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Future studies could be better designed and executed as part of a large (inter)national ICH trials consortium, consisting of dedicated interdisciplinary teams of neurologists, neurosurgeons, intensivists, and epidemiologists. We advocate studies to be pragmatic and adhere to the IDEAL recommendations and CONSORT guidelines.

New findings and research regarding the microsurgical treatment of intracerebral aneurysms (IAs) continue to advance even in the era of endovascular therapies. Research in the past 2 decades has continued to revolve around the question of whether open surgery or endovascular treatment is preferable. The answer remains both complex and in flux.

This review focuses on microsurgery, reflects on the research decisions of previous landmark studies, and proposes future study designs that may further our understanding of IAs and how best to treat them.

The future of IA research may include a combination of pragmatic trials, artificial intelligence integrated tools, and mining of large data sets, in addition to the publication of high-quality single-center studies.

The future will likely emphasize testing innovative techniques, looking at granular patient data, and considering every patient encounter as a potential source of knowledge, creating a system in which data are updated daily because each patient interaction contributes to answering important research questions.

The future will likely emphasize testing innovative techniques, looking at granular patient data, and considering every patient encounter as a potential source of knowledge, creating a system in which data are updated daily because each patient interaction contributes to answering important research questions.

To investigate whether financial bias exists in hydrocephalus and vertebral augmentation literature.

A systematic literature search was performed in PubMed of studies concerning vertebral augmentation and cerebrospinal fluid valves. The relationship between reported conflicts of interest and the nature of the conclusion (positive vs. neutral and negative) was analyzed.

Having a conflict of interest was significantly associated with reporting a positive conclusion in studies investigating valves for hydrocephalus (92.3% positive conclusion vs. 36.4%; P= 0.001), but not for cement augmentation studies (80.5% positive conclusion vs. 65.7%; P= 0.087). As studies concerning vertebral augmentation implants had only positive conclusions, no analysis could be performed.

Our findings suggest a positive relationship between reported conflict of interest and positive outcome in neurosurgical literature concerning cerebrospinal fluid valves.

Our findings suggest a positive relationship between reported conflict of interest and positive outcome in neurosurgical literature concerning cerebrospinal fluid valves.The UK neurosurgical community has a track record of delivering high-quality, practice-changing clinical research studies, facilitated by a robust clinical research infrastructure and close collaborations between neurosurgical centers. More recently, these large-scale studies have been conceived, developed, and delivered by neurosurgical trainees, working under the umbrella of the British Neurosurgical Trainee Research Collaborative (BNTRC). In this paper, we outline the current landscape of large-scale neurosurgical studies in the UK, focusing on the role of trainees in facilitating this research. Importantly, we focus on our experience of trainee-led studies, including the development of the network, current challenges, and future directions. We believe that a similar model can be applied in different settings and countries, which will drive up the quality of neurosurgical research, ultimately benefiting future neurosurgical patients.

Quantifying quality of health care can provide valuable information to patients, providers, and policy makers. However, the observational nature of measuring quality complicates assessments.

We describe a conceptual model for defining quality and its implications about the data collected, how to make inferences about quality, and the assumptions required to provide statistically valid estimates. Twenty-one binary or polytomous quality measures collected from 101,051 adult Medicaid beneficiaries aged 18-64 years with schizophrenia from 5 U.S. states show methodology. A categorical principal components analysis establishes dimensionality of quality, and item response theory models characterize the relationship between each quality measure and a unidimensional quality construct. Latent regression models estimate racial/ethnic and geographic quality disparities.

More than 90% of beneficiaries filled at least 1 antipsychotic prescription and 19% were hospitalized for schizophrenia during a 12-month observatie estimated that has more statistical power to detect differences among subjects than the observed mean per subject.

Stepped wedge cluster randomized trials enable rigorous evaluations of health intervention programs in pragmatic settings. In the present study, we aimed to update neurosurgeon scientists on the design of stepped wedge randomized trials.

We have presented an overview of recent methodological developments for stepped wedge designs and included an update on the newer associated methodological tools to aid with future study designs.

We defined the stepped wedge trial design and reviewed the indications for the design in depth. In addition, key considerations, including mainstream methods of analysis and sample size determination, were discussed.

Stepped wedge designs can be attractive for study intervention programs aiming to improve the delivery of patient care, especially when examining a small number of heterogeneous clusters.

Stepped wedge designs can be attractive for study intervention programs aiming to improve the delivery of patient care, especially when examining a small number of heterogeneous clusters.

