Browsing by Author "Rai, Subash"
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Publication Analysis of Outcomes of Critically ill Surgical Patients using SAPS II Score(Institute of Medicine, 2019) Paudel, Prakash; Rai, Subash; Shrestha, Sunil; Pradhan, Giridhar BN; Bhattachan, Chitra LABSTRACT Introduction Several prognostic models have been implemented for risk assessment and mortality prediction in critically ill patients admitted in ICU. The availability of such sophisticated methods has facilitated in clinical decision making and comparison of outcomes. However, none are universally accepted as standard method to predict mortality. We have decided to use SAPS II score because of the simplicity and easy availability of its variables to analyse the outcomes of critically ill surgical patients admitted to ICU at our centre. Methods The study was conducted between September 2016 and August 2018 at Nepal Medical College and Teaching Hospital, Kathmandu, Nepal. We prospectively collected data on surgical patients consecutively admitted to the ICU during the study period. The variables of SAPS II score were collected from the physiological, laboratory, and patient characteristics mentioned in the ICU scoring data sheet at 24 hours. The SAPS II score and predicted mortality was calculated using computer software programme. The predictive mortality based on the score was compared with the actual outcome to derive the standardized mortality ratio (SMR). Results During the period of study, 64 patients met the inclusion criteria. The mean age of the patients was 54±17.9 (20-84) years and length of ICU stay was 5.3 ±3.5 (3-22) days. GI malignancy was most common pathology comprising 43.8% (n=28). The mean SAPS II score was 24.9±16.4 (3-68). There was no statistical difference in mean SAPS II score between patients with different gender, nature of disease and type of surgical intervention The mean predicted mortality was 13.4% and the observed ICU mortality was 15.6% (n=10). The calculated mean SAPS II score and predicted mortality was higher in nonsurvivors compared to survivors (p<0.0001). The calculated SMR for our study population was 0.85 ranging from 0.01 to 5.2. The number of patients with SMR greater than 1 was only 17 % (11/64). There was significant correlation of mortality with SMR greater than 1 (p=<0.0001). Conclusion The variables in SAPS II score are readily available. Neither special samples nor cumbersome procedures are required. SAPS II can be used as simple and rapid tool to predict mortality in critically ill surgical patients in our set up. Keywords: Critically ill, intensive care unit, mortality, outcome, SAPS IIPublication Risk Factors for Primary Postpartum Hemorrhage in Vaginal Delivery(Nepal Health Research Council, 2024) Rai, Subash; Dangal, Ganesh; Jaiswal. EktaBackground: Postpartum hemorrhage is an emergency, condition encountered in obstetric cases. It is an acute life-threatening situation and needs an immediate and rapid management. Postpartum hemorrhage is leading cause of maternal mortality and morbidity worldwide, with more commonly affecting women of developing countries. Accurate assessment of blood loss, identification of risk factors and timely recognition of postpartum hemorrhage remain major challenge in obstetrics. Different risk factors like hypertensive disorder in pregnancy, antepartum hemorrhage, anemia, big baby, polyhydramnios, multiple pregnancy, obesity, augmented/prolonged labor are risk factors for primary postpartum hemorrhage. The objective of this study was to identify the various risk factors associated with primary postpartum hemorrhage, in Paropakar Maternity and Women’s Hospital (PMWH), which is biggest institute in country for holding records of maximum number of deliveries. Methods: A cross sectional study was conducted over a period of 3 months between March 2023 to May 2023 on 72 patients. Women with term pregnancy who experienced primary PPH were analyzed for different risk factors. Similarly, incidence of postpartum hemorrhage according to age, parity, gestational age, types of labor, types of vaginal delivery and causes of postpartum hemorrhage were studied. The results were then analyzed. Results: The incidence of primary PPH during the study was 3%. Majority of cases of PPH were in age group of 20-24 (44.4%), followed by age group (25-29). Most of cases (50%) were of gravidity 2 to 3, followed by primigravida (45.8%). There was equal distribution of PPH in gestation age (37-39+6) WOG to (40-41+6) WOG. There were no risk factors associated with occurrence of PPH in 56%. Hypertensive disorder of pregnancy, anemia, APH, multiple pregnancy, fetal macrosomia, polyhydramnios and obesity are associated risk factors for PPH. Among risk factors associated with PPH, hypertensive disorder of pregnancy was most common risk factors (40.6%), followed by maternal anemia (25%), multiple pregnancy (12.5%), APH (6.3%) fetal macrosomia (6.3%), maternal obesity (6.3%), polyhydramnios (3.1%). PPH was more common in augmented labor (43%), followed by induced labor (29.2%) and spontaneous labor (27.8%). In this study most women ( 72.2%) experienced blood loss of 500-1000 ml. And most common cause of PPH was atony (83.3%) followed by genital tract injury (14%) and retained tissues (2.7%). Conclusions: In many cases, PPH can’t be predicted fully as many cases of PPH occur without vivid risk factors, as in this study 56% women experiencing PPH had no associated antenatal risk factors. Antenatal risk factors like hypertensive disorder of pregnancy, maternal anemia, twin pregnancy, APH, macrosomia, obesity are common risk factors for PPH. Similarly induced and augmented labor and instrumental delivery can lead to PPH. Keywords: Postpartum haemorrhage, risk factors, vaginal delivery