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Record W4382918344 · doi:10.1097/ccm.0000000000005968

Reliability of Admission Procalcitonin Testing for Capturing Bacteremia Across the Sepsis Spectrum: Real-World Utilization and Performance Characteristics, 65 U.S. Hospitals, 2008–2017*

2023· article· en· W4382918344 on OpenAlexaff
Alexander Lawandi, Marissa Oshiro, Sarah Warner, Guoqing Diao, Jeffrey R. Strich, Ahmed Babiker, Chanu Rhee, Michael Klompas, Robert L. Danner, Sameer S. Kadri

Bibliographic record

VenueCritical Care Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsProcalcitoninMedicineSepsisBacteremiaInternal medicineIntensive care unitBlood cultureReceiver operating characteristicIntensive care medicineEmergency medicineAntibiotics

Abstract

fetched live from OpenAlex

OBJECTIVES: Serum procalcitonin is often ordered at admission for patients with suspected sepsis and bloodstream infections (BSIs), although its performance characteristics in this setting remain contested. This study aimed to evaluate use patterns and performance characteristics of procalcitonin-on-admission in patients with suspected BSI, with or without sepsis. DESIGN: Retrospective cohort study. SETTING: Cerner HealthFacts Database (2008-2017). PATIENTS: Adult inpatients (≥ 18 yr) who had blood cultures and procalcitonin drawn within 24 hours of admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Testing frequency of procalcitonin was determined. Sensitivity of procalcitonin-on-admission for detecting BSI due to different pathogens was calculated. Area under the receiver operating characteristic curve (AUC) was calculated to assess discrimination by procalcitonin-on-admission for BSI in patients with and without fever/hypothermia, ICU admission and sepsis defined by Centers for Disease Control and Prevention Adult Sepsis Event criteria. AUCs were compared using Wald test and p values were adjusted for multiple comparisons. At 65 procalcitonin-reporting hospitals, 74,958 of 739,130 patients (10.1%) who had admission blood cultures also had admission procalcitonin testing. Most patients (83%) who had admission day procalcitonin testing did not have a repeat procalcitonin test. Median procalcitonin varied considerably by pathogen, BSI source, and acute illness severity. At a greater than or equal to 0.5 ng/mL cutoff, sensitivity for BSI detection was 68.2% overall, ranging between 58.0% for enterococcal BSI without sepsis and 96.4% for pneumococcal sepsis. Procalcitonin-on-admission displayed moderate discrimination at best for overall BSI (AUC, 0.73; 95% CI, 0.72-0.73) and showed no additional utility in key subgroups. Empiric antibiotic use proportions were not different between blood culture sampled patients with a positive procalcitonin (39.7%) and negative procalcitonin (38.4%) at admission. CONCLUSIONS: At 65 study hospitals, procalcitonin-on-admission demonstrated poor sensitivity in ruling out BSI, moderate-to-poor discrimination for both bacteremic sepsis and occult BSI and did not appear to meaningfully alter empiric antibiotic usage. Diagnostic stewardship of procalcitonin-on-admission and risk assessment of admission procalcitonin-guided clinical decisions is warranted.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
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 head0.107
GPT teacher head0.399
Teacher spread0.292 · 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

Citations18
Published2023
Admission routes1
Has abstractyes

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