The Floppy Infant: Retrospective Analysis of Clinical Experience (1990—2000) in a Tertiary Care Facility
Bibliographic record
Abstract
We describe the results of a retrospective study of floppy infants evaluated at the Children's Hospital of Winnipeg, a tertiary care children's facility. Cases were ascertained by a systematic search of clinical databases, hospital and electromyographic records for "floppy" infants age < 1 year, referred over a period of 11 years (1990-2000). Eighty-nine infants, 42 female (47.2%) and 47 male (52.8%), were included in the study. A definitive diagnosis was established in 60 (67.4%) cases, in 24 cases (40%) on purely clinical grounds, whereas in 36 (60%) cases, additional investigations were necessary. Karyotype, molecular diagnostics, cranial imaging, and muscle and skin biopsy provided diagnostic information. Genetic disorders in 18 of 60 (20.2%), congenital or acquired disorders of the central nervous system in 22 of 60 (24.7%), and disorders of the lower motor unit in 9 of 60 (10.1%) contributed to the majority of diagnoses. Eight of 89 (8.9%) infants died in the first year, and 2 of 89 (2.6%) were on home ventilation. Of the 61 infants surviving beyond 12 months, 38 of 61 (62.3%) were found to be globally delayed, and only 30 of 61 (49.2%) achieved independent ambulation at their last clinical evaluation. Systematic evaluation of a floppy infant followed by careful selection of investigations (karyotype, DNA-based diagnostic tests, and cranial imaging) can maximize diagnostic yield.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".