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Record W2811264850 · doi:10.1097/pcc.0000000000001598

Mortality Risk Using a Pediatric Quick Sequential (Sepsis-Related) Organ Failure Assessment Varies With Vital Sign Thresholds*

2018· article· en· W2811264850 on OpenAlexaffabout
Cheryl Peters, Srinivas Murthy, Rollin Brant, Niranjan Kissoon, Matthias Görges

Bibliographic record

VenuePediatric Critical Care Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsSunny Hill Health Centre for ChildrenBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineSign (mathematics)SepsisIntensive care medicineRisk assessmentVital signsEmergency medicineMedical emergencyInternal medicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: We evaluated adapting the quick Sequential (Sepsis-Related) Organ Failure Assessment score (fast respiratory rate, altered mental status, low blood pressure) for pediatric use by selecting thresholds from three commonly used definitions: Pediatric Logistic Organ Dysfunction 2, Pediatric Advanced Life Support, and International Pediatric Sepsis Consensus Conference. We examined their respective performance in identifying children who had a discharge diagnosis of infection at high risk of mortality using PICU registry data, with additional focus on the influence of age on performance. DESIGN: Analysis of retrospective data obtained from the Virtual Pediatric Systems PICU database. The performance in predicting observed mortality was assessed for the three candidate approaches using receiver operating characteristics analysis, including age group effects. SETTING: The Virtual Pediatric Systems database contains data on diagnosis, clinical markers, and outcomes in prospectively collected clinical records from 130 participating PICUs in the United States and Canada. PATIENTS: Children who had a discharge diagnosis of infection in a participating PICU between 2009 and 2014, for which all required data were available. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data from 40,228 children revealed an overall mortality of 4.22%. Area under the receiver operating characteristics curve (95% CI) was 0.760 (0.749-0.771) for Pediatric Logistic Organ Dysfunction 2 with mechanical ventilation, 0.700 (0.689-0.712) for Pediatric Advanced Life Support, and 0.709 (0.696-0.721) for International Pediatric Sepsis Consensus Conference. When split by age group, the performance of Pediatric Logistic Organ Dysfunction 2 with mechanical ventilation was lowest in the youngest neonates (under 1 wk old), with an area under the receiver operating characteristics curve (95% CI) of 0.724 (0.656-0.791), and in the teenagers (13-18 yr), with an area under the receiver operating characteristics curve of 0.710 (0.682-0.738), yet it still outperformed Pediatric Advanced Life Support and International Pediatric Sepsis Consensus Conference in both groups. CONCLUSIONS: Among critically ill children who had a discharge diagnosis of infection in the PICU, quick Sequential (Sepsis-Related) Organ Failure Assessment score performs best when using the Pediatric Logistic Organ Dysfunction 2 age thresholds with mechanical ventilation, while all definitions performed worse at extremes of pediatric age. Thus, mortality risk varies with vital sign thresholds, and although Pediatric Logistic Organ Dysfunction 2 with mechanical ventilation performed marginally better, it is unlikely to be of use to clinicians. More work is needed to develop a robust and relevant pediatric sepsis risk score.

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)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.389
Teacher spread0.327 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2018
Admission routes2
Has abstractyes

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