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Record W2175642127 · doi:10.7326/m15-1150

Accuracy of Peripheral Thermometers for Estimating Temperature

2015· article· en· W2175642127 on OpenAlexaff
Daniel J. Niven, Jonathan Gaudet, Kevin B. Laupland, Kelly Mrklas, Derek J. Roberts, Henry T. Stelfox

Bibliographic record

VenueAnnals of Internal Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsMedicineMeta-analysisPulmonary artery catheterConfidence intervalProspective cohort studyInternal medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Body temperature is commonly used to screen patients for infectious diseases, establish diagnoses, monitor therapy, and guide management decisions. PURPOSE: To determine the accuracy of peripheral thermometers for estimating core body temperature in adults and children. DATA SOURCES: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and CINAHL Plus from inception to July 2015. STUDY SELECTION: Prospective studies comparing the accuracy of peripheral (tympanic membrane, temporal artery, axillary, or oral) thermometers with central (pulmonary artery catheter, urinary bladder, esophageal, or rectal) thermometers. DATA EXTRACTION: 2 reviewers extracted data on study characteristics, methods, and outcomes and assessed the quality of individual studies. DATA SYNTHESIS: 75 studies (8682 patients) were included. Most studies were at high or unclear risk of patient selection bias (74%) or index test bias (67%). Compared with central thermometers, peripheral thermometers had pooled 95% limits of agreement (random-effects meta-analysis) outside the predefined clinically acceptable range (± 0.5 °C), especially among patients with fever (-1.44 °C to 1.46 °C for adults; -1.49 °C to 0.43 °C for children) and hypothermia (-2.07 °C to 1.90 °C for adults; no data for children). For detection of fever (bivariate random-effects meta-analysis), sensitivity was low (64% [95% CI, 55% to 72%]; I2 = 95.7%; P < 0.001) but specificity was high (96% [CI, 93% to 97%]; I2 = 96.3%; P < 0.001). Only 1 study reported sensitivity and specificity for the detection of hypothermia. LIMITATIONS: High-quality data for some temperature measurement techniques are limited. Pooled data are associated with interstudy heterogeneity that is not fully explained by stratified and metaregression analyses. CONCLUSION: Peripheral thermometers do not have clinically acceptable accuracy and should not be used when accurate measurement of body temperature will influence clinical decisions. PRIMARY FUNDING SOURCE: None.

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)0.084
metaresearch head score (Gemma)0.319
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 score0.084
Threshold uncertainty score0.447

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.319
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.014
Bibliometrics0.0050.005
Science and technology studies0.0010.002
Scholarly communication0.0060.004
Open science0.0030.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.093
GPT teacher head0.409
Teacher spread0.316 · 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

Citations235
Published2015
Admission routes1
Has abstractyes

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