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Classifying Chronic Lower Respiratory Disease Events in Epidemiologic Cohort Studies

2016· article· en· W2337873308 on OpenAlexaff
Elizabeth C. Oelsner, Laura R. Loehr, Ashley G. Henderson, Kathleen M. Donohue, Paul Enright, Ravi Kalhan, Christian M. Lo Cascio, Andrew L. Ries, Neomi Shah, Benjamin M. Smith, Wayne D. Rosamond, R. Graham Barr

Bibliographic record

VenueAnnals of the American Thoracic Society · 2016
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill University
FundersNational Center for Advancing Translational SciencesNational Institute on Minority Health and Health DisparitiesNational Center for Research ResourcesUniversity of MiamiNational Institute on Deafness and Other Communication DisordersNational Institute of Diabetes and Digestive and Kidney DiseasesNorthwestern UniversityNational Heart, Lung, and Blood InstituteOffice of Dietary SupplementsNational Institutes of HealthSan Diego State UniversityCOPD FoundationNational Institute of Environmental Health Sciences
KeywordsMedicineEmergency departmentMedical recordSpirometryAsthmaPopulationEmergency medicineDiagnosis codeCohortIntensive care medicinePediatricsInternal medicine

Abstract

fetched live from OpenAlex

RATIONALE: One in 12 adults has chronic obstructive pulmonary disease or asthma. Acute exacerbations of these chronic lower respiratory diseases (CLRDs) are a major cause of morbidity and mortality. Valid approaches to classifying cases and exacerbations in the general population are needed to facilitate prevention research. OBJECTIVES: To assess the feasibility, reproducibility, and performance of a protocol to identify CLRD cases and exacerbations triggering emergency department (ED) visits or hospitalizations in cohorts of patients derived from general populations of adults. METHODS: A protocol was developed to classify CLRD cases and severe exacerbations on the basis of review of medical records. ED and inpatient medical records were ascertained prospectively in the Hispanic Community Health Study/Study of Latinos, and inpatient records were retrospectively identified by administrative codes in the Multi-Ethnic Study of Atherosclerosis. "Probable" exacerbations were defined as a physician's diagnosis of CLRD with acute respiratory symptoms. "Highly probable" exacerbations additionally required systemic corticosteroid therapy, and "definite" exacerbations required airflow limitation or evidence of CLRD on imaging studies. Adjudicated results were compared with CLRD cases identified by spirometry and self-report, and with an administrative definition of exacerbations. MEASUREMENTS AND MAIN RESULTS: Protocol-based classification was completed independently by two physicians for 216 medical records (56 ED visits and 61 hospitalizations in the Hispanic Community Health Study/Study of Latinos; 99 hospitalizations in the Multi-Ethnic Study of Atherosclerosis). Reviewer disagreement occurred in 2-5% of cases and 4-8% of exacerbations. Eighty-nine percent of records were confirmed as at least probable CLRD cases. Fifty-six percent of confirmed CLRD cases had airflow limitation on the basis of baseline study spirometry. Of records that described CLRD as the primary discharge diagnosis code, an acute exacerbation was confirmed as at least probable for 96% and as highly probable or definite for 77%. Only 50% of records with CLRD as a secondary code were confirmed, although such records accounted for over half of all confirmed exacerbations. CONCLUSIONS: CLRD cases and severe exacerbations without preceding documentation of airflow limitation are identified frequently in population-based cohorts of persons. A primary discharge diagnosis of CLRD is specific but insensitive for defining exacerbations. Protocol-based classification of medical records may be appropriate to supplement and to validate identification of CLRD cases and exacerbations in general population studies. Clinical trials registered with www.clinicaltrials.gov (NCT00005487 and NCT02060344).

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)0.176
metaresearch head score (Gemma)0.257
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 score0.176
Threshold uncertainty score0.930

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1760.257
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0110.008
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.187
GPT teacher head0.468
Teacher spread0.281 · 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

Citations32
Published2016
Admission routes1
Has abstractyes

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