2466. Evaluation of Immunization on the Neonatal Intensive Care Unit at British Columbia Women’s Hospital
Bibliographic record
Abstract
Term and preterm infants in the neonatal intensive care unit (NICU) should be immunized at the same chronological age and on the same schedule as healthy term infants, but are often under-immunized. Reasons for under-immunization in this population have not been well-defined. The aim of this study was to assess the immunization rates of hospitalized term and preterm infants in the NICU and examine reasons for under-immunization. Pharmacy and NICU databases were utilized to determine the immunization rates of eligible babies admitted to the NICU between 2011 and 2015. A retrospective review of unimmunized infants was undertaken to identify barriers to timely immunization. Patient demographics and transfers to other hospitals were recorded. Reasons for the delay in immunization were evaluated by detailed review of the hospital medical record. Of the 3,261 babies admitted to the NICU during the study period, 534 (16%) were hospitalized at ≥8 weeks of age, when first immunizations are administered. Of these, 142 (27%) received no immunizations in hospital. Sixty-five medical records were reviewed in detail. Thirty of the 65 (46%) medical records did not document that immunizations were due. In 21 (32%) of the 65 cases, there was no clear reason for lack of immunization. Of the remaining cases, infants were not vaccinated for 1 or more reasons. Infants deemed too unwell, including recovery from surgery, seizures/encephalopathy, severe immunocompromise, or palliative care, was one of the reasons for lack of vaccination in 35 (54%) of the 65 cases, parental refusal of vaccinations in 8 (12%) of cases, and deferral to discharging hospital in 7 (11%) of cases. Significant comorbidity appeared to be the major reason behind vaccination delays, with 27% of highly vulnerable infants unimmunized. Significant improvements are required to ensure these babies receive vaccines upon recovery from their illness, and to ensure absence of immunization is clearly documented upon hospital discharge. All authors: No reported disclosures.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".