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Record W2918961688 · doi:10.1183/20734735.0346-2018

Under- and over-diagnosis of COPD: a global perspective

2019· review· en· W2918961688 on OpenAlexaff
Terence Ho, Ruth P. Cusack, Nagendra Chaudhary, Imran Satia, Om Kurmi

Bibliographic record

VenueBreathe · 2019
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsPopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsPerspective (graphical)COPDComputer scienceMedicineArtificial intelligenceInternal medicine

Abstract

fetched live from OpenAlex

Globally, chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity and projected to rise to third within a decade as our efforts to prevent, identify, diagnose and treat patients at a global population level have been insufficient. The European Respiratory Society and American Thoracic Society, along with the Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy document, have highlighted key pathological risk factors and suggested clinical treatment strategies in order to reduce the mortality and morbidity associated with COPD. This review focuses solely on issues related to the under- and over-diagnosis of COPD across the main geographical regions of the world and highlights some of the associated risk factors. Prevalence of COPD obtained mainly from epidemiological studies varies greatly depending on the clinical and spirometric criteria used to diagnose COPD, i.e. forced expiratory volume in 1 s to forced vital capacity ratio <0.7 or 5% below the lower limit of normal, and this subsequently affects the rates of under- and over-diagnosis. Although under-utilisation of spirometry is the major reason, additional factors such as exposure to airborne pollutants, educational level, age of patients and language barriers have been widely identified as other potential risk factors. Co-existent diseases, such as asthma, bronchiectasis, heart failure and previously treated tuberculosis, are reported to be the other determinants of under- and over-diagnosis of COPD. Key points Globally, there is large variation in the prevalence of COPD, with 10–95% under-diagnosis and 5–60% over-diagnosis (table 1) due to differences in the definition of diagnosis used, and the unavailability of spirometry in rural areas of low- and middle-income countries where the prevalence of COPD is likely to be high. In order to be diagnosed with COPD, patients must have a combination of symptoms with irreversible airflow obstruction defined by a post-bronchodilator FEV 1 /FVC ratio of <0.7 or below the fifth centile of the lower limit of normal (LLN), and with a history of significant exposure to a risk factor. Repeat spirometry is recommended if the ratio is between 0.6 and 0.8. Not performing spirometry is the strongest predictor for an incorrect diagnosis of COPD; however, additional factors, such as age, gender, ethnicity, self-perception of symptoms, co-existent asthma, and educational awareness of risk factor by patients and their physician, are also important. COPD can be associated with inhalation of noxious particles other than smoking tobacco. Educational aims To summarise the global prevalence of over- and under-diagnosis of COPD. To highlight the risk factors associated with the under- and over-diagnosis of COPD. To update readers on the key changes in the recent progress made regarding the correct diagnosis of COPD.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0010.000

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 head0.063
GPT teacher head0.396
Teacher spread0.333 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations205
Published2019
Admission routes1
Has abstractyes

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