and APOA5 (rs662799), as well as anemia, are independent risk factors for stroke in Mexicans, together with traditional cardiovascular risk factors such as high triglycerides and high blood pressure.