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Record W4280524177 · doi:10.1542/peds.2021-056028

Guideline-Based Risk Stratification for Febrile Young Infants Without Procalcitonin Measurement

2022· article· en· W4280524177 on OpenAlexaff
Brett Burstein, Nawal Alathari, Jesse Papenburg

Bibliographic record

VenuePEDIATRICS · 2022
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsMcGill University Health CentreMontreal Children's HospitalMcGill University
Fundersnot available
KeywordsMedicineProcalcitoninGuidelineRisk stratificationStratification (seeds)Internal medicineIntensive care medicinePediatricsPathologySepsis

Abstract

fetched live from OpenAlex

Modern risk-stratification strategies have been derived to identify infants at low risk of serious bacterial infections (SBIs; urinary tract infections, bacteremia, and bacterial meningitis) and invasive bacterial infections (IBIs; bacteremia and bacterial meningitis).1–3 These incorporate different diagnostic tests and low-risk cut-points. Procalcitonin testing offers the best discrimination of low-risk infants4; however, this test is not universally available.5,6 Recent guidelines from the American Academy of Pediatrics (AAP) recommend that if procalcitonin is unavailable, C-reactive protein (CRP), absolute neutrophil count (ANC), and temperature should be used5; however, these inflammatory markers have never been evaluated together in combination. This study sought to estimate the diagnostic accuracy of CRP, ANC, and temperature at AAP-recommended cut-points, prioritizing not missing IBIs.This was a secondary analysis of quality improvement data collected prospectively to standardize diagnostic testing for febrile infants ≤60 days of age at an urban tertiary pediatric emergency department between January 2018 and October 2021. All infants had blood and urine cultures, whereas cerebrospinal fluid testing was at the discretion of the treating physician. SBIs and IBIs were classified according to current definitions.5 Final SBI/IBI status was ascertained for all infants by chart review and by telephone follow-up 14 to 28 days postdischarge for those without cerebrospinal fluid testing. This was a complete-case analysis of all previously healthy, term-born infants, 8 to 60 days old meeting AAP inclusion/exclusion criteria,5 and for whom CRP, ANC, and temperature data were available. The primary outcome was accuracy for detecting IBIs (sensitivity and negative predictive value [NPV]). Infants with CRP ≤20.0 mg/L, ANC ≤5200/mm3, and a maximum home or emergency department rectal temperature ≤38.5°C were classified as low-risk.5 AAP guidelines define abnormal ANC as “>4000, >5200/mm3”; ≤5200/mm3 was selected for the primary analysis as this threshold was derived without procalcitonin,2 and sensitivity analyses were conducted by using a cut-point of ≤4000/mm3. This study received institutional research ethics board approval and followed the 2015 Standards for Reporting of Diagnostic Accuracy guidelines.There were 957 of 1041 infants (91.9%) meeting inclusion with complete data (Table 1); 779 of 957 were >21 days old (81.4%), 27 of 957 had IBIs (2.8%), and 164 of 957 had SBIs (17.1%). Among infants with IBIs, 22 had bacteremia and 5 had bacteremia with meningitis. Test characteristics using AAP criteria are summarized in Table 2. AAP-recommended cut-points of ANC/CRP/temperature classified 431 infants (45.0%) as low risk. In the full cohort, there were no cases of IBI misclassified as low risk (0 of 27); sensitivity for identifying IBI was 100.0% (95% confidence interval [CI] 87.2–100.0) and NPV was 100.0% (95% CI 99.2–100.0). A threshold of ANC ≤4000/mm3 (Supplemental Table 3) classified 373 infants (39.0%) as low risk, maintaining high sensitivity (100.0%; 95% CI 87.2–100.0) and NPV (100.0%; 95% CI 99.0–100.0) for IBI. Among all infants, sensitivity and NPV for SBI were 83.5% and 93.7%; 27 infants with positive urine culture results were classified as low risk, among whom 18 of 27 (66.7%) had a positive urinalysis result.This is the first assessment of recent AAP guidelines for risk-stratifying febrile young infants when procalcitonin is unavailable. The AAP-recommended combination of CRP, ANC, and maximal temperature resulted in 0 misclassified IBIs in a cohort of nearly 1000 well-appearing febrile infants 8 to 60 days old, yielding sensitivity and NPV of 100%. Overall, there were 526 of 957 infants who did not meet ANC/CRP/temperature low-risk criteria. However, applying AAP guidelines could reduce lumbar punctures, hospitalizations, and antibiotic exposure for nearly half (364 of 779) of all infants as young as 22 days. Findings suggest that clinicians without access to procalcitonin testing may safely follow AAP guidelines to assess the risk of IBI using these readily available, inexpensive inflammatory markers.Although accuracy was lower for identifying SBIs, recent efforts have prioritized identifying infants at risk for IBI. Most SBIs among febrile infants are urinary tract infections,7 which are less dangerous and identified with high sensitivity/specificity by urinalysis results.8,9 AAP guidelines consider inflammatory markers independently from urinalysis results.5 Infants with isolated urinary tract infections and low-risk inflammatory markers would have been identified by urinalysis in 18 of 27 cases. Nine were included as misclassified SBIs because their urine culture grew >50 000 colony-forming units of a uropathogen and they were managed clinically as UTIs9; however, even these more likely represented asymptomatic bacteriuria or contamination.5This study has limitations. This was a single-center study and the results may not be generalizable to other settings. Systematic CRP testing began in October 2019; consequently, complete data were not available for all eligible infants. Infants may have had higher unrecorded temperatures; however, this would lower specificity without affecting sensitivity. Only 27 infants had IBIs; however, the study cohort was similarly large compared with recent large prospective cohorts used to derive clinical prediction rules.1,3 AAP-recommended thresholds of CRP and ANC were used, although different cut-points may improve performance.10 Also, the analysis was limited to infants meeting all low-risk criteria and did not assess test characteristics when inflammatory markers were discordant.The authors thank Alexandra Yannopoulos and Emma Bainbridge for technical assistance, and Xun Zhang for statistical support.

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)0.008
metaresearch head score (Gemma)0.026
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 score0.016
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.102
GPT teacher head0.351
Teacher spread0.249 · 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".

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Citations26
Published2022
Admission routes1
Has abstractyes

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