Factors influencing place of delivery : evidence from three south-Asian countries

Background High maternal mortality is still a significant public health challenge in many countries of the South-Asian region. The majority of maternal deaths occur due to pregnancy and deliveryrelated complications, which can mostly be prevented by safe facility delivery. Due to the paucity of existing evidence, our study aimed to examine the factors associated with place of delivery, including women's preferences for such in three selected South-Asian countries. Methods We extracted data from the most recent demographic and health surveys (DHS) conducted in Bangladesh (2014), Nepal (2016), and Pakistan (2017-18) and analyzed to identify the association between the outcome variable and socio-demographic characteristics. A total of 16,429 women from Bangladesh (4278; mean age 24.57 years), Nepal (3962; mean age 26.35 years), and Pakistan (8189; mean age 29.57 years) were included in this study. Following descriptive analyses, bivariate and multivariate logistic regressions were conducted. Results Overall, the prevalence of facility-based delivery was 40%, 62%, and 69% in Bangladesh, Nepal, and Pakistan, respectively. Inequity in utilizing facility-based delivery was observed for women in the highest wealth quintile. Participants from Urban areas, educated, middle and upper household economic status, and with high antenatal care (ANC) visits were significantly associated with facility-based delivery in all three countries. Interestingly, watching TV was also found as a strong determinant for facility-based delivery in Bangladesh (aOR = 1.31, 95% CI:1.09-1.56, P = 0.003), Nepal (aOR = 1.42, 95% CI:1.20-1.67, P<0.001) and Pakistan (aOR = 1.17, 95% CI: 1.03-1.32, P = 0.013). Higher education of husband was a significant predictor for facility delivery in Bangladesh (aOR = 1.73, 95% CI:1.27-2.35, P = 0.001) and Pakistan (aOR = 1.19, 95% CI: 0.99-1.43, P = 0.065); husband's occupation was also a significant factor in Bangladesh (aOR = 1.30, 95% CI:1.04-1.61, P = 0.020) and Nepal (aOR = 1.26, 95% CI:1.01-1.58, P = 0.041). Conclusion Our findings suggest that the educational status of both women and their husbands, household economic situation, and the number of ANC visits influenced the place of delivery. There is an urgent need to promote facility delivery by building more birthing facilities, training and deployment of skilled birth attendants in rural and hard-to-reach areas, ensuring compulsory female education for all women, encouraging more ANC visits, and providing financial incentives for facility deliveries. There is a need to promote facility delivery by encouraging health facility visits through utilizing social networks and continuing mass media campaigns. Ensuring adequate Government funding for free maternal and newborn health care and local community involvement is crucial for reducing maternal and neonatal mortality and achieving sustainable development goals in this region. © 2021 Rahman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Rahman” is provided in this record*

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Comprehensive Serum Profiling for the Discovery of Epithelial Ovarian Cancer Biomarkers

FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC = 0.933) and CA-125 (AUC = 0.907) were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800). To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912). Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the detection of ovarian cancer

3,3′-Diindolylmethane Induces G1 Arrest and Apoptosis in Human Acute T-Cell Lymphoblastic Leukemia Cells

Certain bioactive food components, including indole-3-carbinol (I3C) and 3,3′-diindolylmethane (DIM) from cruciferous vegetables, have been shown to target cellular pathways regulating carcinogenesis. Previously, our laboratory showed that dietary I3C is an effective transplacental chemopreventive agent in a dibenzo[def,p]chrysene (DBC)-dependent model of murine T-cell lymphoblastic lymphoma. The primary objective of the present study was to extend our chemoprevention studies in mice to an analogous human neoplasm in cell culture. Therefore, we tested the hypothesis that I3C or DIM may be chemotherapeutic in human T-cell acute lymphoblastic leukemia (T-ALL) cells. Treatment of the T-ALL cell lines CCRF-CEM, CCRF-HSB2, SUP-T1 and Jurkat with DIM in vitro significantly reduced cell proliferation and viability at concentrations 8- to 25-fold lower than the parent compound I3C. DIM (7.5 µM) arrested CEM and HSB2 cells at the G1 phase of the cell cycle and 15 µM DIM significantly increased the percentage of apoptotic cells in all T-ALL lines. In CEM cells, DIM reduced protein expression of cyclin dependent kinases 4 and 6 (CDK4, CDK6) and D-type cyclin 3 (CCND3); DIM also significantly altered expression of eight transcripts related to human apoptosis (BCL2L10, CD40LG, HRK, TNF, TNFRSF1A, TNFRSF25, TNFSF8, TRAF4). Similar anticancer effects of DIM were observed in vivo. Dietary exposure to 100 ppm DIM significantly decreased the rate of growth of human CEM xenografts in immunodeficient SCID mice, reduced final tumor size by 44% and increased the apoptotic index compared to control-fed mice. Taken together, our results demonstrate a potential for therapeutic application of DIM in T-ALL

<Book Reviews> Ingemar Fagerlind and Lawrence J Saha Education and National Development : A Comparative Perspective

textabstractVarious modeling methods have been proposed to estimate the potential predictive ability of polygenic risk variants that predispose to various common diseases. However, it is unknown whether differences between them affect their conclusions on predictive ability. We reviewed input parameters, assumptions and output of the five most common methods and compared their estimates of the area under the receiver operating characteristic (ROC) curve (AUC) using hypothetical data representing effect sizes and frequencies of genetic variants, population disease risk and number of variants. To assess the accuracy of the estimated AUCs, we aimed to reproduce the AUCs of published empirical studies. All methods assumed that the combined effect of genetic variants on disease risk followed a multiplicative risk model of independent genetic effects, but they either assumed per allele, per genotype or dominant/recessive effects for the genetic variants. Modeling strategy and input parameters differed. Methods used simulation analysis or analytical formulas with effect sizes quantified by odds ratios (ORs) or relative risks. Estimated AUC values were similar for lower ORs (0.7) due to variants with strong effects, differences in estimated AUCs between methods increased. The simulation methods accurately reproduced the AUC values of empirical studies, but the analytical methods did not. We conclude that despite differences in input parameters, the modeling methods estimate similar AUC for realistic values of the ORs. When one or more variants have stronger effects and AUC values are higher, the simulation methods tend to be more accurate