Comparison of Cognitive and Behavioural Problems and Psychiatric Diagnoses in Preterm Born Children between 6-13 Years Old
Bibliographic record
Abstract
Introduction: Despite the increased survival rates follow up studies of preterm born children have documented increased prevalence of neurodevelopmental disabilities and cognitive deficits. By using psychiatric assessment, we aimed to evaluate cognitive functions by comparing preterm born babies according to the week of gestation by comparing the scores of the Wechsler Intelligence Scale for Children-Revised Form (WISC-R) in childhood. Material and methods: Children with a history of birth as preterm babies between 1998-2004 were included in the study. The children born between 27-36 weeks, currently 6-13 years old were admitted to the study. The controls consisted of healthy children chosen from the nearest primary school. The WISC-R test was administered to all children. Classification was made according to gestational age. The comparison of cognitive functions was performed by comparing the WISC-R scores of the preterm group and the control group. Results: 238 children were included in our prospective study. (case group: 175 children, control group: 63 children). Because of the comparison of the WISC-R scores of the preterm and control groups, the WISC-R verbal score and WISC-R total score were found to be statistically significant between the preterm and control groups. In the analysis made according to the gestation age, no statistical significance was found between the WISC-R Verbal, WISC-R performance, and WISC-R total scores according to the week of gestation. No statistically significant difference was found in terms of previous and current psychiatric diagnoses. Conclusions: While the WISC-R score was, found to be statistically significantly higher in the case group compared to controls. Our results differed from those in the literature that preterm children had a lower WISC-R score and it indicates the need to investigate this situation by further studies, even by different tests.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".