Hypothyroïdie grave associée à la prise prophylactique de chloroquine chez une patiente traitée avec la lévothyroxine
Bibliographic record
Abstract
Resume Objectif : Presenter le cas d’une interaction medicamenteuse suspectee entre la chloroquine et la levothyroxine et determiner la conduite a suivre au moment d’un tel evenement. Resume du cas : Cet article rapporte le cas d’une femme de 51 ans, souffrant depuis plusieurs annees d’hypothyroidie stabilisee a une dose de 300 mcg de levothyroxine, s’etant presentee avec un taux de TSH eleve a l’urgence au retour d’un voyage en Republique dominicaine. Le taux de TSH est revenu a la normale a la fin du traitement prophylactique de la malaria a la chloroquine et a l’aide d’un court traitement a la liothyronine. Discussion : De nombreux medicaments sont repertories comme pouvant interagir avec la levothyroxine. Un seul cas d’interaction entre la chloroquine et la levothyroxine a ete recense, bien qu’une etude effectuee sur l’animal ait demontre que la chloroquine pouvait diminuer la conversion peripherique de tetra-iodothyronine (T4) en triiodothyronine (T3) et pouvait egalement augmenter la TSH lorsqu’elle est combinee avec le methimazole. De nombreuses personnes utilisent la chloroquine pendant de courtes periodes seulement, ce qui fait que les interactions avec ce produit peuvent etre sousestimees. Le patient utilisant ces deux produits de maniere concomitante devrait etre averti de surveiller les symptomes d’hypothyroidie. Conclusion : L’interaction entre la chloroquine et la levothyroxine n’est pas rapportee comme frequente dans la litterature medicale. Cependant, cette interaction peut augmenter de facon importante les symptomes d’hypothyroidie. Compte tenu des consequences sur la qualite de vie des patients, il est important pour les cliniciens de savoir reconnaitre et traiter cette reaction. Abstract Objective: To present a practical approach for continuing education in hospitals and related healthcare settings. Context: Concern for safe delivery of health care stems mainly from the scientific literature on drugrelated errors and from appreciation of the inherent risks to the medication use and medication management process. Pharmacists and pharmacy technical assistants should actively participate in updating their skills. Results: We introduce a profile of the various approaches to personnel training (i.e., participants, technological support, time, feedback, procedure, strategies, production tools and distribution, examples). Using the Camtasia Studio software, we developed an approach to content production/distribution, and have created some 20 Web productions 5–12 minutes in length, involving about 20 hours of work per production, all of it done by students. Discussion: Video production is a task that can be delegated to pharmacy students, in collaboration with pharmacists as content experts in order to effectively target the content and structuring of key messages; and to develop, complete, and evaluate the production scenario. We think that this approach is more realistic than the videos provided by external organizations, of which production costs are estimated to be tens of thousands of dollars. Conclusion: This pilot study demonstrates the feasibility of a practical approach using online videos for the continuing education of healthcare professionals. A low-cost way to produce videos was achieved. Key words: continuing education, video
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".