Evidence map›Paper›PMID 42857028›Full record

ArticleCureus2026

Comparison of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Obstetrically Modified SOFA, and Obstetrically Modified qSOFA Scores for Predicting Maternal Outcomes in High-Risk Obstetric Patients.

Monika Chaudhary, Divya Yadav, Nidhi Gupta, Arpita Saxena, Asha Nigam, Neelam Singh

Abstract read
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Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Monika ChaudharyObstetrics and Gynaecology, Sarojini Naidu Medical College, Agra, IND.
Divya YadavObstetrics and Gynecology, Sarojini Naidu Medical College, Agra, IND.
Nidhi GuptaObstetrics and Gynaecology, Sarojini Naidu Medical College, Agra, IND.
Arpita SaxenaAnaesthesiology, Sarojini Naidu Medical College, Agra, IND.
Asha NigamObstetrics and Gynaecology, Sarojini Naidu Medical College, Agra, IND.
Neelam SinghObstetrics and Gynaecology, Sarojini Naidu Medical College, Agra, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Maternal morbidity and mortality remain significant challenges in obstetric critical care. Early identification of organ dysfunction is essential for timely intervention and improved outcomes. This study compared the prognostic performance of the Sequential Organ Failure Assessment (SOFA), quick Sequential Organ Failure Assessment (qSOFA), obstetrically modified SOFA (omSOFA), and obstetrically modified qSOFA (omqSOFA) scores in predicting maternal outcomes among high-risk obstetric patients. Methods A prospective observational study was conducted among 200 high-risk obstetric patients admitted to a tertiary care center. Twelve patients who left against medical advice were excluded from outcome-based analyses, leaving 188 patients for final evaluation. SOFA, qSOFA, omSOFA, and omqSOFA scores were calculated at admission. Receiver operating characteristic (ROC) curve analysis was performed to determine the predictive performance of each scoring system for maternal mortality. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and optimal cutoff values were calculated. Results Among the 188 patients included in the final analysis, 15 maternal deaths occurred. SOFA demonstrated the highest discriminatory ability for predicting maternal mortality, with an AUC of 0.97 (95% CI: 0.94-0.99) at a cutoff value of ≥10, followed by omSOFA with an AUC of 0.93 (95% CI: 0.89-0.97) at a cutoff value of ≥9. qSOFA and omqSOFA showed AUCs of 0.76 (95% CI: 0.68-0.84) and 0.79 (95% CI: 0.71-0.87), respectively. qSOFA and omqSOFA demonstrated 100% sensitivity and negative predictive value at a cutoff score of ≥2, while SOFA and omSOFA provided superior specificity and overall discriminatory performance. Conclusions Among high-risk obstetric patients, SOFA demonstrated the highest discriminatory ability for predicting maternal mortality, followed by omSOFA. While qSOFA and omqSOFA showed lower specificity, they demonstrated excellent sensitivity and negative predictive value, making them useful bedside screening tools for early risk identification. Incorporation of these scoring systems into obstetric critical care practice may facilitate timely risk stratification and early intervention. Further multicentre studies are required to validate these findings in larger and more diverse obstetric populations.

Indexed as

high-risk pregnancyintensive carematernal mortalitymaternal outcomesobstetrically modified sofaobstetric critical careorgan dysfunctionprognostic scoring systemsqsofasofa score

Identifiers

PMID42857028
PMCPMC13650759

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.