NICU‐only versus universal screening for newborn hearing loss: Population audit
Bibliographic record
Abstract
AIM: Targeted newborn hearing screening for infants in neonatal intensive care units (NICUs) may be considered when resources preclude universal newborn hearing screening (UNHS). However, process outcomes have not been compared between stand-alone NICU hearing screening programs and NICU screening within a full UNHS program. METHODS: Comparison of two consecutive hearing screening programs delivered under similar conditions in the four NICUs in Victoria, Australia. All NICU infants were eligible for pre-discharge automated auditory brainstem response (AABR) hearing screening. Capture, referral and diagnostic data were collected for all NICU infants during the NICU-only (April 2003-February 2005) and subsequent UNHS (April 2005-June 2006) programs. RESULTS: 4704 eligible infants were admitted during the 23-month NICU-only period, and 3160 during the 15-month UNHS period. Double AABR using ALGO 3i equipment was planned for both programs but, due to clinician concern about this high-risk clinical population, the NICU-only protocol was amended to single AABR using AccuScreen equipment. Capture rates were 71.1% (NICU-only) vs. 95.4% (UNHS) (P < 0.001), successful follow-up rates were 85.8% vs. 96% (P= 0.004), and mean corrected age at the first audiology appointment was 51.5 vs. 40.2 days (P= 0.05). CONCLUSIONS: NICU screening offered within a larger UNHS program outperformed the stand-alone NICU hearing screening program on all measured parameters. Greater resourcing might address shortcomings of the stand-alone program but would also reduce its potential savings. The high loss to follow-up also argues against the often-advocated approach of referring all NICU infants for diagnostic audiologic testing, bypassing hearing screening altogether.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".