The Effect of Morbid Obesity on Subarachnoid Hemorrhage Prognosis in the United States

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.

Risk Factors for Delayed Cerebral Ischemia in Good-Grade Patients With Aneurysmal Subarachnoid Hemorrhage

Background A subset of good-grade patients with aneurysmal subarachnoid hemorrhage (aSAH) develop delayed cerebral ischemia (DCI) that may cause permanent disabilities after aSAH. However, little is known about the risk factors of DCI among this specific patient group. Methods and Results We obtained a multinational cohort of good-grade (Glasgow Coma Scale 13-15 on admission) patients with aSAH by pooling patient data from 4 clinical trials and 2 prospective cohort studies. We collected baseline data on lifestyle-related factors and the clinical characteristics of aSAHs. By calculating fully adjusted risk estimates for DCI and DCI-related poor outcome, we identified the most high-risk patient groups. The pooled study cohort included 1918 good-grade patients with aSAH (median age, 51 years; 64% women), of whom 21% and 7% experienced DCI and DCI-related poor outcome, respectively. Among men, patients with obesity and (body mass index ≥30 kg/m²) thick aSAH experienced most commonly DCI (33%) and DCI-related poor outcome (20%), whereas none of the normotensive or young (aged <50 years) men with low body mass index (body mass index <22.5 kg/m²) had DCI-related poor outcome. In women, the highest prevalence of DCI (28%) and DCI-related poor outcome (13%) was found in patients with preadmission hypertension and thick aSAH. Conversely, the lowest rates (11% and 2%, respectively) were observed in normotensive women with a thin aSAH. Conclusions Increasing age, thick aSAH, obesity, and preadmission hypertension are risk factors for DCI in good-grade patients with aSAH. These findings may help clinicians to consider which good-grade patients with aSAH should be monitored carefully in the intensive care unit.

Body Mass Index and the Risk of Poor Outcome in Surgically Treated Patients With Good-Grade Aneurysmal Subarachnoid Hemorrhage

BACKGROUND

Heterogeneity among study populations and treatment procedures has led to conflicting results on outcome predictors for patients with aneurysmal subarachnoid hemorrhage (aSAH). One such conflicting predictor is body mass index (BMI).

OBJECTIVE

To clarify whether high BMI values protect patients from poor outcome after aSAH, as previously suggested.

METHODS

We surveyed 6 prospective studies conducted in 14 different countries (93 healthcare units) between 1985 and 2016 and pooled the data on surgically treated patients with good-grade (Glasgow Coma Scale 13-15 on admission) aSAH. We calculated BMI for each patient and created 4 balanced categories based on the BMI quartiles of each cohort. We calculated adjusted odds ratios (ORs) with 95% CIs for the 3-month poor outcome (Glasgow Outcome Scale 1-3) by BMI.

RESULTS

The pooled study cohort included 1692 patients with good-grade aSAH (mean age 51 years; 64% female). At 3 months, 288 (17%) had poor outcomes. The risk for poor outcomes increased with increasing BMI values (OR = 1.15 [1.02-1.31] per each standard deviation increase of BMI). The risk for poor outcome was over 1.6 times higher (OR = 1.66 [1.13-2.43]) in the highest BMI category (range 27.1-69.2) compared with the lowest BMI category (range 14.4-23.8). These associations were found in each of the 6 study cohorts in both men and women, regardless of age.

CONCLUSION

Because higher BMI values seem to associate with poor outcomes in surgically treated patients with good-grade aSAH, it seems unlikely that obesity protects patients with aSAH from poor outcomes.

Impact of obesity and diabetes on postoperative outcomes following surgical treatment of nontraumatic subarachnoid hemorrhage: Analysis of the ACS-NSQIP Database

BACKGROUND

Nontraumatic subarachnoid hemorrhage (SAH) refers to high pressure extravasation of blood into the subarachnoid space that typically occurs spontaneously from rupture of cerebral aneurysm. The purpose of this study was to identify postoperative complications requiring increased surveillance in obese, diabetic, and hypertensive patients.

METHODS

Patients who underwent surgical treatment for nontraumatic SAH were queried in the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database from the years 2012-2018. Cases were identified using ICD codes and then classified independently by three dichotomous diagnoses: obesity, diabetes, and hypertension.

