Maternal deaths in Sagamu in the new millennium: a facility-based retrospective analysis

BACKGROUND: Health institutions need to contribute their quota towards the achievement of the Millennium Development Goal (MDG) with respect to maternal health. In order to do so, current data on maternal mortality is essential for careproviders and policy makers to appreciate the burden of the problem and understand how best to distribute resources. This study presents the magnitude and distribution of causes of maternal deaths at the beginning of the 21st century in a Nigerian referral hospital and derives recommendations to reduce its frequency. METHODS: A retrospective descriptive analysis of all cases of maternal deaths at Olabisi Onabanjo University Teaching Hospital, Sagamu, Southwest Nigeria between 1 January 2000 to 30 June 2005. RESULTS: There were 75 maternal deaths, 2509 live births and 2728 deliveries during the study period. Sixty-three (84.0%) of the deaths were direct maternal deaths while 12 (16.0%) were indirect maternal deaths. Major causes of deaths were hypertensive disorders in pregnancy (28.0%), haemorrhage (21.3%) and sepsis (20.0%). Overall, eclampsia was the leading cause of deaths singly accounting for 24.0% of all maternal deaths. Abortion and HIV-related mortality accounted for 1.3% and 4.0% of maternal deaths, respectively. The maternal mortality ratio of 2989.2 per 100,000 live births was significantly higher than that reported for 1988–1997 in the same institution. Up to 67/794 (8.4%) patients referred from other facilities died compared to 8/1934 (0.4%) booked patients (OR: 22.1; 95% CI: 10.2–50.1). Maternal death was more likely to follow operative deliveries than non-operative deliveries (27/545 vs 22/2161; OR: 5.07; 95% CI: 2.77–9.31). CONCLUSION: At the middle of the first decade of the new millennium, a large number of pregnant women receiving care in this centre continue to die from preventable causes of maternal death. Adoption of evidence-based protocol for the management of eclampsia and improvement in the quality of obstetric care for unbooked emergencies would go a long way to significantly reduce the frequency of maternal deaths in this institution

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

Peer reviewe

Statistically Significant Difference in the First-trimester Fetal Heart Rate Between Genders?

Background: The study aims to establish the pattern of fetal heart rates in the first and second trimesters and determine whether there is a statistically significant difference in the first-trimester fetal heart rate (FHR) of males and females. Methods: This retrospective observational research is a study of FHRs measured at 11+0–13+6 wk and 18+0–23+6 wk, and ultrasound scan-diagnosed fetal sex at 18+0–23+6 wk. Singleton fetuses with nonambiguous external genitalia were recruited. The FHR was measured in B or M mode with Pulsed Wave Doppler, while ultrasound appearance of external genitalia determined the fetal sex at 18+0–23+6 wk. Student's t-test and Chi-square test were used for data analysis, and statistical significance was set at p &lt; 0.05. Results: A total of 2437 pregnancies meeting the study criteria were analyzed. The fetal sexes were 1398 (57.4%) males and 1039 (42.6%) females. There was no statistically significant difference in the first-trimester FHR between males and females (p = 0.74). However, females had higher mean FHR in both the first and second trimesters (First trimester: 165.4 ± 18.2 bpm vs 163.2 ± 17.1 bpm and Second trimester: 150.9 ±22.6 bpm vs 141.9 ±23.1 bpm). The FHR reduces with the increase in gestational age. Conclusion: There is no statistically significant difference in the first-trimester FHRs between sexes

Optimizing Fetal Outcomes in Twin-Twin-Transfusion Syndrome using Serial Amnioreduction in Resource-Constrained Unit: A Case Report

Background: Twin-twin transfusion syndrome is an important complication of monochorionic placentation in twin pregnancy. The management of this condition in Nigeria and many other developing countries has always been “watchful expectancy” with attendant high perinatal morbidity and mortality. Amnioreduction is a less demanding treatment option compared with fetoscopic laser coagulation management option in terms of cost and expertise, but has not been reported from any unit in Nigeria. Case Presentation: A 28-year-old gravid 2 para 1+0, 1 alive, carrying twin pregnancy was referred at 22 weeks gestation with complaint of mild discomfort due to sudden rapid enlargement of the abdomen. Physical examination and ultrasound scan assessment confirm Quintero stage II Twin-twin transfusion syndrome and she underwent serial amnioreduction at 24, 28 and 31 weeks of gestation with satisfactory outcomes. She had caesarean section at 33 weeks due to an acute episode of severe maternal discomfort and was delivered of 2 live female babies. There were no adverse perinatal events. Conclusion: This case presented demonstrates the role of amnioreduction in the management of carefully selected cases of twin-twin transfusion syndrome and further encouraged its utilization. in resource-constrained units instead of ‘watchful expectancy’ and in the absence of fetoscopic laser photocoagulatio

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

<p>Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.</p>

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available