Asociación entre aborto inducido y depresión: una revisión sistemática y metaanálisis
Bibliographic record
Abstract
This article is a systematic review (SR) and meta-analysis (MA) whose objective was to identify the association between induced abortion and the development of depression, based on the Cochrane guidelines for SRs. A systematic search was carried out in the WoS, PubMed and Scopus databases. Retrospective and prospective cohort studies, carried out until November 2020, that evaluated a population of women in childbearing age (12 to 46 years) with at least 1 induced and/or provoked abortion, including pharma-cological and surgical abortion. Only studies with healthy women at the beginning of the research were included, i.e., with absence of psychiatric pathology prior to induced abor-tion. The quality of the included studies was measured with the Newcastle-Ottawa Scale (NOS), and for the MA random-effects models were specified using the DerSimonian & Laird method, grouping them into follow-up after abortion before and after one year. The results of the SR were measured with relative risk (RR), hazard ratio (HR), odds ratio (OR), and the chi-square test, which assessed the intensity of the statistical relationship between population and exposure. Systematic review demonstrated an OR of 1.38 (95% CI 1.14-1.68) of depression after induced abortion. Meta-analysis demonstrated a statis-tically significant association between depression and induced abortion when the as-sessment after one year was performed OR: 1.37 (95% CI 1.09-1.71). The risks, harms and mental health consequences of induced abortion, such as depression, should be in-vestigated and warned.
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 | 0.028 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".