Risk factors for postpartum sepsis: a nested case-control study.

BACKGROUND: The Majority (99%) of maternal deaths occur in low and middle-income countries. The three most important causes of maternal deaths in these regions are postpartum hemorrhage, pre-eclampsia and puerperal sepsis. There are several diagnostic criteria used to identify sepsis and one of the commonly used criteria is systematic inflammatory response syndrome (SIRS). However, these criteria require laboratory investigations that may not be feasible in resource-constrained settings. Therefore, this study aimed to develop a model based on risk factors and clinical signs and symptoms that can identify sepsis early among postpartum women. METHODS: A case-control study was nested in an ongoing cohort of 4000 postpartum women who delivered or were admitted to the study hospital. According to standard criteria of SIRS, 100 women with sepsis (cases) and 498 women without sepsis (controls) were recruited from January to July 2017. Information related to the socio-demographic status, antenatal care and use of tobacco were obtained via interview while pregnancy and delivery related information, comorbid and clinical sign and symptoms were retrieved from the ongoing cohort. Multivariable logistic regression was performed and discriminative performance of the model was assessed using area under the curve (AUC) of the receiver operating characteristic (ROC). RESULTS: Multivariable analysis revealed that 1-4 antenatal visits (95% CI 0.01-0.62). , 3 or more vaginal examinations (95% CI 1.21-3.65), home delivery (95% CI 1.72-50.02), preterm delivery, diabetes in pregnancy (95% CI 1.93-20.23), lower abdominal pain (95% CI 1.15-3.42)) vaginal discharge (95% CI 2.97-20.21), SpO2 < 93% (95% CI 4.80-37.10) and blood glucose were significantly associated with sepsis. AUC was 0.84 (95% C.I 0.80-0.89) which indicated that risk factors and clinical sign and symptoms-based model has adequate ability to discriminate women with and without sepsis. CONCLUSION: This study developed a non-invasive tool that can identify postpartum women with sepsis as accurately as SIRS criteria with good discriminative ability. Once validated, this tool has the potential to be scaled up for community use by frontline health care workers.

Comparison of qSOFA and SOFA score for predicting mortality in severe sepsis and septic shock patients in the emergency department of a low middle income country.

OBJECTIVE: We aimed to determine a comparison between the Quick Sequential Organ Failure Assessment (qSOFA) score and existing Sequential Organ Failure Assessment (SOFA) score when applied to severe sepsis & septic shock patients in the Emergency Department (ED) for prediction of in-hospital mortality in the setting of a tertiary care hospital ED in a low-middle income country. METHOD: We conducted a prospective observational cohort study on 760 subjects. The qSOFA, SOFA score and in-hospital mortality were assessed by area under the receiver operating curve (AUROC). We calculated sensitivity and specificity for each score for outcomes at cut-offs of 0.92 and 0.63 for qSOFA and SOFA in Severe Sepsis respectively and 0.89 and 0.63 for qSOFA and SOFA in Septic shock respectively. RESULTS: In patients with severe sepsis, the AUROC of qSOFA for predicting mortality in subjects was 0.92 (95% CI; 0.89-0.94) with 96% sensitivity and 87% specificity in comparison to the AUROC of SOFA score which was 0.63 (95% CI; 0.55-0.70 with 71% sensitivity and 57% specificity. In patients with septic shock, the AUROC of qSOFA for predicting mortality in subjects was 0.89 (95% CI; 0.85-0.92) with 92% sensitivity and 85% specificity in comparison to the AUROC of SOFA score which was 0.63 (95% CI; 0.55-0.70 with 70% sensitivity and 59% specificity. CONCLUSION: Our study concludes that qSOFA score is an effective tool at predicting in hospital mortality in comparison to SOFA score when applied to severe sepsis and septic shock patients in the setting of a tertiary care hospital ED of a low-middle income country however, further studies are needed before application for this purpose.