Comorbidity in adults with traumatic brain injury and all-cause mortality: a systematic review
Bibliographic record
Abstract
OBJECTIVES: Comorbidity in traumatic brain injury (TBI) has been recognised to alter the clinical course of patients and influence short-term and long-term outcomes. We synthesised the evidence on the effects of different comorbid conditions on early and late mortality post-TBI in order to (1) examine the relationship between comorbid condition(s) and all-cause mortality in TBI and (2) determine the influence of sociodemographic and clinical characteristics of patients with a TBI at baseline on all-cause mortality. DESIGN: Systematic review. DATA SOURCES: Medline, Central, Embase, PsycINFO and bibliographies of identified articles were searched from May 1997 to January 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Included studies met the following criteria: (1) focused on comorbidity as it related to our outcome of interest in adults (ie, ≥18 years of age) diagnosed with a TBI; (2) comorbidity was detected by any means excluding self-report; (3) reported the proportion of participants without comorbidity and (4) followed participants for any period of time. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers extracted the data and assessed risk of bias using the Quality in Prognosis Studies tool. Data were synthesised through tabulation and qualitative description. RESULTS: A total of 27 cohort studies were included. Among the wide range of individual comorbid conditions studied, only low blood pressure was a consistent predictors of post-TBI mortality. Other consistent predictors were traditional sociodemographic risk factors. Higher comorbidity scale, scores and the number of comorbid conditions were not consistently associated with post-TBI mortality. CONCLUSIONS: Given the high number of comorbid conditions that were examined by the single studies, research is required to further substantiate the evidence and address conflicting findings. Finally, an enhanced set of comorbidity measures that are suited for the TBI population will allow for better risk stratification to guide TBI management and treatment. PROSPERO REGISTRATION NUMBER: CRD42017070033.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".