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Record W2065548764 · doi:10.1097/inf.0000000000000411

Monocyte CD64 Does Not Enhance Neutrophil CD64 as a Diagnostic Marker in Neonatal Sepsis

2014· letter· en· W2065548764 on OpenAlexaff
Fangyong Li, Veronika Shabanova, Chao Wang, Henry M. Rinder, Vineet Bhandari

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2014
Typeletter
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsTrillium Therapeutics (Canada)
FundersNational Center for Research Resources
KeywordsCD64SepsisNeonatal sepsisMedicineReceiver operating characteristicArea under the curveGastroenterologyMonocyteInternal medicineImmunologyReceptor

Abstract

fetched live from OpenAlex

To The Editors: We were intrigued by the recent paper that suggested that monocyte CD64 (mCD64) could enhance the ability of neutrophil CD64 (nCD64) as a diagnostic marker for neonatal sepsis, when expressed as median m/n CD64 values.1 As part of our recent investigations into the role of nCD64 as a diagnostic marker for neonatal sepsis,2,3 we had also collected data on mCD64 measurements. Hence, we went back to analyze our mCD64 data to assess whether it would improve our diagnostic abilities. We had 919 episodes of sepsis evaluations with both nCD64 and mCD64 measurements available. Of these 919, 533 episodes were of early-onset sepsis, of which 2 were culture proven. Of 386 episodes of late-onset sepsis, 46 were culture proven. Hence, we had a total of 48 episodes of culture-proven sepsis available for analysis. As we have done previously,2,3 we generated area under the curve (AUC) for receiver operator characteristic curves using nCD64 and mCD64, controlling for birth weight as a predictor. We found similar values for the AUC 0.88 and 0.82 for nCD64 and mCD64, respectively. Combining the two, even when they were correlated, gave similar results; an AUC of 0.88. We also calculated the AUC using the m/nCD64 ratio and obtained a result of 0.83. This value was similar to that of mCD64 alone, but less than that of nCD64 alone. Next, we performed a simple correlation of nCD64 and mCD64, regardless of repeated measurements, and obtained an R = 0.75, P < 0.0001 (Fig. 1). We concluded that mCD64 appeared to have no additional value in predicting culture-proven neonatal sepsis compared with nCD64 measurements. Our results support reports by other investigators where the mCD64 performed on par or below that of nCD64 as a diagnostic marker for neonatal sepsis.4,5 We speculate the differences in our results, compared with the earlier study,1 could be because of the different methodology used for measuring and analyzing mCD64. Our monocyte and neutrophil CD64 values were generated using a different antibody and were derived using an additional isotype control-based index to control for nonspecific fluorescence, often a significant issue for quantitating monocyte surface marker fluorescence. In addition, the differences in the types of microorganisms (which could instigate variable response in the n and/or m CD64 expression) isolated from the neonates at these 2 sites could also be another potential reason for the discrepant results. Additional studies are required to assess the utility, if any, of mCD64 in addition to that of nCD64, in the diagnosis of neonatal sepsis.FIGURE 1: Simple correlation between neutrophil and mCD64, regardless of repeated measurements. R = 0.75; P < 0.0001.Fang-Yong Li, MPH Veronika Shabanova, MPH Yale Center for Analytical Sciences Chao Wang, BS Henry M. Rinder, MD Department of Laboratory Medicine Yale University School of Medicine Vineet Bhandari, MD, DM Division of Perinatal Medicine Department of Pediatrics Yale University School of Medicine New Haven, CT

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)0.052
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.052
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0040.001
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0030.002

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 head0.008
GPT teacher head0.254
Teacher spread0.247 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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