Meta-analiza podataka o razlikama u izloženosti psihijatrijskim lekovima između sporih i normalnih CYP2C19/CYP2D6 metabolizera
Bibliographic record
Abstract
Postoji mogućnost da genetski predodređene razlike između osoba u kapacitetu CYP450\nenzima mogu uticati na farmakoterapiju u psihijatriji. Cilj ovog istraživanja bio je precizna\nkvantifikacije uticaja CYP2C19/CYP2D6 fenotipa na izloženost antidepresivima i\nantipsihoticima metodom meta-analize odnosa srednjih vrednosti. Drugi cilj bio je\nispitivanje uticaja CYP2C19 fenotipa na efikasnost i podnošljivost antidepresiva pomoću\nkliničke studije u kojoj su hospitalizovani pacijenti praćeni četiri nedelje.\nSerija meta-analiza podataka iz 94 jedinstvene studije na ukupno 8379 precizno je\nkvantifikovala povećanu izloženost escitalopramu (+163%; 95%CI: +140%, 189%;\nn=1262, p<0,0001) i sertralinu (+38%; 95%CI: +27%, +51%; n=917, p<0,0001) kod osoba\nsa genetski predviđenim smanjenim kapacitetom CYP2C19 enzima, kao i povećanu\nizloženost risperidonu (+36%; 95%CI: +28%, +44%; n=1492, p<0,0001), aripiprazolu\n(+48%; 95%CI: +41%, +57%; n=1038, p<0,0001) i haloperidolu (+68%; CI95%: 40%,\n102%; n=423, p<0.0001) kod osoba sa genetski predviđenim smanjenim kapacitetom\nCYP2D6 enzima. Klinička studija demonstrirala je da su, u toku četiri nedelje, osobe sa\nsporijim CYP2C19 metabolizmom imale 36% (95%CI: 20-52%, p<0,0001) manje izraženo\npoboljšanje simptoma depresije (praćeno Hamilton skalom za depresiju) i značajno veći\nintenzitet neželjenih efekata vezanih za gastrointestinalni (q=0,002) i centralni nervni\nsistem (q=0,045) što je mereno Toronto skalom, u odnosu na kontrolne osobe.\nZbog visoke preciznosti kvantifikacije, rezultati meta-analiza mogu poslužiti kao osnova za\nkliničke smernice za precizno doziranje ispitivanih lekova na osnovu CYP2C19/CYP2D6\ngenotipa. Takođe, rezultati kliničke studije naglašavaju da CYP2C19 genotip može biti\nklinički važna informacija u psihijatrijskoj praksi.
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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 | 0.022 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.025 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".