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Record W2998637131 · doi:10.1136/bmj.l6722

Gastrointestinal bleeding prophylaxis for critically ill patients: a clinical practice guideline

2020· letter· en· W2998637131 on OpenAlexaff
Zhikang Ye, Annika Reintam Blaser, Lyubov Lytvyn, Ying Wang, Gordon Guyatt, J Stephen Mikita, Jamie Roberts, Thomas Agoritsas, Sonja Bertschy, Filippo Boroli, Julie Camsooksai, Bin Du, Anja Fog Heen, Jianyou Lu, José M. Mella, Per Olav Vandvik, Robert Wise, Yue Zheng, Lihong Liu, Reed Siemieniuk

Bibliographic record

VenueBMJ · 2020
Typeletter
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineGuidelineIntensive care medicineSucralfateGastrointestinal bleedingStress ulcerMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

CLINICAL QUESTION: What is the role of gastrointestinal bleeding prophylaxis (stress ulcer prophylaxis) in critically ill patients? This guideline was prompted by the publication of a new large randomised controlled trial. CURRENT PRACTICE: Gastric acid suppression with proton pump inhibitors (PPIs) or histamine-2 receptor antagonists (H2RAs) is commonly done to prevent gastrointestinal bleeding in critically ill patients. Existing guidelines vary in their recommendations of which population to treat and which agent to use. RECOMMENDATIONS: This guideline panel makes a weak recommendation for using gastrointestinal bleeding prophylaxis in critically ill patients at high risk (>4%) of clinically important gastrointestinal bleeding, and a weak recommendation for not using prophylaxis in patients at lower risk of clinically important bleeding (≤4%). The panel identified risk categories based on evidence, with variable certainty regarding risk factors. The panel suggests using a PPI rather than a H2RA (weak recommendation) and recommends against using sucralfate (strong recommendation). HOW THIS GUIDELINE WAS CREATED: A guideline panel including patients, clinicians, and methodologists produced these recommendations using standards for trustworthy guidelines and the GRADE approach. The recommendations are based on a linked systematic review and network meta-analysis. A weak recommendation means that both options are reasonable. THE EVIDENCE: The linked systematic review and network meta-analysis estimated the benefit and harm of these medications in 12 660 critically ill patients in 72 trials. Both PPIs and H2RAs reduce the risk of clinically important bleeding. The effect is larger in patients at higher bleeding risk (those with a coagulopathy, chronic liver disease, or receiving mechanical ventilation but not enteral nutrition or two or more of mechanical ventilation with enteral nutrition, acute kidney injury, sepsis, and shock) (moderate certainty). PPIs and H2RAs might increase the risk of pneumonia (low certainty). They probably do not have an effect on mortality (moderate certainty), length of hospital stay, or any other important outcomes. PPIs probably reduce the risk of bleeding more than H2RAs (moderate certainty). UNDERSTANDING THE RECOMMENDATION: In most critically ill patients, the reduction in clinically important gastrointestinal bleeding from gastric acid suppressants is closely balanced with the possibility of pneumonia. Clinicians should consider individual patient values, risk of bleeding, and other factors such as medication availability when deciding whether to use gastrointestinal bleeding prophylaxis. Visual overviews provide the relative and absolute benefits and harms of the options in multilayered evidence summaries and decision aids available on MAGICapp.

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 imitation

Not 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.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.101
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.101
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0050.005
Science and technology studies0.0020.002
Scholarly communication0.0050.006
Open science0.0080.004
Research integrity0.0200.018
Insufficient payload (model declined to judge)0.0070.008

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.

Opus teacher head0.066
GPT teacher head0.420
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

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Citations142
Published2020
Admission routes1
Has abstractyes

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