Outcomes studies in cerebrovascular neurosurgery

Systematic reviews and meta-analyses in the cerebrovascular space: essential domains for readers

INTRODUCTION

Systematic Review and Meta-Analysis (SRMAs) in neurosurgery have significantly increased. With approximately 1 million patients affected by cerebrovascular disease annually, interpreting SRMAs necessitates a systematic approach. The objective of this review is to identify and describe four essential domains for SRMA interpretation.

METHODS

This review outlines the necessities of reviewing existing literature and methodological frameworks essential for interpreting cerebrovascular neurosurgery SRMAs. Each domain is to accurately assess study design variations, heterogeneity assessment methods, outcome comparability strategies, and the impact of technological advancements and time bias on study outcomes.

RESULTS

Study design evaluation distinguishes between randomized controlled trials (RCTs) and non-randomized studies. RCTs provide high internal validity, but as seen in the ARUBA trial, can contain internal flaws that necessitate a deeper understanding before application to clinical practices. Non-randomized studies offer valuable real-world insights. A heterogeneity assessment involves readers and writers accurately using forest plots, Cochrane's Q test, Higgins I² statistics, subgroup analysis, and meta-regressions to understand a study's clinical findings. The expertise thresholds, as in the NASCET trial, significantly impact a study's external validity. Strategies such as the GRADE approach can assist in managing diverse outcome measures. Technological advancements, particularly in endovascular procedures and SRS, influence the accuracy of comparing studies across periods, and thus swiftly outdate older studies, lowering the applicability of SRMAs.

CONCLUSION

Effective interpretation of cerebrovascular neurosurgery SRMAs requires attention to study design, heterogeneity, outcome comparability, and technological advancements. These domains collectively enable evidence-based clinical decision-making and optimized patient care in a dynamic field.

Living with a Brain AVM: A Quality of Life Assessment

BACKGROUND AND PURPOSE

Brain arteriovenous malformations (AVM) are uncommon vascular lesions with the risk of hemorrhage, epileptic seizures, neurological deficits, and headache. Comparing the risks of the natural history and that of preventive treatment, a recent study has found observation more beneficial than treatment for unruptured AVMs. This study, however, did not consider the long-term impact of carrying a brain AVM on everyday activities. In this study we analyzed the Quality Of Life (QOL) of patients with untreated AVMs, a measure increasingly used in clinical trials to asses this kind of impact.

METHODS

We enrolled 36 patients with unruptured, untreated brain AVM from our hospital database and measured their QOL retrospectively using the EQ-5D-5L questionnaire. As a control group we used the results of the Research Report, a nationwide study based on the quality of life of 5534 healthy Hungarians in 2002. Due to the low number of cases, statistical analysis could not be made.

RESULTS

Headache proved to be the most common AVM-related sign in our cohort (40%, n = 17), with a female predominance; neurological deficit was detected in 33% (n = 14), while epileptic seizures occurred in 26% (n = 11), more commonly affecting male subjects. Anxiety and discomfort seemed to be the most prevalent influencing factors on QOL, especially in the youngest age group (18-34 years). Female subjects showed a greater dependence than men in all age groups, though males had a more significant impairment in their usual activities. Older patients were affected more significantly in their self-care and usual activities compared with the younger population.

CONCLUSIONS

Untreated AVMs have a significant negative impact on patients carrying unruptured brain AVMs, as proved by QOL assessment. Beside neurological deficits, this impact should also be considered in the therapeutic decision.

Tigecycline reduced tumor necrosis factor alpha level and inhospital mortality in spontaneous supratentorial intracerebral hemorrhage

Background: The outcome of patients with spontaneous supratentorial intracerebral hemorrhage (SSICH) is unsatisfactory. Inflammatory response secondary to brain injury as well as those resulted from surgical procedure were considered responsible of this outcome. This study was intended to elucidate the anti-inflammatory activity of tigecycline by measuring TNF-α level and its neuroprotective effect as represented by inhospital mortality rate.Methods: Patients with SSICH who were prepared for hematoma evacuation were randomized to receive either tigecycline (n=35) or fosfomycine (n=37) as prophylactic antibiotic. TNF-α level was measured in all subjects before surgery and postoperatively on day-1 and day-7. A repeated brain CT Scan was performed on postoperative day-7. The Glasgow outcome scale (GOS) and length of stay (LOS) were recorded at the time of hospital discharge. Data were analyzed using Mann-Whitney and Chi square test. Relative clinical effectiveness was measured by calculating the number needed to treat (NNT).Results: There was a significant difference regarding the proportion of subject who had  reduced TNF-α level on postoperative day-7 between the groups receiving tigecycline and fosfomycine (62% vs 29%, p=0.022). Decrease brain edema on CT control (86% vs 80%, p=0.580). Tigecycline administration showed a tendency of better clinical effectiveness in lowering inhospital mortality (17% vs 35%; p=0.083; OR=0.49; NNT=5) and worse clinical outcome / GOS ≤ 2 (20% vs 38% ; p=0.096; OR=0.41; NNT=6). LOS ≥ 15 hari ( 40% vs 27%; p=0.243; OR=1.81; NNT=8).Conclusion: Tigecycline showed anti-inflammatory and neuroprotective activities. These activities were associated with improved clinical outcome in patients with SSICH after hematoma evacuation.

Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis

Background:

Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH).

Methods:

The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months.

Results:

Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56–2.45, P < 0.01).

Conclusions:

A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

Association between dentures and the rate of falls in dementia

Background

Poor oral health, chronic diseases, functional decline, and low cognitive ability can increase the risk of falls in the elderly.

Objectives

The current study aimed to show the effects of oral health, diabetes mellitus (DM), hypertension (HT), heart disease, functional status, and sociodemographic factors on the risk of falls in elderly with dementia.

Materials and methods

The sample comprised 1,210 Malaysian elderly who were demented and noninstitutionalized. This study was a national cross-sectional survey entitled “Determinants of Health Status among Older Malaysians”. The effects of age, ethnicity, sex differences, marital status, educational level, oral health, DM, HT, heart disease, and functional status on the risk of falls were evaluated. The multiple logistic regression model was used to estimate the effects of contributing variables on the risk of falls in samples.

Results

The prevalence of falls was approximately 17% in subjects. It was found that age (odds ratio [OR] 1.02), non-Malay ethnicity (OR 1.66), heart disease (OR 1.92), and functional decline (OR 1.58) significantly increased the risk of falls in respondents (P<0.05). Furthermore, having teeth (OR 0.59) and dentures (OR 0.66) significantly decreased the rate of falls (P<0.05).

Conclusion

It was concluded that age, non-Malay ethnicity, functional decline, heart disease, and oral health significantly affected falls in dementia.