Management of adult sepsis in resource-limited settings: global expert consensus statements using a Delphi method
Bibliographic record
Abstract
PURPOSE: To generate consensus and provide expert clinical practice statements for the management of adult sepsis in resource-limited settings. METHODS: An international multidisciplinary Steering Committee with expertise in sepsis management and including a Delphi methodologist was convened by the Asia Pacific Sepsis Alliance (APSA). The committee selected an international panel of clinicians and researchers with expertise in sepsis management. A Delphi process based on an iterative approach was used to obtain the final consensus statements. RESULTS: A stable consensus was achieved for 30 (94%) of the statements by 41 experts after four survey rounds. These include consensus on managing patients with sepsis outside a designated critical care area, triggers for escalating clinical management and criteria for safe transfer to another facility. The experts agreed on the following: in the absence of serum lactate, clinical parameters such as altered mental status, capillary refill time and urine output may be used to guide resuscitation; special considerations regarding the volume of fluid used for resuscitation, especially in tropical infections, including the use of simple tests to assess fluid responsiveness when facilities for advanced hemodynamic monitoring are limited; use of Ringer's lactate or Hartmann's solution as balanced salt solutions; epinephrine when norepinephrine or vasopressin are unavailable; and the administration of vasopressors via a peripheral vein if central venous access is unavailable or not feasible. Similarly, where facilities for investigation are unavailable, there was consensus for empirical antimicrobial administration without delay when sepsis was strongly suspected, as was the empirical use of antiparasitic agents in patients with suspicion of parasitic infections. CONCLUSION: Using a Delphi method, international experts reached consensus to generate expert clinical practice statements providing guidance to clinicians worldwide on the management of sepsis in resource-limited settings. These statements complement existing guidelines where evidence is lacking and add relevant aspects of sepsis management that are not addressed by current international guidelines. Future studies are needed to assess the effects of these practice statements and address remaining uncertainties.
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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 | 0.226 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".