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Record W2996234883 · doi:10.1371/journal.pone.0226672

External validation of clinical prediction rules for complications and mortality following Clostridioides difficile infection

2019· review· en· W2996234883 on OpenAlexaff
Catherine Beauregard-Paultre, Claire Nour Abou Chakra, Allison McGeer, Annie‐Claude Labbé, Andrew E. Simor, Wayne L. Gold, Matthew Muller, Jeff Powis, Kevin Katz, Suzanne M. Cadarette, Louis Valiquette

Bibliographic record

VenuePLoS ONE · 2019
Typereview
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsCentre Hospitalier Universitaire de SherbrookePublic Health OntarioSunnybrook Health Science CentreSt. Michael's HospitalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-MontréalNorth York General HospitalHealth Sciences CentreMount Sinai HospitalUniversité de SherbrookeUniversity of TorontoToronto East General HospitalToronto General Hospital
Fundersnot available
KeywordsMedicineInternal medicineProspective cohort studyCohortClostridioidesWhite blood cellPredictive value of testsCohort study

Abstract

fetched live from OpenAlex

BACKGROUND: Several clinical prediction rules (CPRs) for complications and mortality of Clostridioides difficile infection (CDI) have been developed but only a few have gone through external validation, and none is widely recommended in clinical practice. METHODS: CPRs were identified through a systematic review. We included studies that predicted severe or complicated CDI (cCDI) and mortality, reported at least an internal validation step, and for which data were available with minimal modifications. Data from a multicenter prospective cohort of 1380 adults with confirmed CDI were used for external validation. In this cohort, cCDI occurred in 8% of the patients and 30-day all-cause mortality occurred in 12%. The performance of each tool was assessed using individual outcomes, with the same cut-offs and standard parameters. RESULTS: Seven CPRs were assessed. Three predictive scores for cCDI showed low sensitivity (25-61%) and positive predictive value (PPV; 9-31%), but moderate specificity (54-90%) and negative predictive value (NPV; 82-95%). One model [using age, white blood cell count (WBC), narcotic use, antacids use, and creatinine ratio > 1.5× the normal level as covariates] showed a probability of 25% of cCDI at the optimal cut-off point with 36% sensitivity and 84% specificity. Two scores for mortality had low sensitivity (4-55%) and PPV (25-31%), and moderate specificity (71-78%) and NPV (87-92%). One predictive model for 30-day all-cause mortality [Charlson comorbidity index, WBC, blood urea nitrogen (BUN), diagnosis in ICU, and delirium] showed an AUC-ROC of 0.74. All other CPRs showed lower AUC values (0.63-0.69). Errors in calibration ranged from 12%- 27%. CONCLUSIONS: Included CPRs showed moderate performance for clinical use in a large validation cohort with a majority of patients infected with ribotype 027 strains and a low rate of cCDI and mortality. These data show that better CPRs need to be developed and validated.

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)0.105
metaresearch head score (Gemma)0.247
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.105
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1050.247
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0100.007
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
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 head0.337
GPT teacher head0.449
Teacher spread0.112 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations9
Published2019
Admission routes1
Has abstractyes

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