ArticlePloS one2020
Surgical decision making in the setting of severe traumatic brain injury: A survey of neurosurgeons.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction performance of the machine learning model in predicting mortality risk in patients with traumatic brain injuries: a systematic review and meta-analysis.BMC medical informatics and decision making · 2023Pooled it
- Minimally Invasive Surgery With Thrombolysis for Intracerebral Hemorrhage Evacuation: Bayesian Reanalysis of a Randomized Controlled Trial.Neurology · 2023Trial
- A novel CT-based edema grading system combined with machine learning for precise prognostic prediction in traumatic brain injury.European journal of medical research · 2025Article
- Article
- Noise is an underrecognized problem in medical decision making and is known by other names: a scoping review.BMC medical informatics and decision making · 2025Article
- Machine learning-enhanced causal inference of surgical decisions and rehabilitation strategies in traumatic brain injury.Frontiers in neurology · 2025Article
- The application of mesenchymal stem cells in the treatment of traumatic brain injury: Mechanisms, results, and problems.Histology and histopathology · 2024Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSurgical decision-making in severe traumatic brain injury (TBI) is complex. Neurosurgeons weigh risks and benefits of interventions that have the potential to both maximize the chance of recovery and prolong suffering. Inaccurate prognostication can lead to over- or under-estimation of outcomes and influence treatment recommendations.
objectiveTo evaluate the impact of evidence-based risk estimates on neurosurgeon treatment recommendations and prognostic beliefs in severe TBI.
methodsIn a survey-based randomized experiment, a total of 139 neurosurgeons were presented with two hypothetical patient with severe TBI and subdural hematoma; the intervention group received additional evidence-based risk estimates for each patient. The main outcome was neurosurgeon treatment recommendation of non-surgical management. Secondary outcomes included prediction of functional recovery at six months.
resultsIn the first patient scenario, 22% of neurosurgeons recommended non-surgical management and provision of evidence-based risk estimates increased the propensity to recommend non-surgical treatment (odds ratio [OR]: 2.81, 95% CI: 1.21-6.98; p = 0.02). Neurosurgeon prognostic beliefs of 6-month functional recovery were variable in both control (median 20%, IQR: 10%-40%) and intervention (30% IQR: 10%-50%) groups and neurosurgeons were less likely to recommend non-surgical management when they believed prognosis was favorable (odds ratio [OR] per percentage point increase in 6-month functional recovery: 0.97, 95% confidence interval [CI]: 0.95-0.99). The results for the second patient scenario were qualitatively similar.
conclusionsOur findings show that the provision of evidence-based risk predictions can influence neurosurgeon treatment recommendations and prognostication, but the effect is modest and there remains large variability in neurosurgeon prognostication.
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