RESULTS

Among 1,002 patients meeting inclusion criteria, 311 (31%) were obese (BMI >30), 86 (9%) had diabetes treated with insulin or non-insulin agents and 409 (41%) required medication for hypertension. There was a statistically significant association between diabetes and post-operative pneumonia (OR = 1.694; 95% CI 0.995 - 2.883; p = 0.050), prolonged ventilator dependence (OR = 1.700; 95% CI 1.087 - 2.661; p = 0.019), and death (OR = 1.846; 95% CI 1.071 - 3.179; p = 0.025). Medicationdependent hypertension was statistically associated with incidence of stroke/CVA (OR = 1.763; 95% CI 1.056 - 2.943; p = 0.023). Obesity was not associated with adverse outcomes in this population.

CONCLUSIONS

In patients undergoing surgical management of SAH, hypertensive and diabetic patients had poorer outcomes, including prolonged ventilator dependence, pneumonia, stroke/CVA, and death. Surprisingly, preexisting obesity was not associated with poor outcomes. In fact, overweight BMI, Class I, and Class II obesity had decreased need for transfusion in the 30-day postoperative period.

Body mass index and leptin levels in serum and cerebrospinal fluid in relation to delayed cerebral ischemia and outcome after aneurysmal subarachnoid hemorrhage

Aneurysmal subarachnoid hemorrhage (SAH) is associated with a high mortality rate and may leave surviving patients severely disabled. After the initial hemorrhage, clinical outcome is further compromised by the occurrence of delayed cerebral ischemia (DCI). Overweight and obesity have previously been associated with protective effects in the post-bleeding phase. The aim of this study was to assess the effects of a patient’s body mass index (BMI) and leptin levels on the occurrence of DCI, DCI-related cerebral infarction, and clinical outcome. In total, 263 SAH patients were included of which leptin levels were assessed in 24 cases. BMI was recorded along disease severity documented by the Hunt and Hess and modified Fisher scales. The occurrence of clinical or functional DCI (neuromonitoring, CT Perfusion) was assessed. Long-term clinical outcome was documented after 12 months (extended Glasgow outcome scale). A total of 136 (51.7%) patients developed DCI of which 72 (27.4%) developed DCI-related cerebral infarctions. No association between BMI and DCI occurrence (P = .410) or better clinical outcome (P = .643) was identified. Early leptin concentration in serum (P = .258) and CSF (P = .159) showed no predictive value in identifying patients at risk of unfavorable outcomes. However, a significant increase of leptin levels in CSF occurred from 326.0 pg/ml IQR 171.9 prior to DCI development to 579.2 pg/ml IQR 211.9 during ongoing DCI (P = .049). In our data, no association between obesity and clinical outcome was detected. After DCI development, leptin levels in CSF increased either by an upsurge of active transport or disruption of the blood-CSF barrier. This trial has been registered at ClinicalTrials.gov (NCT02142166) as part of a larger-scale prospective data collection. BioSAB: https://clinicaltrials.gov/ct2/show/NCT02142166

Predicting High-Value Care Outcomes After Surgery for Skull Base Meningiomas

BACKGROUND

Although various predictors of adverse postoperative outcomes among patients with meningioma have been established, research has yet to develop a method for consolidating these findings to allow for predictions of adverse health care outcomes for patients diagnosed with skull base meningiomas. The objective of the present study was to develop 3 predictive algorithms that can be used to estimate an individual patient's probability of extended length of stay (LOS) in hospital, experiencing a nonroutine discharge disposition, or incurring high hospital charges after surgical resection of a skull base meningioma.

METHODS

The present study used data from patients who underwent surgical resection for skull base meningiomas at a single academic institution between 2017 and 2019. Multivariate logistic regression analysis was used to predict extended LOS, nonroutine discharge, and high hospital charges, and 2000 bootstrapped samples were used to calculate an optimism-corrected C-statistic. The Hosmer-Lemeshow test was used to assess model calibration, and P < 0.05 was considered statistically significant.

RESULTS

A total of 245 patients were included in our analysis. Our cohort was mostly female (77.6%) and white (62.4%). Our models predicting extended LOS, nonroutine discharge, and high hospital charges had optimism-corrected C-statistics of 0.768, 0.784, and 0.783, respectively. All models showed adequate calibration (P>0.05), and were deployed via an open-access, online calculator: https://neurooncsurgery3.shinyapps.io/high_value_skull_base_calc/.

CONCLUSIONS

After external validation, our predictive models have the potential to aid clinicians in providing patients with individualized risk estimation for health care outcomes after meningioma surgery.

Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients

Objective

Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral ischemia (DCI). The ability to accurately predict survival for SAH patients during the hospital course would provide valuable information for healthcare providers, patients, and families. This study aims to utilize electronic health record (EHR) data and machine learning approaches to predict the adverse outcome for nontraumatic SAH adult patients.

Methods

The cohort included nontraumatic SAH patients treated with vasopressors for presumed DCI from a large EHR database, the Cerner Health Facts^® EMR database (2000–2014). The outcome of interest was the adverse outcome, defined as death in hospital or discharged to hospice. Machine learning‐based models were developed and primarily assessed by area under the receiver operating characteristic curve (AUC).

Results

A total of 2467 nontraumatic SAH patients (64% female; median age [interquartile range]: 56 [47–66]) who were treated with vasopressors for presumed DCI were included in the study. 934 (38%) patients died or were discharged to hospice. The model achieved an AUC of 0.88 (95% CI, 0.84–0.92) with only the initial 24 h EHR data, and 0.94 (95% CI, 0.92–0.96) after the next 24 h.

Interpretation

EHR data and machine learning models can accurately predict the risk of the adverse outcome for critically ill nontraumatic SAH patients. It is possible to use EHR data and machine learning techniques to help with clinical decision‐making.

Efficacy and safety of Euiiyin-tang in Korean women with obesity: A randomized, double-blind, placebo-controlled, multicenter trial

BACKGROUND

Obesity is a global health problem and its incidence is on the rise. Euiiyin-tang is an herbal medicinal formula that is often used in the clinical treatment of obesity. The purpose of the present study was to evaluate the efficacy and safety of Euiiyin-tang in obesity treatment.

METHODS

A randomized, double-blind, placebo-controlled, multicenter trial was conducted. Participants with obesity were randomly assigned to receive Euiiyin-tang or placebo 3 times daily for 12-weeks. The primary outcome was weight reduction between the baseline and 12 weeks. The secondary outcomes included the rate of weight loss compared to baseline, and changes in body mass index, lipid profiles, and questionnaires related to the quality of life and diet. Safety factors, such as vital signs and laboratory parameters, were also measured.

RESULTS

A total of 149 participants were randomly distributed to either the Euiiyin-tang group (n = 76) or the placebo group (n = 73). Weight reduction in the Euiiyin-tang group was significantly greater than that in the placebo group (2.50 kg in the Euiiyin-tang group vs. 0.82 kg in the placebo group). The participant response rates of ≥3% weight loss compared to baseline was 36.8 % in the Euiiyin-tang group and 17.8 % in the placebo group. Body mass index, waist circumference, and hip circumference showed a greater change in the Euiiyin-tang group than in the placebo group (1.00, 3.23, and 2.00 in the Euiiyin-tang group vs. 0.33, 1.96, and 0.86 in the placebo group). Questionnaires, lipid profiles, and safety factors did not show significant differences between groups.

CONCLUSION

The results of this study suggest that Euiiyin-tang has beneficial effects on weight loss.

TRIAL REGISTRATION

Clinicaltrials.gov NCT01724099.

Obesity paradox in subarachnoid hemorrhage: a systematic review

As the number of obese people is globally increasing, reports about the putative protective effect of obesity in life-threatening diseases, such as subarachnoid hemorrhage (SAH), are gaining more interest. This theory-the obesity paradox-is challenging to study, and the impact of obesity has remained unclear in survival of several critical illnesses, including SAH. Thus, we performed a systematic review to clarify the relation of obesity and SAH mortality. Our study protocol included systematic literature search in PubMed, Scopus, and Cochrane library databases, whereas risk-of-bias estimation and quality of each selected study were evaluated by the Critical Appraisal Skills Program and Cochrane Collaboration guidelines. A directional power analysis was performed to estimate sufficient sample size for significant results. From 176 reviewed studies, six fulfilled our eligibility criteria for qualitative analysis. One study found paradoxical effect (odds ratio, OR = 0.83 (0.74-0.92)) between morbid obesity (body mass index (BMI) > 40) and in-hospital SAH mortality, and another study found the effect between continuously increasing BMI and both short-term (OR = 0.90 (0.82-0.99)) and long-term SAH mortalities (OR = 0.92 (0.85-0.98)). However, according to our quality assessment, methodological shortcomings expose all reviewed studies to a high-risk-of-bias. Even though two studies suggest that obesity may protect SAH patients from death in the acute phase, all reviewed studies suffered from methodological shortcomings that have been typical in the research field of obesity paradox. Therefore, no definite conclusions could be drawn.