Bibliographic record
Abstract
ABSTRACT: Pregnancy could affect the mobility of women with lower extremity limb loss, deficiency, or amputations. The aim of this systematic review was to characterize the pregnancy-related experiences, including prosthesis, gait aid, and mobility outcomes, of women with lower extremity limb loss, deficiency, or amputations. MEDLINE, CINAHL, and Embase databases were searched for all relevant English-language articles describing pregnancy experiences of women with lower extremity limb loss, deficiency, or amputations. Data extracted were age, amputation level and etiology, obstetrical history, prosthesis and/or gait aid use before, during, and after pregnancy, and pregnancy-related complications. Risk of bias was assessed using applicable CLARITY tools. Data were analyzed with descriptive statistics. Among 399 retrieved studies, 24 met inclusion criteria describing 31 pregnancies in 25 women. All were case series/reports with high risk of bias. All women had acquired lower extremity limb loss, deficiency, or amputations. Sixteen women had hemipelvectomy (64%) and 4 had transfemoral amputations (16%). Three women used a prosthesis, 5 did not, and use was not described for 17 (68%). Prosthesis or gait aid use changed in 2 pregnancies, did not change in 6, and was not specified in 23 (74%). Available cases are likely not representative; additional research is required to characterize the impact of pregnancy on women with lower extremity limb loss, deficiency, or amputations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".