Ancillary investigations for death determination in infants and children: a systematic review and meta-analysis
Bibliographic record
Abstract
Purpose We performed a systematic review and meta-analysis to determine the diagnostic test accuracy of ancillary investigations for declaration of death by neurologic criteria (DNC) in infants and children. Source We searched MEDLINE, EMBASE, Web of Science, and Cochrane databases from their inception to June 2021 for relevant randomized controlled trials, observational studies, and abstracts published in the last three years. We identified relevant studies using Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and a two-stage review. We assessed the risk of bias using the QUADAS-2 tool, and applied Grading of Recommendations Assessment, Development, and Evaluation methodology to determine the certainty of evidence. A fixed-effects model was used to meta-analyze pooled sensitivity and specificity data for each ancillary investigation with at least two studies. Principal findings Thirty-nine eligible manuscripts assessing 18 unique ancillary investigations (n = 866) were identified. The sensitivity and specificity ranged from 0.00 to 1.00 and 0.50 to 1.00, respectively. The quality of evidence was low to very low for all ancillary investigations, with the exception of radionuclide dynamic flow studies for which it was graded as moderate. Radionuclide scintigraphy using the lipophilic radiopharmaceutical 99mTc-hexamethylpropyleneamine oxime (HMPAO) with or without tomographic imaging were the most accurate ancillary investigations with a combined sensitivity of 0.99 (95% highest density interval [HDI], 0.89 to 1.00) and specificity of 0.97 (95% HDI, 0.65 to 1.00). Conclusion The ancillary investigation for DNC in infants and children with the greatest accuracy appears to be radionuclide scintigraphy using HMPAO with or without tomographic imaging; however, the certainty of the evidence is low. Nonimaging modalities performed at the bedside require further investigation. Study registration: PROSPERO (CRD42021278788); registered 16 October 2021.
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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 | 0.024 | 0.052 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.050 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".