Assessing feasibility of resources at health facilities in Uganda to diagnose pregnancy and neonatal outcomes
Bibliographic record
Abstract
BACKGROUND: Standardized case definitions for obstetric and neonatal outcomes were developed by the Global Alignment of Immunization Safety Assessment in Pregnancy (GAIA) project. These definitions can facilitate comparable assessment of maternal immunization safety surveillance and research. This study assessed the capabilities of health centers (HC) in Uganda to implement these definitions in a low income country, which has not been explored. METHODS: Healthcare practitioners at 15 government-accredited health centers and one government-funded district hospital in the Iganga-Mayuge Health and Demographic Surveillance Site (IMHDSS) in Uganda were interviewed about the facility's clinical diagnostic and laboratory capabilities. Five obstetric and five neonatal case definitions were evaluated. Definitions with the highest diagnostic certainty were designated as level 1, while definitions that decreased in certainty were designated as level 2 or 4. HCs were evaluated on diagnostic and laboratory capabilities to apply the GAIA definitions. RESULTS: Higher-level facilities in the IMHDSS demonstrated the ability to diagnose more specific levels of the GAIA obstetric and neonatal outcomes than lower-level facilities. Furthermore, for the neonatal outcome assessment, there was an increased ability to diagnose outcomes moving from GAIA level 1 to level 3. CONCLUSIONS: The ability of health centers to implement globally standardized definitions is promising for implementation of standardized data collection methods for global vaccine safety surveillance and research.
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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 | 0.000 |
| 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".