Evaluation of the pharmacotherapy optimization in residents of the Retirement home Nova Gorica with kidney impairment within the clinical pharmacist´s consultation practice
Bibliographic record
Abstract
Pri kronični ledvični bolezni (KLB) ledvice sčasoma izgubijo sposobnost odstranjevanja odpadnih snovi in uravnavanja ravnovesja tekočin ter elektrolitov v telesu. Številna zdravila se izločajo skozi ledvice, zato je treba pri bolnikih s KLB pogosto prilagajati farmakoterapijo, da preprečimo neželene učinke zdravil. Namen retrospektivne klinične raziskave je bila analiza optimizacije farmakoterapije pri oskrbovancih Doma upokojencev Nova Gorica, ki so bili v drugi polovici leta 2022 in leta 2023 napoteni na farmakoterapijski pregled zaradi KLB. Analizirali smo njihove laboratorijske podatke, število in vrsto predpisanih zdravil, priporočila farmacevta svetovalca in ali so bila priporočila upoštevana s strani zdravnika. Raziskava je vključevala 55 bolnikov (78,2 % žensk, mediana starosti 88 let). Predpisano so imeli različno število zdravilnih učinkovin, mediana je bila 15. Večina bolnikov je imela napredovale stopnje KLB (stopnje 3b, 4 ali 5). Celokupno je farmacevt svetovalec podal 87 predlogov za prilagoditev terapije, ki smo jih razdelili v 7 kategorij, in sicer na prilagoditev odmerjanja, spremljanje ledvične funkcije, ukinitev zdravila, zamenjava zdravila, odsvetovana uporaba in uvedba novega zdravila, pri nekaterih zdravilih pa prilagoditev ni bila potrebna. Najpogosteje podana predloga sta bila spremljanje ledvične funkcije (26/87
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".