Selective Decontamination of the Digestive Tract in Invasively Ventilated Patients in an Intensive Care Unit: A protocol for a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Introduction The use of Selective Decontamination of the Digestive Tract (SDD) as a preventative infection-control strategy in invasively ventilated patients in the intensive care unit (ICU) remains low despite numerous randomised controlled trials (RCTs) consistently reporting reductions in interval mortality rates and shorter durations of mechanical ventilation. The Selective Decontamination of the Digestive Tract in the Intensive Care Unit (SuDDICU) cluster cross-over RCT, that includes over 5500 participants randomised to receive a standardised commercial grade SDD interventions or standard care, will be reported in 2022 and will add substantive weight to previous RCT data assessing the effect of SDD on interval mortality compared to standard care. We will conduct an updated systematic review and prospective aggregate data meta-analysis of previous conducted and published RCTs, developed using a protocol and statistical analysis plan completed prior to the completion of the SuDDICU RCT and including the SuDDICU data to present the most current evidence available to guide clinical practice. Methods and analysis We will include RCTs that compare the effect on hospital mortality and other patient-centred outcomes of treatment with SDD compared to standard care in invasively ventilated adults in the ICU. We will perform a search that includes the electronic databases MEDLINE and EMBASE and clinical trial registries. Two reviewers will independently screen titles and abstracts, perform full article reviews and extract study data, with discrepancies resolved by a third reviewer. We will report study characteristics and quantify risk of bias. We will perform random effects Bayesian meta-analyses to provide pooled estimates that SDD improves outcomes, whenever it is feasible to do so. We will evaluate overall certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework. Conclusion This updated systematic review and prospective meta-analysis will provide clinicians with an expedited assessment of the totality of current evidence about the effect on mortality of using SDD in mechanically ventilated ICU patients.
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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 | 0.084 | 0.159 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.025 | 0.029 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".