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Record W3197490484 · doi:10.1080/16078454.2021.1966223

Patient vital signs in relation to ICU admission in treatment of acute leukemia: a retrospective chart review

2021· article· en· W3197490484 on OpenAlexafffund
Katharine McLaughlin, Amanda Stojcevski, Abdulkadir Hussein, Devinder Moudgil, Indryas Woldie, Caroline Hamm

Bibliographic record

VenueHematology · 2021
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsWindsor Regional HospitalUniversity of WindsorWestern University
FundersSchulich School of Medicine and DentistryWestern University
KeywordsMedicineVital signsIntensive care unitAcute leukemiaFraction of inspired oxygenInduction chemotherapyRetrospective cohort studyRespiratory rateAnesthesiaIntensive care medicineChemotherapyLeukemiaInternal medicineMechanical ventilationHeart rateBlood pressure

Abstract

fetched live from OpenAlex

OBJECTIVES: The objective of the current study was to investigate the relationship between changes in vital signs and intensive care unit (ICU) admission. Windsor Regional Hospital treats 15-20 new patients a year with acute leukemia. These patients are at increased risk of neutropenic fevers and admission to the ICU following induction chemotherapy. METHODS: ) required to maintain a stable oxygen saturation. RESULTS: and HR were significantly higher in the ICU group at time zero compared with the control group. RR was recorded least frequently in the 24 hours leading up to ICU admission. DISCUSSION: predicted clinical deterioration requiring ICU admission in acute leukemia patients. This is consistent with the predominant reason for ICU admission which was respiratory failure. CONCLUSION: in acute leukemia patients following induction chemotherapy with early intervention if identified.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.315
Teacher spread0.297 · 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 teacher head, 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

Citations5
Published2021
Admission routes2
Has abstractyes

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