Early diagnosis of abnormal development of preterm newborns: assessment instruments
Bibliographic record
Abstract
OBJECTIVE: To review the literature regarding screening psychomotor tests for the early identification of developmental problems. SOURCES: A search on SciELO, PubMed and Google Scholar was performed using the terms "prematurity," "developmental delay," "cerebral palsy," "early diagnosis" and "evaluation tests." SUMMARY OF THE FINDINGS: A total of 455 references were listed, and 174 studies were selected for this review based on title, relevance, and abstract. Only original and electronically available material, from 1985 forward, with information on design, applicability, and psychometric properties of those tests was included. CONCLUSIONS: Screening tests are important to speed the beginning of treatment measures in order to allow for better developmental outcome. Among the many tests that can be employed for this purpose, the DENVER II and the Alberta Infant Motor Scale are the most often used in Brazilian studies. The Movement Assessment of Infants is starting to be used in our country. Two other tests are recommended in the literature due to their high sensibility and specificity: the Test of Infant Motor Performance and the General Movements.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".