The use of standardized management protocols for critically ill patients with non-traumatic subarachnoid hemorrhage: a protocol of a systematic review and meta-analysis
Bibliographic record
Abstract
Caring for patients with subarachnoid hemorrhage (SAH) presents unique challenges, due in part to the severity of the underlying insult, competing systemic injuries, and unpredictable clinical course. Even when management occurs in dedicated critical care settings, treatment uncertainty often persists, and morbidity and mortality from the condition remain high. Complex decisions in SAH care may be simplified with the use of standardized management protocols (SMPs). SMPs incorporate evidence-based guidelines into a practical framework for decision-making, thereby providing clinicians with an algorithm for organizing treatments. But despite these potential advantages, it is currently unknown whether SMPs may improve outcomes in the critical care of patients with SAH. We will conduct a systematic review of cohort studies and randomized control trials of adult patients with non-traumatic SAH who received care according to a standardized management protocol. Comprehensive search strategies will be developed for MEDLINE, EMBASE, WoS, CINAHL, and CENTRAL, to identify studies for review. The gray literature will be scanned for further eligible studies. Two reviewers will independently screen the material generated by the search to identify studies for inclusion. A standardized data extraction form will be used to collect information on study design, baseline characteristics, details of the management protocol employed, and primary and secondary outcomes. Where possible, meta-analyses with random-effects models will be used to calculate pooled estimates of effect sizes. Statistical heterogeneity will be evaluated with the I2 statistics, and risk of bias and reporting quality will be assessed independently and in duplicate with standardized scales. We anticipate a significant degree of clinical heterogeneity in our review, as protocols will likely vary in their content, implementation, and ICU setting. We will aim to summarize the current literature in this domain to understand if SMPs, as a low-cost process-targeted intervention, improve outcomes for critically ill patients with SAH. Our review will additionally inform future research endeavors to improve the processes of care for this patient population. CRD42017069173
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.128 | 0.195 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.024 | 0.033 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".