77: Examining the Use of Withdrawal of Life-Sustaining Therapy in Three Pediatric Patient Populations
Bibliographic record
Abstract
A poor prognosis based on mortality or disability rates can push physicians to discuss withdrawal of life-sustaining therapy (WLST) for newborns in the NICU. However, WLST may not be discussed with families of an older child despite a similar poor prognosis. Three patient populations with overlapping prognoses include: ventilated extremely premature infants (22–25 weeks) (EPI), ventilated term neonates with hypoxic ischemic encephalopathy (HIE) and ventilated children with traumatic brain injury (TBI). 1) To document the frequency with which physicians discuss WLST with families in each respective population; 2) to compare the frequency of discussions between populations; and, 3) to document the frequency of five possible ‘outcomes’ of WLST discussions in each population: WLST ‘late’ in clinical course, WLST ‘early’ in clinical course, WLST with ‘unexpected survival’, refusal of WLST with survival and refusal of WLST with death. Retrospective chart review of cases from January 2003 to December 2013. Included cases met pre-specified inclusion criteria (eg. in-hospital survival of >24 hrs). Prevalence of WLST discussions and the outcome after WLST discussions will be determined using the Wilson score method. Comparisons will use Fisher's exact test. Of the 300 charts reviewed to date, 155 were included: 95 EPI, 48 HIE and 12 TBI. WLST was discussed in 35 of EPI, 24 of HIE and one of TBI. For EPI, in 16 cases, WLST was ‘late’; in 12 cases, WLST was ‘early’; there was one ‘unexpected survival’. For HIE, in one case, WLST was ‘late’; in 16 cases, WLST was ‘early’; there was no ‘unexpected survival’. For TBI, there was no occurrence of WLST. For EPI, WLST was refused in six cases: three died and three survived. For HIE, WLST was refused in two cases: one died and one survived. For TBI, WLST was never recommended and thus never refused. Statistical comparison between populations will occur after chart review completion. In 55 EPI, 24 HIE and 11 TBI (90/155 cases), no discussion of WLST was documented. Preliminary data does not demonstrate a greater frequency of WLST discussions in EPI compared with HIE; this does not support literature suggesting a bias against EPI. There was a very low frequency of WLST discussions and actual WLST in TBI, as per the current literature. Despite guarded prognoses for these populations, discussion of WLST is relatively infrequent.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".