The 24-hour urinary cortisol in post-traumatic stress disorder: A meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Previous studies found inconsistent results on the relationship between post-traumatic stress disorder (PTSD) and concentrations of 24-hour (24-h) urinary cortisol. This study performed a systematic review and meta-analysis to summarize previous findings on this relationship. METHODS: We searched in the databases of Web of Science, PubMed, Embase, and Psyc-ARTICLES for articles published before September 2018. We used the random-effects model with restricted maximum-likelihood estimator to synthesize the effect sizes by calculating the standardized mean difference (SMD) and assessing its significance. RESULTS: Six hundred and nineteen articles were identified from the preceding databases and 20 of them were included in the meta-analysis. Lower concentrations of 24-h urinary cortisol were observed in patients with PTSD when compared with the controls (SMD = -0.49, 95%CI [-0.91; -0.07], p = 0.02). Subgroup analysis revealed that the concentrations of 24-h urinary cortisol were lower in PTSD patients than in the controls for studies that included female participants or studies that included participants from the United States of America. CONCLUSIONS: Overall, decreased levels of 24-h urinary cortisol were linked with the pathophysiology of PTSD. Nonetheless, more studies should be conducted to validate the molecular underpinnings of urine cortisol degeneration in PTSD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".