Characteristics and outcomes of patients with culture negative septic shock compared with patients with culture positive septic shock: a retrospective cohort study
Bibliographic record
Abstract
Background: Reliable surveillance methods are indispensable for benchmarking of healthcare-associated infection rates.The National Healthcare Safety Network (NHSN) recently introduced surveillance of ventilator-associated events (VAE), including ventilator-associated conditions (VAC) [1].This new algorithm is amenable to automated implementation and strives for more consistent interpretation.We assess the feasibility and reliability of automated implementation.Materials and methods: Retrospective analysis of an ICU cohort with prospective assessment of ventilator-associated pneumonia (VAP) in two academic medical centers (January 2011 to June 2012).The algorithm was electronically implemented as specified by the NHSN using minuteto-minute ventilator data.Two minor modifications were developed to improve stability and comparability with manual surveillance (10th percentile and intermittent ventilation).Concordance was assessed between the algorithms and prospective surveillance.Attributable mortality of VAC was estimated by multivariable competing-risk survival analysis.Results: Two thousand and eighty patients contributed 2,296 episodes of mechanical ventilation (MV).VAC incidence was 10.0/1,000 MV days.Prospective surveillance identified 8 VAP cases/1,000 MV days.The original VAC algorithm detected 32% (38/115) of patients affected by VAP; positive predictive value was 25% (38/152).Using the 10th percentile identified the same number of VAC cases, but only 116 were identical.VAC incidence was 24.9/1,000 MV days with the intermittent ventilation modification.Concordance between the original algorithm and the modified versions was suboptimal.Estimates of attributable mortality varied by implementation: original VAC subdistribution hazard ratio (sdHR) = 4.33, 10th percentile sdHR = 6.26 and intermittent ventilation sdHR = 2.40.Conclusions: Concordance between manual VAP surveillance and the VAE algorithm was poor.Although electronic implementation of the VAE algorithm was feasible, small variations considerably altered the events detected and their effect on mortality.Using the current specifications, comparability across institutions using different electronic or manual implementations remains questionable.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".