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Record W4398131747 · doi:10.2196/44397

Predictive Value of Physiological Values and Symptom Scores for Exacerbations in Bronchiectasis and Chronic Obstructive Pulmonary Disease With Frequent Exacerbations: Longitudinal Observational Cohort Study

2024· article· en· W4398131747 on OpenAlexvenueno aff
Thomas Jones, Claire Roberts, Scott Elliott, Sharon Glaysher, Ben Green, Janis K. Shute, Anoop Chauhan

Bibliographic record

VenueInteractive Journal of Medical Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
Fundersnot available
KeywordsBronchiectasisMedicinePulmonary diseaseObservational studyCohortPredictive valueInternal medicineIntensive care medicineDiseaseCOPDCohort studyValue (mathematics)Physical therapyLungStatisticsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: COPD (chronic obstructive pulmonary disease) and bronchiectasis are common, and exacerbations contribute to their morbidity and mortality. Predictive factors for the frequency of future exacerbations include previous exacerbation frequency and airway colonization. Earlier treatment of exacerbations is likely to reduce severity. OBJECTIVE: This study tested the hypothesis that, in a population with bronchiectasis, COPD, or both who have frequent exacerbations and airway colonization, changes in symptom scores or physiological variables within 10 days prior to an exacerbation would allow the prediction of the event. METHODS: We performed a 6-month, longitudinal, observational, cohort study among 30 participants with bronchiectasis, COPD, or both; at least 2 exacerbations per year; and colonization with Pseudomonas aeruginosa or Haemophilus influenzae. Daily symptom and physiological data were collected, comprising pulse rate, blood pressure, oxygen saturation, peak flow rate, step count, weight, and temperature. Exacerbations (defined as the onset of new antibiotic use for respiratory symptoms) were collected, and predictive values for abnormal values in the 10 days prior to an exacerbation were calculated. RESULTS: A total of 30 participants were recruited, collecting a total of 39,534 physiological and 25,334 symptom data points across 5358 participant-days; these included 78 exacerbations across 27 participants, with the remaining 3 participants not having exacerbations within the 6-month observation period. Peak flow rate, oxygen saturation, and weight were significantly different at the point of exacerbation (all P<.001), but no significant trends around exacerbation were noted and no clinically beneficial predictive value was found in the overall or individually adjusted model. Symptom scores tended to worsen for 10 days on either side of an exacerbation but were of insufficient magnitude for prediction, with area under the receiver operating characteristic curve values of ranging from 0.4 to 0.6. CONCLUSIONS: Within this small cohort with bronchiectasis, COPD, or both and airway colonization, physiological and symptom variables did not show sufficient predictive value for exacerbations to be of clinical utility. The self-management education provided as standard of care may be superior to either of these approaches, but benefit in another or larger cohort cannot be excluded. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.6636.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.062
GPT teacher head0.427
Teacher spread0.365 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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