Recently, obstetric massive transfusion protocols have shifted toward early intervention. This study aimed to develop a prediction model for transfusion of ≥5 units of packed red blood cells (PRBCs) during cesarean section in women with placenta previa. We conducted a cohort study including 287 women with placenta previa who delivered between September 2011 and April 2018. Univariate and multivariate logistic regression analyses were used to test the association between clinical factors, ultrasound factors, and massive transfusion. For the external validation set, we obtained data (n=50) from another hospital. We formulated a scoring model for predicting transfusion of ≥5 units of PRBCs, including maternal age, degree of previa, grade of lacunae, presence of a hypoechoic layer, and anterior placentation. For example, total score of 223/260 had a probability of 0.7 for massive transfusion. Hosmer-Lemeshow goodness-of-fit test indicated that the model was suitable (p>0.05). The area under the receiver operating characteristics curve (AUC) was 0.922 [95% confidence interval (CI) 0.89-0.95]. In external validation, the discrimination was good, with an AUC value of 0.833 (95% CI 0.70-0.92) for this model. Nomogram calibration plots indicated good agreement between the predicted and observed outcomes, exhibiting close approximation between the predicted and observed probability. We constructed a scoring model for predicting massive transfusion during cesarean section in women with placenta previa. This model may help in determining the need to prepare an appropriate amount of blood products and the optimal timing of blood transfusion.

The increasing prevalence of advanced maternal age (AMA) births necessitates the exploration of associated pregnancy outcomes within the healthcare-limited context of northern Tanzania to elucidate potential region-specific risks and implications. This study explored the influence of AMA on pregnancy outcomes in northern Tanzania, where healthcare resources and infrastructure are constrained in comparison to developed countries. This cross-sectional hospital-based study utilized maternally linked data from the Kilimanjaro Christian Medical Center (KCMC) Medical Registry and included 32,798 women who delivered single infants between 2004 and 2013. Multiple logistic regression models were used to determine adjusted odds ratios (aORs) and 95 % confidence intervals (CIs) for AMA-associated adverse pregnancy outcomes. A total of 16 % of mothers belonged to AMA with increased odds of undergoing a cesarean section (aOR: 1.32; 95%CI [1.24-1.41]; P < 0.001), gestational diabetes (aOR: 13.16; 95%CI [3.28-52.86]; P < 0.001) or pregestational diabetes (aOR: 3.15; 95%CI [1.87-5.31]; P < 0.000), and developing pre-eclampsia (aOR: 1.63; 95%CI [1.41-1.89]; P < 0.000). More women with AMA reported alcohol use during pregnancy and had preexisting conditions before conception than did younger women. Maternal education level, employment status, urban residency, and Christianity were statistically significant. This study establishes a connection between AMA and higher odds of cesarean section, gestational diabetes, pregestational diabetes, and pre-eclampsia. Women with AMA were more inclined to consume alcohol during pregnancy and exhibited preexisting conditions before conception. Moreover, AMA was linked to increased odds of low birth weight, stillbirths, and NICU transfers.

Sarcopenia is defined as an age-related loss of skeletal muscle and is associated with several health disorders. Causes of sarcopenia, which included physical inactivity, alcohol, dietary habits, and smoking, have been researched. The present study was undertaken to examine the association between reproductive span and sarcopenia in Korean women. Data obtained from 2008 to 2011 Korea National Health and Nutrition Examination Surveys (KNHANES) were analyzed. We defined sarcopenia based on the cut-off values of the Foundation for the National Institutes of Health (FNIH) sarcopenia project criteria: ASM/BMI < 0.512 for women. Reproductive span was defined as years from menarche to menopause, and we divided the 3970 study subjects into three groups by reproductive span tertile. Multivariate logistic regression analysis was used to determine adjusted ORs for the relation between reproductive span and sarcopenia. The prevalence of sarcopenia in the study was 17.7% (704 of 3970). Multiple logistic regression analysis was performed using weighted populations. After adjusting for covariates, reproductive span was found to be inversely associated with the risk of sarcopenia [Tertile 1 = 1 (reference); Tertile 2, odds ratio (OR) = 0.927, 95% confidence interval (CI) = 0.863–0.995; Tertile 3, OR = 0.854, 95% CI = 0.793–0.915].

