Assessment of the Antidepressant Side Effects Occurrence in Patients Treated in Primary Care
Bibliographic record
Abstract
INTRODUCTION: It is an undeniable fact that antidepressants can cause side effects. Antidepressants generally have a similar effect but they differ in their application safety, as well as their side effects. AIM: To determine differences in the frequency and intensity of antidepressant induced side effects in patients treated in primary care. METHODS: The research was designed as a prospective, cross-sectional study, conducted on a voluntary and anonymous basis, and it included depression patients treated with antidepressant medications during 2013-2015 in Zenica-Doboj Canton using the Hamilton Depression Rating Scale and Toronto Side Effects Scale. RESULTS: The total sample included 508 subjects. As a significant problem, abdominal pain was felt by 14% of subjects, indigestion by 19% of subjects, nausea by 15% of subjects, diarrhea by 9% of subjects, and constipation by 11% of subjects. 29% of subjects suffered from sweating, 20% suffered from a sudden heat stroke, 10% suffered from swelling, and 23% of them reported suffering from dry mouth as a significant problem. The prevalence of side effects in relation to how do they affect life and daily activities of subjects is statistically significant (P <0.000). Statistically significant side effects of SSRI antidepressants correlate with the duration of our subject's treatment: perception of increased sleep (0.039) as well as decreased sleep (P = 0.009), sweating (P <0.001), sudden heat stroke (P <0.001), being without orgasm (P = 0.004), decreased libido (P <0.001), weight loss (P = 0.045). CONCLUSION: It is necessary to educate the patients about the nature and features of the depressive disorder, and to notify the patients of the expected course of recovery, as well as the need to adhere to the recommended therapy and the possible side effects of the medication.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".