β-Blockers in sepsis: protocol for a systematic review and meta-analysis of randomised control trials
Bibliographic record
Abstract
INTRODUCTION: Sepsis is a common and deadly complication of infection. As part of the host response, sympathetic stimulation can result in septic myocardial depression, and metabolic, haematological and immunological dysfunction. Administration of β-blockers may attenuate this pathophysiological response to infection, but the effects on clinical outcomes are unknown. The objective of this systematic review is to determine the efficacy and safety of β-blockers in adults with sepsis using data from randomised control trials. METHODS AND ANALYSIS: We will identify randomised control trials comparing treatment with β-blockers, versus placebo or standard care in adults with sepsis. Data sources will include MEDLINE, EMBASE, CENTRAL, clinical trial registries and conference proceedings. Two reviewers will independently determine trial eligibility. For each included trial, we will conduct duplicate independent data extraction, risk of bias assessment and evaluation of the quality of the evidence using the GRADE approach. ETHICS AND DISSEMINATION: Our systematic review will evaluate the effects of β-blockers in adults with sepsis, comprehensively summarising and appraising the available evidence from randomised control trials. The results of this systematic review will help clinicians treating patients with sepsis to understand the potential role of β-blockade, and inform future research on this topic. Our findings will be disseminated through conference presentation and publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: CRD42016036933.
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 | 0.080 | 0.125 |
| Meta-epidemiology (narrow) | 0.009 | 0.006 |
| Meta-epidemiology (broad) | 0.033 | 0.034 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.068 | 0.008 |
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".