It is well accepted that randomized controlled trials provide the greatest quality of evidence about effectiveness and safety of new interventions. In neurosurgery, randomized controlled trials face challenges, with their use remaining relatively low compared with other clinical areas. Adaptive designs have emerged as a method for improving the efficiency and patient benefit of trials. They allow modifications to the trial design to be made as patient outcome data are collected. The benefit they provide is highly variable, predominantly governed by the time taken to observe the primary endpoint compared with the planned recruitment rate. They also face challenges in design, conduct, and reporting.

We provide an overview of the benefits and challenges of adaptive designs, with a focus on neurosurgery applications. To investigate how often an adaptive design may be advantageous in neurosurgery, we extracted data on recruitment rates and endpoint lengths for ongoing neurosurgery trials registered in ClinicalTrials.gov.

We found that a majority of neurosurgery trials had a relatively short endpoint length compared with the planned recruitment period and therefore may benefit from an adaptive trial. However, we did not identify any ongoing ClinicalTrials.gov registered neurosurgery trials that mentioned using an adaptive design.

Adaptive designs may provide benefits to neurosurgery trials and should be considered for use more widely. Use of some types of adaptive design, such as multiarm multistage, may further increase the number of interventions that can be tested with limited patient and financial resources.

Adaptive designs may provide benefits to neurosurgery trials and should be considered for use more widely. Use of some types of adaptive design, such as multiarm multistage, may further increase the number of interventions that can be tested with limited patient and financial resources.

When using observational data to estimate the causal effects of a treatment on clinical outcomes, we need to adjust for confounding. In the presence of time-dependent confounders that are affected by previous treatment, adjustments cannot be made via the conventional regression approach or propensity score-based methods, but requires sophisticated methods called g-methods. We aimed to introduce g-methods to estimate the causal effects of treatment strategies defined by treatment at multiple time points, such as treat 2 days versus treat only day 1 versus never-treat.

Two g-methods were introduced the g-formula and inverse probability-weighted marginal structural models. Under exchangeability, consistency, and positivity assumptions, they provide a consistent estimate of the causal effects of the treatment strategy.

Using a numeric example that mimics the observational study data, we presented how the g-formula and inverse probability-weighted marginal structural models can estimate the effect of the treatment strategy.

Both g-formula and inverse probability-weighted marginal structural models can correctly estimate the effect of the treatment strategy under 3 identifiability assumptions, which conventional regression analysis cannot. G-methods may assist in estimating the effect of treatment strategy defined by treatment at multiple time points.

Both g-formula and inverse probability-weighted marginal structural models can correctly estimate the effect of the treatment strategy under 3 identifiability assumptions, which conventional regression analysis cannot. G-methods may assist in estimating the effect of treatment strategy defined by treatment at multiple time points.

Survival analyses are heavily used to analyze data in which the time to event is of interest. The purpose of this paper is to introduce some fundamental concepts for survival analyses in medical studies.

We comprehensively review current survival methodologies, such as the nonparametric Kaplan-Meier method used to estimate survival probability, the log-rank test, one of the most popular tests for comparing survival curves, and the Cox proportional hazard model, which is used for building the relationship between survival time and specific risk factors. More advanced methods, such as time-dependent receiver operating characteristic, restricted mean survival time, and time-dependent covariates are also introduced.

This tutorial is aimed toward covering the basics of survival analysis. We used a neurosurgical case series of surgically treated brain metastases from non-small cell lung cancer patients as an example. The survival time was defined from the date of craniotomy to the date of patient death.

This work is an attempt to encourage more investigators/medical practitioners to use survival analyses appropriately in medical research. We highlight some statistical issues, make recommendations, and provide more advanced survival modeling in this aspect.

This work is an attempt to encourage more investigators/medical practitioners to use survival analyses appropriately in medical research. We highlight some statistical issues, make recommendations, and provide more advanced survival modeling in this aspect.Neurosurgeons today are inundated with rapidly amassing neurosurgical research publications. Tofacitinib price Systematic reviews and meta-analyses have consequently surged in popularity because, when executed properly, they constitute a high level of evidence and may save busy neurosurgeons many hours of combing and reviewing the literature for relevant articles. Meta-analysis refers to the quantitative (and discretionary) component of systematic reviews. It involves applying statistical techniques to combine effect sizes from multiple studies, which might offer more actionable insights than a systematic review without meta-analysis. Well-executed meta-analyses may prove instructive for clinical practice, but poorly conducted ones sow confusion and have the potential to cause harm. Unfortunately, recent audits have found the conduct and reporting of meta-analyses in neurosurgery (but also other surgical disciplines) to be relatively lackluster in methodologic rigor and compliance to established guidelines. Some of these deficiencies can be easily remedied through better awareness and adherence to prescribed standards-which will be reviewed in this article-but others stem from inherent problems with the source data (e.