Maternal severity from survival to death: Gamma regression analysis of WHO organ dysfunction markers in South India
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Maternal mortality alone underestimates the burden of severe obstetric complications, as many women survive life-threatening events with significant organ dysfunction. The WHO maternal near-miss framework provides a severity-based assessment for better understanding extreme maternal morbidity and care quality. This study examined associations between organ dysfunction-based severity markers and maternal death, modelling severity from near miss to death. Methods A cross-sectional study conducted at a South Indian tertiary referral hospital (February 2024–January 2025) included all pregnant and postpartum women within 42 days who met WHO near-miss criteria or experienced death. Associations were assessed using relative risks (RR) with 95% confidence intervals. A generalized linear model with a log link and a gamma distribution was used to assess severity scores. Results Of 4,068 deliveries, 206 had severe outcomes (191 near misses, 15 deaths). Highest mortality is linked to cardiopulmonary resuscitation (82.4%; RR 154.8), intubation/ventilation (45.5%; RR 289.4), shock (24.1%; RR 35.7), severe hypoxemia (50.0%; RR 11.8), oliguria unresponsive to fluids (66.7%; RR 29.2), and dialysis (40.0%; RR 9.3). Hemorrhage (6.9%) and massive transfusion (11.1%) were common but not significantly associated with death. Deaths rose from severity scores ≥5, with none surviving ≥7. Gamma regression showed multi-organ dysfunction as the strongest severity predictor. Conclusion Organ dysfunction-based assessment captures the full spectrum of severe maternal outcomes beyond mortality. Integrating these indicators into obstetric care and health systems enables early risk detection, timely interventions, and improved maternal health monitoring .
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,000
OpenAlex ID: W7160708716