Systematic review of the relationship between comorbidity and out-of-hospital cardiac arrest outcomes
Bibliographic record
Abstract
OBJECTIVES: To assess the current evidence on the effect pre-arrest comorbidity has on survival and neurological outcomes following out-of-hospital cardiac arrest (OHCA). DESIGN: Systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. DATA SOURCES: MEDLINE, Ovid Embase, Scopus, CINAHL, Cochrane Library and MedNar were searched from inception to 31 December 2018. ELIGIBILITY CRITERIA: Studies included if they examined the association between prearrest comorbidity and OHCA survival and neurological outcomes in adult or paediatric populations. DATA EXTRACTION AND SYNTHESIS: Data were extracted from individual studies but not pooled due to heterogeneity. Quality of included studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. RESULTS: This review included 29 observational studies. There were high levels of clinical heterogeneity between studies with regards to patient recruitment, inclusion criteria, outcome measures and statistical methods used which ultimately resulted in a high risk of bias. Comorbidities reported across the studies were diverse, with some studies reporting individual comorbidities while others reported comorbidity burden using tools like the Charlson Comorbidity Index. Generally, prearrest comorbidity was associated with both reduced survival and poorer neurological outcomes following OHCA with 79% (74/94) of all reported adjusted results across 23 studies showing effect estimates suggesting lower survival with 42% (40/94) of these being statistically significant. OHCA survival was particularly reduced in patients with a prior history of diabetes (four out of six studies). However, a prearrest history of myocardial infarction appeared to be associated with increased survival in one of four studies. CONCLUSIONS: Prearrest comorbidity is generally associated with unfavourable OHCA outcomes, however differences between individual studies makes comparisons difficult. Due to the clinical and statistical heterogeneity across the studies, no meta-analysis was conducted. Future studies should follow a more standardised approach to investigating the impact of comorbidity on OHCA outcomes. PROSPERO REGISTRATION NUMBER: CRD42018087578.
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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 | 0.010 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".