A decade of neonatal polycythaemia – has anything changed in this field?
Bibliographic record
Abstract
Introduction This study aims to determine the prevalence, clinical features, and methods of treating polycythaemia (PC) and hyperviscosity (HVS) syndrome in newborns over a 10-year period (2012–2022). Furthermore, it aims to determine whether there have been changes in the incidence of PC in the region encompassed by the study. Material and methods This retrospective study sample included all the newborns with a diagnosis upon admittance and discharge of PC and HVS syndrome. Results Incidence of PC and HVS syndrome was 0.8% (153/18.407) of the total number of babies born and 2.8% (153/5.483) of the treated newborn. Polycythaemia was more common in newborn males, in newborn weighing more than 2500 grams, with normal vitality scores, born at full term, and with other pathological conditions. The most common pathological condition in the newborn with PC was jaundice, and the most common symptoms were plethoric and dry skin, rash, and hypotonia. Furthermore, mothers with and without pathological conditions, who gave birth naturally, were equally represented. Conclusions This 10-year study concludes that the prevalence of PC was constant over the years. Furthermore, mothers with and without pathological conditions, who gave birth naturally, were equally represented. The newborns were more frequently male, full-term babies, with good vitality scores and birth weights. Also, all the above leads to the conclusion that the newborns had passive PC that was not caused by a medical indication at birth, which led to the spectrum of various symptoms and pathological conditions that accompany PC. On the basis of the above results, it can be concluded that PC is most often passive in our region, which is why PC must be taken into consideration in the daily care of newborns despite the controversial opinions on the above-mentioned pathology.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.023 | 0.012 |
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".