Metformin in pregnancy to avert gestational diabetes in women at high risk: Meta‐analysis of randomized controlled trials

Previous randomized and observational studies on the efficacy of metformin in pregnancy to reduce incident gestational diabetes mellitus (GDM) in women at high risk (obesity, polycystic ovary syndrome [PCOS], or pregestational insulin resistance) have been conflicting and several groups are planning further randomized controlled trials (RCTs) to answer this question conclusively. This work assesses the efficacy of metformin in pregnancy to avert one outcome—incident GDM in women at high risk. We included RCTs comparing metformin with usual care or placebo controls in terms of incident GDM and recruiting women at high risk during early pregnancy. Eleven eligible trials enrolled 2370 adult women whose intervention arm consisted of metformin started at conception or before 20 weeks of gestation. Risk of GDM was similar in intervention compared with controls (risk ratio [RR] 1.03; 95% confidence interval [CI], 0.85‐1.24). The data were of sufficient quality meeting the criteria for consistency and directness. We conclude that metformin does not contribute to averting the GDM outcome in women at high risk when initiated in pregnancy. The evidence provided by this synthesis affirms that further broad clinical trials investigating this question are no longer needed.     

Psychiatric morbidity in stroke patients attending a neurology clinic in Nigeria

Back ground

Stroke produces a wide range of mental and emotional disorders. Neuropsychiatric complications associated with stroke may have negative effects on the social functioning, overall quality of life and the recovery of motor functioning of stroke survivors.

Objective

To determine the prevalence and nature of psychiatric morbidity among stroke patients attending neurology outpatient clinic of the University of Ilorin Teaching Hospital (UITH), Ilorin-Nigeria.

Methods

All patients with stroke aged 18 years and above at an outpatient neurology clinic in Ilorin, Nigeria were assessed for mental and emotional disorders using the Schedule for Clinical Assessment in Neuropsychiatry (SCAN) over one year (March 2009 to February 2010).

Results

Overall prevalence of psychiatric morbidity was 36.0% (30/83) among 83 patients who constituted the study population. Specific diagnoses recorded were depression (19.2%), generalised anxiety disorder (9.6%), harmful alcohol use (2.4%); dementia, somatoform disorder, phobia and delusional disorder each had a prevalence of 1.2%. Clinical and sociodemographic variables were not significantly associated with psychiatric morbidity.

Conclusion

Psychiatric disorders are often associated with stroke. Identifying and treating stroke patients with these psychiatric co-morbidities could thus help to improve the overall quality of life of these patients.     

What Is the Mechanism of the Atrial Arrhythmia in a Patient After Orthotopic Heart Transplantation?

Atrial arrhythmias are quite common in patients after heart transplantation; they can occur via focal or reentrant mechanisms and are amenable to curative therapy with catheter ablation. Integration of the individual patient's surgical anatomy with the arrhythmia pattern on 12-lead electrocardiogram can help both to narrow the potential arrhythmia diagnoses and to facilitate therapeutic decision making. This case highlights the differential diagnosis and management of such a patient.     

Determining a continuous marker for sleep depth

Detection and quantification of sleep arousals is an important issue, as the frequent arousals are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep staging, electroencephalograph (EEG) is the core signal and based on the visual inspection of the frequency content of EEG, non-rapid eye movement sleep is staged into four somewhat rough categories. In this study, we aimed at developing a continuous marker based on a more rigorous spectral analysis of EEG to measure or quantify the depth of sleep. In order to develop such a marker, we obtained the time-frequency map of two EEG channels around sleep arousals and identified the frequency bands that show the most change during arousals. We then evaluated classification performance of the potential signals for representing the depth of sleep, using receiver operating characteristic analysis. Our comparisons based on the area under the curve values revealed that the sum of absolute powers in alpha and beta bands is a good continuous marker to represent the depth of sleep. Higher values of this marker indicate low-quality sleep and vice versa. We believe that use of this marker will lead to a better quantification of sleep quality.     

Gene expression profile class prediction using linear Bayesian classifiers

Due to recent advances in DNA microarray technology, using gene expression profiles, diagnostic category of tissue samples can be predicted with high accuracy. In this study, we discuss shortcomings of some existing gene expression profile classification methods and propose a new approach based on linear Bayesian classifiers. In our approach, we first construct gene-level linear classifiers to identify genes that provide high class-prediction accuracies, i.e., low error rates. After this screening phase, starting with the gene that offers the lowest error rate, we construct a multi-dimensional linear classifier by incorporating next best-performing genes, until the prediction error becomes minimum or 0, if possible. When we compared classification performance of our approach against prediction analysis of microarrays (PAM) and support vector machines (SVM) based approaches, we found that our method outperforms PAM and produces comparable results with SVM. In addition, we observed that the gene selection scheme of PAM could be misleading. Albeit SVM achieves relatively higher prediction performance, it has two major disadvantages: Complexity and lack of insight about important genes. Our intuitive approach offers competing performance and also an efficient means for finding important genes.