Subjective Cognitive Functioning in Silicone Breast Implant Patients: A Cohort Study
Bibliographic record
Abstract
Background: Cognitive impairment is frequently reported by silicone breast implant (SBI) patients. The aim of our study is to investigate whether subjective cognitive failure indeed is more frequent in a cohort of SBI patients compared with healthy controls (HCs). Furthermore, the severity of this cognitive failure and a possible relation to other symptoms as well as the duration of SBI exposure was examined. In addition, we assessed the effect of ruptures and reinterventions on cognitive failure severity. Methods: A cohort study was performed, including 376 women and consisting of 3 different groups of patients; 143 SBI patients (group 1), 94 age- and sex-matched HC patients (group 2), and 139 women with SBI and health issues who registered themselves at a Dutch foundation for women with illness due to SBI (group 3). All patients filled in the Cognitive Failure Questionnaire (CFQ). The American College of Rheumatology Fibromyalgia Diagnostic Criteria (2010) were used to score other symptoms. Results: Completed CFQ data from 222 patients were available for analysis: n = 79 for group 1, n = 62 for group 2, and n = 81 for group 3. SBI patients from group 3 had a significantly higher prevalence of subjective cognitive dysfunction (CFQ score ≥ 43) compared with SBI patients from group 1 and HC (60.5% versus 13.9% and 12.9%; P = 0.000). Linear regression showed a statistically significant relation between subjective cognitive functioning scores and other symptoms (P = 0.000). Implant duration as well as rupture rate and reinterventions were not found to significantly influence CFQ scores. Conclusion: An increased risk of cognitive failure in consecutive SBI patients when compared with HCs could not be found.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".