Performance characteristics of a local triage tool and internationally validated tools among under-fives presenting to an urban emergency department in Tanzania
Bibliographic record
Abstract
BACKGROUND: A number of region-specific validated triage systems exist; however very little is known about their performance in resource limited settings. We compare the local triage tool and internationally validated tools among under-fives presenting to an urban emergency department in Tanzania. METHODOLOGY: Prospective descriptive study of consecutive under-fives seen at Muhimbili National Hospital (MNH), ED between November 2017 to April 2018. Patients were triaged according to Local Triage System (LTS), and the information collected were used to assign acuities in the other triage scales: Canadian Triage and Acuity Scale (CTAS), Australasian Triage Scale (ATS), Manchester Triage Scale (MTS) and South African Triage Scale (SATS). Patients were then followed up to determine disposition and 24 h outcome. Sensitivity, specificity, positive and negative predictive values for admission and mortality were then calculated. RESULTS: A total of 384 paediatric patients were enrolled, their median age was 17 months (IQR 7-36 months). Using LTS, 67(17.4%) patients were triaged in level one, 291(75.8%) level 2 and 26 (6.8%) in level 3 categories. Overall admission rate was 59.6% and at 24 h there were five deaths (1.3%). Using Level 1 in LTS, and Levels 1 and 2 in other systems, sensitivity and specificity for admission for all triage scales ranged between 27.1-28.4% and 95.4-98% respectively, (PPV 90.3-95.3%, NPV 47.1-47.4%). Sensitivity for mortality was 80% for LTS, and 100% for the other scales, while specificity was low, yielding a PPV for all scales between 6.9 and 8%. CONCLUSION: All triage scales showed poor ability to predict need for admission, however all triage scales except LTS predicted mortality. The test characteristics for the other scales were similar. Future studies should focus on determining the reliability and validity of each of these triage tools in our setting.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".