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Record W2811073408 · doi:10.4037/ajcc2018576

Derivation of a PIRO Score for Prediction of Mortality in Surgical Patients With Intra-Abdominal Sepsis

2018· article· en· W2811073408 on OpenAlex
Juan Gabriel Posadas-Calleja, Henry T. Stelfox, André Ferland, Danny J. Zuege, Daniel J. Niven, Luc Berthiaume, Christopher J. Doig

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Critical Care · 2018
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsCARE Canada
Fundersnot available
KeywordsMedicineSepsisSeptic shockOrgan dysfunctionInternal medicineLogistic regressionMortality rateIntensive careIntensive care medicineShock (circulatory)Receiver operating characteristicCohort study

Abstract

fetched live from OpenAlex

BACKGROUND: Mortality in patients with intra-abdominal sepsis remains high. Recognition and classification of patients with sepsis are challenging; about 70% of critical care specialists find the existing definitions confusing and not clinically useful. OBJECTIVE: To assess the usefulness of the predisposition, infection/injury, response, organ dysfunction (PIRO) concept in surgical intensive care patients with severe sepsis or septic shock due to an intra-abdominal source. METHODS: Data from 2005 through 2010 of a prospective observational cohort were reviewed retrospectively. RESULTS: < .001). CONCLUSION: The PIRO score is useful for predicting mortality in patients with surgically related intra-abdominal sepsis.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.369
Teacher spread0.313 · 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