Bibliographic record
Abstract
Sir, We would like to thank Drs. Caroline H.G. Bastiaenen, Rob A. de Bie and Gerard G.M. Essed for their interest in our work. Bastiaenen et al. comment on our assertion that Dutch data on prevalence of pregnancy-related pelvic girdle pain (PPGP) are lacking. They give an outline of their study in which they examined treatment of pregnancy-related pelvic girdle and/or low back pain. As they stated in their article (1) multiparity plays an important role in etiology and prognosis of pregnancy-related pelvic girdle pain. In their cohort, only 42.3% of included women were pregnant with their first child. Their data were not analysed separately for first and consecutive pregnancies. Participants were recruited both through midwives and gynecologists. In the Netherlands pregnancy and delivery are considered physiological events. Therefore, healthy pregnant women are monitored by midwives or general practitioners. If prior to or during pregnancy or parturition a medical problem occurs, the woman is referred to a gynecologist/obstetrician. In our study we choose to use a clinical model which theoretically generates the least amount of bias, by including only women pregnant with their first child and by recruiting these women through midwifery practices to ensure participation of healthy women. Bastiaenen et al. used in their study a very broad definition on PPGP; pain in the lower back, buttocks, symphysis, groins and/or radiation into the legs. Because there is no consensus on definition nor etiology, and clinical criteria are lacking, this was a good choice. We congratulate the authors on their research in a very large cohort. However, in the present study, we were particularly interested in the prevalence of self reported and so-called “pelvic instability”. As depicted in the introduction of the article, the term pelvic instability is not supported by our group, but was and still is used so extensively in Dutch media and among lay people that we aimed to examine how many women thought of themselves as suffering from this specific problem. As Bastiaenen et al. correctly suggested, this group of women seems to be a selective group within the pregnancy-related pelvic girdle pain group as illustrated by excessive sick leave and loss of mobility compared to women only suffering from back pain. Finally, Bastiaenen et al. mention the use of the Pregnancy Mobility Index (PMI). This mobility scale has been shown to be a reliable and valid questionnaire specifically designed for use during and after pregnancy (2). The PMI was not validated with the Roland Disability Questionnaire, which is a questionnaire designed to measure mobility in a non-pregnant population suffering from back pain. This questionnaire was used, together with the Quebec Back Pain Disability Scale by Bastiaenen et al. (1). Neither questionnaire has been validated in a pregnant population, and consequently had to be adjusted by adding “not applicable” to the answer possibilities and by changing “because of my back pain” to “because of my back and/or pelvic pain”. We agree that in retrospect it would have been interesting to compare all three questionnaires.
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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 | 0.004 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.016 | 0.029 |
| Insufficient payload (model declined to judge) | 0.028 | 0.024 |
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".