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Record W2910997829 · doi:10.3399/bjgp19x700805

Continuity of care in general practice at cancer diagnosis (COOC-GP study): a national cohort study of 2853 patients

2019· article· en· W2910997829 on OpenAlexaff
Aline Hurtaud, Michèle Aubin, Émilie Ferrat, Julien Lebreton, Éléna Paillaud, Étienne Audureau, Sylvie Bastuji‐Garin, C. Chouaïd, Philippe Boisnault, Pascal Clerc, Florence Canouï‐Poitrine

Bibliographic record

VenueBritish Journal of General Practice · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineProspective cohort studyCancerCohortConfidence intervalCancer registryCohort studyComorbidityPediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: At cancer diagnosis, it is unclear whether continuity of care (COC) between the patient and GP is safeguarded. AIM: To identify patient-GP loss of COC around the time of, and in the year after, a cancer diagnosis, together with its determinants. DESIGN AND SETTING: A post-hoc analysis of data from a prospective cohort of GPs in France, taken from a survey by the Observatoire de la Médecine Générale. METHOD: = 96) filed data on patients who were diagnosed with incident cancer between 1 January 2000 and 31 December 2010. COC was assessed by ascertaining the frequency of consultations and the maximal interval between them. (In France, patients see their referring/named GP in most cases.) A loss of COC was measured during the trimester before and the year after the cancer diagnosis, and the results compared with those from a 1-year baseline period before cancer had been diagnosed. A loss of COC was defined as a longer interval (that is, the maximum number of days) between consultations in the measurement periods than at baseline. Determinants of the loss in COC were assessed with univariate and multivariate logistic regression models. RESULTS: In total, 2853 patients were included; the mean age was 66.1 years. Of these, 1440 (50.5%) were women, 389 (13.6%) had metastatic cancer, and 769 (27.0%) had a comorbidity. The mean number of consultations increased up to, and including, the first trimester after diagnosis. Overall, 26.9% (95% confidence interval [CI] = 25.3 to 28.6) of patients had a loss of COC in the trimester before the diagnosis, and 22.3% (95% CI = 20.7 to 23.9) in the year after. Increasing comorbidity score was independently associated with a reduction in the loss of COC during the year after diagnosis (adjusted odds ratio [OR] comorbidity versus no comorbidity 0.61, 95% CI = 0.48 to 0.79); the same was true for metastatic status (adjusted OR metastasis versus no metastasis 0.49, 95% CI = 0.35 to 0.70). CONCLUSION: As COC is a core value for GPs and for most patients, special care should be taken to prevent a loss of COC around the time of a cancer diagnosis, and in the year after.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
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 head0.031
GPT teacher head0.439
Teacher spread0.408 · 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".

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Citations13
Published2019
Admission routes1
Has abstractyes

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