Mise en place de l’oncologie gériatrique dans un hôpital isolé de Guyane française
Bibliographic record
Abstract
L’objectif était d’analyser l’implantation du modèle de l’oncogériatrie dans un territoire isolé ultramarin : l’Ouest guyanais. La population est socialement précaire sur les plans des revenus, de la couverture sociale, du statut administratif, le plus souvent de langue non française et de culture non occidentale. Description narrative de l’implantation et étude rétrospective des données anonymisées de la base de données des patients âgés pris en charge entre septembre 2014 et décembre 2020. Au total, 574 nouveaux patients ont été pris en charge. Parmi eux, 107 étaient âgés de 70 ans et plus ; 78 (73 %) ont eu un test G8. Quarante-deux patients ont eu une évaluation gériatrique multidimensionnelle. Plus de la moitié des patients présentaient des critères de dépendance, de malnutrition, avec un nombre de comorbidités sévères élevé. Les difficultés rencontrées ont été : la langue, le niveau d’éducation, le contexte clinique (chez dix-huit patients), mais aussi la participation insuffisante des soignants et les conséquences de l’organisation sanitaire et d’une implantation progressive. L’implantation a été impactée par le fait que les critères de qualité d’une mise en œuvre n’ont pas été suffisants. Des études, menées dans les pays à revenu moyen-haut d’Amérique du Sud, suggèrent que la réalisation initiale de l’évaluation gériatrique multidimensionnelle peut être préférable, que les tests de dépistage de la fragilité et la procédure de l’évaluation gériatrique multidimensionnelle peuvent être adaptés à des populations non occidentales, que l’utilisation de nouvelles technologies peut améliorer la prise en charge des patients âgés dans ce contexte. The aim was to analyze the implementation of the Onco-Geriatrics model in a remote ultramarine territory: West-French Guiana. The population is socially precarious in terms of income, social coverage and administrative status, and most often speaks a non-French language and has a non-Western culture. Narrative description of the implementation and retrospective study of anonymized data from the database of older patients managed for cancer between September 2014 and December 2020. A total of 574 new patients were managed. Of these, 107 were aged 70 and over; 78 (73 %) had a G8 test. Forty-two patients had a multidimensional geriatric assessment (MGA). More than half the patients had dependency criteria, malnutrition and a high number of severe comorbidities. Difficulties encountered were language, level of education, clinical context (in 18 patients), but also insufficient involvement of health professional and the consequences of health organization and gradual implementation. Implementation was impacted by the fact that quality criteria for implementation were not sufficient. Studies in high-middle-income countries in South America suggest that initial implementation of the MGA may be preferable, that frailty screening tests and the MGA procedure can be adapted to non-Western populations, and that the use of new technologies can improve the management of older patients in this context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".