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Record W1567446245 · doi:10.1186/1471-2431-6-28

Screening for hypoglycemia at the bedside in the neonatal intensive care unit (NICU) with the Abbott PCx glucose meter

2006· article· en· W1567446245 on OpenAlexaff
Cynthia Balion, Vijaylaxmi Grey, Afisi Ismaila, Susan Blatz, Wendy Seidlitz

Bibliographic record

VenueBMC Pediatrics · 2006
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsMcMaster UniversityHamilton Health Sciences
FundersAbbott Diagnostics
KeywordsMedicineHypoglycemiaGlucose meterHematocritNeonatal intensive care unitNeonatal hypoglycemiaEmergency medicinePediatricsInternal medicineDiabetes mellitusEndocrinologyInsulinGestation

Abstract

fetched live from OpenAlex

BACKGROUND: Point of care (POC) glucose meters are routinely used as a screening tool for hypoglycemia in a neonatal setting. Glucose meters however, lack the same accuracy as laboratory instruments for glucose measurement. In this study we investigated potential reasons for this inaccuracy and established a cut off value for confirmatory testing. METHODS: In this prospective study, all patients in the neonatal intensive care unit who had a plasma glucose test ordered were eligible to participate. Demographic information, sample collection information (nine variables) and a recent hematocrit value were recorded for each sample. Glucose measurements were taken at the bedside on the glucose meter (RN PCx) as well as in the laboratory on both the glucose meter (LAB PCx) and the laboratory analyzer (PG). Data were analyzed by simple and mixed-effects regression analysis and by analysis of a receiver operator characteristics (ROC) curve. RESULTS: There were 475 samples analyzed from 132 patients. RN PCx values were higher than PG values (mean = 4.9%), while LAB PCx results were lower (mean = -5.2%) than PG values. Only 31% of the difference between RN PCx--PG and 46% of the difference for LAB PCx--PG could be accounted for by the variables tested. The largest proportion of variance between PCx and PG measurements was explained by hematocrit (about 30%) with a greater effect seen at glucose concentrations < or =4.0 mmol/L (< or =72 mg/dL)(48% and 40% for RN PCx and LAB PCx, respectively). The ROC analysis showed that for detection of all cases of hypoglycemia (PG < 2.6 mmol/L)(PG < 47 mg/dL) the PCx screening cut off value would need to be set at 3.8 mmol/L (68 mg/dL) requiring 20% of all samples to have confirmatory analysis by the laboratory method. CONCLUSION: The large difference between glucose results obtained by PCx glucose meter compared to the laboratory analyzer can be explained in part by hematocrit and low glucose concentration. These results emphasize that the glucose meter is useful only as a screening device for neonatal hypoglycemia and that a screening cut off value must be established.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.026
GPT teacher head0.280
Teacher spread0.254 · 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

Citations45
Published2006
Admission routes1
Has abstractyes

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