The Effects of Lavandula Angustifolia Mill Infusion on Depression in Patients Using Citalopram: A comparison Study
Bibliographic record
Abstract
BACKGROUND: Many herbs have been used to treat psychiatric disorders including anxiety and depression in traditional medicine. OBJECTIVES: This study was carried out to determine the effect of using Lavandula angustifilia infusion on depression in patients taking Citalopram. PATIENTS AND METHODS: Among all patients referred to the Hajar Hospital psychiatric clinic, Shahrekord, Iran, 80 patients who met the criteria of major depression according to the structured interviews and the Hamilton questionnaire for Depression were included in the study. They were randomly assigned into two groups of experimental treatment group and standard treatment group at this study. In standard treatment group, the patients were given Citalopram 20 mg. In experimental treatment group, the patients took 2 cups of the infusion of 5 g dried Lavandula angustifilia in addition to tablet Citalopram 20 mg twice a day. The patients were followed up for four and eight weeks of the study onset using Hamilton Scale questionnaire and treatment side effects form. Data were analyzed using student t-test, pair t-test and chi square. RESULTS: After four weeks of the trial onset, the mean depression score according to the Hamilton Scale for Depression was 17.5 ± 3.5 in the standard treatment group and 15.2 ± 3.6 in the experimental treatment group (P < 0.05). After eight weeks, it was 16.8±4.6 and 14.8±4 respectively (P < 0.01). In addition, the most commonly observed adverse effects were nausea (12.8 %) and confusion (10%). In terms of side effects, there were no significant differences between two groups. CONCLUSIONS: Considering the results of this study, Lavandula angustifilia infusion has some positive therapeutic effects on depressed patients most importantly decreases mean depression score and might be used alone or as an adjunct to other anti-depressant drugs.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".