Notice bibliographique
Résumé
The objective of this thesis was to use health administrative data to investigate two important adverse drug reactions (ADRs) related to renal function. The first study examined the risk of hyperkalemia associated with the antibiotic trimethoprim-sulfamethoxazole (TMP-SMX) and its interaction with beta-adrenergic receptor blockers (“beta blockers”). The second study evaluated the effect of impaired kidney function on the risk of hypoglycemia conferred by the anti-diabetic drug glyburide. The simultaneous use of beta adrenergic receptor blockers (β-blockers) and trimethoprim-sulfamethoxazole (TMP-SMX) may confer a high risk of hyperkalemia. We conducted two nested case-control studies to examine the association between hospitalization for hyperkalemia and the use of TMP-SMX in older patients receiving β-blockers. We used linked health administrative records from Ontario, Canada to assemble a cohort of 299,749 β-blockers users, aged 66 years or older and capture data regarding medication use and hospital admissions for hyperkalemia. Over the study period from 1994 to 2008, 189 patients in this cohort were hospitalized for hyperkalemia within 14 days of receiving a study antibiotic. Compared to amoxicillin, the use of TMP-SMX was associated with a substantially greater risk of hyperkalemia requiring hospital admission (adjusted odds ratio 5.1 [95% CI, 2.8 to 9.4]). No such risk was identified with ciprofloxacin, norfloxacin, or nitrofurantoin. When dosing was considered, the association was greater at higher doses of TMP-SMX. When we repeated the primary analysis in a cohort of non-β-blocker users, the risk of hyperkalemia comparing TMP-SMX to amoxicillin was not significantly different from that found among β-blocker users. Although TMP-SMX is associated with an increased risk of hyperkalemia in older adults, our findings show no added risk when used in combination with β-blockers. Little evidence justifies the avoidance of glyburide in patients with impaired renal function. We aimed to determine if renal function modifies the risk of hypoglycemia among patients using glyburide. We conducted a nested case-control study using administrative records and laboratory data from Ontario, Canada. We included outpatients 66 years of age and older with diabetes mellitus and prescriptions for glyburide, insulin or metformin. We ascertained hypoglycemic events using administrative records and we estimated glomerular filtration rates (eGFR) using serum creatinine concentrations. From a cohort of 19,620 patients, we identified 204 cases whose eGFR was ≥ 60 ml/min/1.73m2 (normal renal function) and 354 cases whose eGFR was < 60 ml/min/1.73m2 (impaired renal function). Compared to metformin, glyburide associated with a greater risk of hypoglycemia in patients with both normal (adjusted OR 9.0, 95% CI 4.9 to 16.4) and impaired renal function (adjusted OR 6.0, 95% CI 3.8 to 9.5). We observed a similar relationship when comparing insulin to metformin; the risk was greater in patients with normal renal function (adjusted OR 18.7, 95% CI 10.5 to 33.5) compared to those with impaired renal function (adjusted OR 7.9, 95% CI 5.0 to 12.4). Tests of interaction showed that among glyburide users renal function did not significantly modify the risk of hypoglycemia, but among insulin users, impaired renal function associated with a lower risk. In this population-based study, impaired renal function did not augment the risk of hypoglycemia associated with glyburide use. In summary, these studies described important ADRs associated with commonly used prescription drugs and highlighted the kidney’s role, both as a target of the drug effect, as in the case of TMP-SMX, and as the cause of the drug accumulation, as in the case of glyburide. Both studies identified significant risks associated with the study drugs and reinforce the need for vigilance when monitoring patients prescribed these medications.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».