We aimed to determine the prevalence and factors associated with the use of long-acting reversible contraceptives (LARCs) among women of reproductive age in Tanzania. We analyzed the Tanzania Demographic and Health Survey (DHS) data from 2015 to 2016. The study included 8189 women aged 15–49 years. The relationship between various factors and LARC use was determined through various analyses. Among women with a partner/husband, 7.27% used LARCs, 21.07% were grand multiparous, and 20.56% did not desire more children. Women aged 36–49 years (adjusted odds ratio (AOR)-2.10, 95% confidence interval (CI): 1.11–3.96), who completed secondary education (AOR-1.64, 95% CI: 1.05–2.55), who did not desire more children (AOR-2.28, 95% CI: 1.53–3.41), with a partner with primary level education (AOR-2.02, 95% CI: 1.34–3.02), or living in richer households (AOR-1.60, 95% CI: 1.12–2.27) were more likely to use LARCs. Further, women with a partner who wanted more children were less likely to use LARCs (AOR-0.69, 95% CI: 0.54–0.90). Tanzania has a low LARC usage rate. Women’s age, wife and partner’s education status, couple’s desire for more children, and household wealth index influenced the use of LARCs, highlighting the need to reach more couples of lower socioeconomic status to improve LARC utilization.

Background: In general, early intervention in disease based on early diagnosis is considered to be very important for improving health outcomes. However, there is still insufficient evidence regarding how medical care that is based on the early diagnosis of confirmed cases can affect the outcome of COVID-19 treatment.Objective: We aimed to investigate the effect of the duration from the onset of clinical symptoms to confirmation of COVID-19 on the duration from the onset of symptoms to the resolution of COVID-19 (release from quarantine).Methods: For preliminary data collection, we performed data crawling to extract data from social networks, blogs, and official websites operated by local governments. We collected data from the 4002 confirmed cases in 33 cities reported up to May 31, 2020, for whom sex and age information could be verified. Subsequently, 2494 patients with unclear symptom onset dates and 1349 patients who had not been released or had no data about their release dates were excluded. Thus, 159 patients were finally included in this study. To investigate whether rapid confirmation reduces the prevalence period, we divided the duration from symptom onset to confirmation into quartiles of ≤1, ≤3, ≤6, and ≥7 days, respectively. We investigated the duration from symptom onset to release and that from confirmation to release according to these quartiles. Furthermore, we performed multiple regression analysis to investigate the effects of rapid confirmation after symptom onset on the treatment period, duration of prevalence, and duration until release from isolation.Results: We performed multiple regression analysis to investigate the association between rapid confirmation after symptom onset and the total prevalence period (faster release from isolation). The time from symptom onset to confirmation showed a negative association with the time from confirmation to release (t1=−3.58; P<.001) and a positive association with the time from symptom onset to release (t1=5.86; P<.001); these associations were statistically significant.Conclusions: The duration from COVID-19 symptom onset to confirmation date is an important variable for predicting disease prevalence, and these results support the hypothesis that a short duration of symptom onset to confirmation can reduce the time from symptom onset to release.

BACKGROUND In general, early intervention in disease based on early diagnosis is considered to be very important for improving health outcomes. However, there is still insufficient evidence regarding how medical care that is based on the early diagnosis of confirmed cases can affect the outcome of COVID-19 treatment. OBJECTIVE We aimed to investigate the effect of the duration from the onset of clinical symptoms to confirmation of COVID-19 on the duration from the onset of symptoms to the resolution of COVID-19 (release from quarantine). METHODS For preliminary data collection, we performed data crawling to extract data from social networks, blogs, and official websites operated by local governments. We collected data from the 4002 confirmed cases in 33 cities reported up to May 31, 2020, for whom sex and age information could be verified. Subsequently, 2494 patients with unclear symptom onset dates and 1349 patients who had not been released or had no data about their release dates were excluded. Thus, 159 patients were finally included in this study. To investigate whether rapid confirmation reduces the prevalence period, we divided the duration from symptom onset to confirmation into quartiles of ≤1, ≤3, ≤6, and ≥7 days, respectively. We investigated the duration from symptom onset to release and that from confirmation to release according to these quartiles. Furthermore, we performed multiple regression analysis to investigate the effects of rapid confirmation after symptom onset on the treatment period, duration of prevalence, and duration until release from isolation. RESULTS We performed multiple regression analysis to investigate the association between rapid confirmation after symptom onset and the total prevalence period (faster release from isolation). The time from symptom onset to confirmation showed a negative association with the time from confirmation to release (t1=−3.58; P<.001) and a positive association with the time from symptom onset to release (t1=5.86; P<.001); these associations were statistically significant. CONCLUSIONS The duration from COVID-19 symptom onset to confirmation date is an important variable for predicting disease prevalence, and these results support the hypothesis that a short duration of symptom onset to confirmation can reduce the time from symptom onset to release.