Observational study to assess prescription cost and its relation to the socioeconomic status of the patients in psychiatry outpatient department in a tertiary care hospital

Background: To analyse the cost of prescriptions and to determine the relationship between socioeconomic status of the patients and the cost of prescriptions.Methods: A prospective, observational study was conducted in psychiatry OPD of a tertiary care hospital from August 2007 to January 2008. 300 patients of either sex and irrespective of age suffering from mental disorders were included. Information about the socioeconomic status of the patient was analysed on the basis of Kuppuswami’s socioeconomic status scale (updated for 2007). Cost analysis (calculated for 30 days) was done by calculating (a) average cost of the prescription borne by the hospital (b) average cost of the prescription borne by the patient and (c) average total cost of the prescription. The correlation between the socioeconomic score of the patients with the above three cost parameters was carried out using the Spearman rank correlation.Results: In a cohort of 300 patients, 61.3% patients belong to upper lower class. Cost analysis showed that the average total cost of the prescription was 121.97 INR of which average cost of the prescription borne by the hospital and the patients was 18.43 INR and 103.54 INR respectively. The total cost of the prescription and cost of prescription borne by the patient had a positive correlation with the socioeconomic score of the patient, while the cost of prescription borne by the hospital was inversely correlated with the socioeconomic score of the patient.Conclusions: It seems that the prescribing decision was influenced by the socioeconomic status of the patients.

A hybrid multiscale Monte Carlo algorithm (HyMSMC) to cope with disparity in time scales and species populations in intracellular networks

<p>Abstract</p> <p>Background</p> <p>The fundamental role that intrinsic stochasticity plays in cellular functions has been shown via numerous computational and experimental studies. In the face of such evidence, it is important that intracellular networks are simulated with stochastic algorithms that can capture molecular fluctuations. However, separation of time scales and disparity in species population, two common features of intracellular networks, make stochastic simulation of such networks computationally prohibitive. While recent work has addressed each of these challenges separately, a generic algorithm that can <it>simultaneously </it>tackle disparity in time scales <it>and </it>population scales in stochastic systems is currently lacking. In this paper, we propose the hybrid, multiscale Monte Carlo (HyMSMC) method that fills in this void.</p> <p>Results</p> <p>The proposed HyMSMC method blends stochastic singular perturbation concepts, to deal with potential stiffness, with a hybrid of exact and coarse-grained stochastic algorithms, to cope with separation in population sizes. In addition, we introduce the computational singular perturbation (CSP) method as a means of systematically partitioning fast and slow networks and computing relaxation times for convergence. We also propose a new criteria of convergence of fast networks to stochastic low-dimensional manifolds, which further accelerates the algorithm.</p> <p>Conclusion</p> <p>We use several prototype and biological examples, including a gene expression model displaying bistability, to demonstrate the efficiency, accuracy and applicability of the HyMSMC method. Bistable models serve as stringent tests for the success of multiscale MC methods and illustrate limitations of some literature methods.</p

Importance of Explicit Vectorization for CPU and GPU Software Performance

Much of the current focus in high-performance computing is on multi-threading, multi-computing, and graphics processing unit (GPU) computing. However, vectorization and non-parallel optimization techniques, which can often be employed additionally, are less frequently discussed. In this paper, we present an analysis of several optimizations done on both central processing unit (CPU) and GPU implementations of a particular computationally intensive Metropolis Monte Carlo algorithm. Explicit vectorization on the CPU and the equivalent, explicit memory coalescing, on the GPU are found to be critical to achieving good performance of this algorithm in both environments. The fully-optimized CPU version achieves a 9x to 12x speedup over the original CPU version, in addition to speedup from multi-threading. This is 2x faster than the fully-optimized GPU version.Comment: 17 pages, 17 figure

Sewage effluent from an Indian hospital harbors novel carbapenemases and integron-borne antibiotic resistance genes

Background: Hospital wastewaters contain fecal material from a large number of individuals, of which many are undergoing antibiotic therapy. It is, thus, plausible that hospital wastewaters could provide opportunities to find novel carbapenemases and other resistance genes not yet described in clinical strains. Our aim was therefore to investigate the microbiota and antibiotic resistome of hospital effluent collected from the city of Mumbai, India, with a special focus on identifying novel carbapenemases. Results: Shotgun metagenomics revealed a total of 112 different mobile antibiotic resistance gene types, conferring resistance against almost all classes of antibiotics. Beta-lactamase genes, including encoding clinically important carbapenemases, such as NDM, VIM, IMP, KPC, and OXA-48, were abundant. NDM (0.9% relative abundance to 16S rRNA genes) was the most common carbapenemase gene, followed by OXA-58 (0.84% relative abundance to 16S rRNA genes). Among the investigated mobile genetic elements, class 1 integrons (11% relative abundance to 16S rRNA genes) were the most abundant. The genus Acinetobacter accounted for as many as 30% of the total 16S rRNA reads, with A. baumannii accounting for an estimated 2.5%. High throughput sequencing of amplified integron gene cassettes identified a novel functional variant of an IMP-type (proposed IMP-81) carbapenemase gene (eight aa substitutions) along with recently described novel resistance genes like sul4 and bla RSA1. Using a computational hidden Markov model, we detected 27 unique metallo-beta-lactamase (MBL) genes in the shotgun data, of which nine were novel subclass B1 genes, one novel subclass B2, and 10 novel subclass B3 genes. Six of the seven novel MBL genes were functional when expressed in Escherichia coli. Conclusion: By exploring hospital wastewater from India, our understanding of the diversity of carbapenemases has been extended. The study also demonstrates that the microbiota of hospital wastewater can serve as a reservoir of novel resistance genes, including previously uncharacterized carbapenemases with the potential to spread further

Management of venous thromboembolism in pregnancy

Venous thromboembolism (VTE) in pregnancy, consisting of deep venous thrombosis (DVT) and pulmonary embolism (PE), is a major factor of maternal mortality. Several patient-specific risk factors along with the physiologic changes of pregnancy promote a state of hypercoagulability in pregnant women. Detailed assessment of all pregnant women can establish a risk profile that would guide clinical decisions, and balance potential therapeutic benefits with side effects. Differentiating between physiologic changes of pregnancy and symptoms of VTE can be challenging and warrants meticulous clinical evaluation. Timely and accurate diagnosis of VTE with proper imaging is essential for its management, and systemic anticoagulation remains the cornerstone of VTE prevention and therapy. Furthermore, advanced invasive treatment options such as inferior vena cava filters and thrombectomy can be considered for complex cases. Importantly, the risk of systemic anticoagulation should be balanced against the risk of VTE-associated morbidity and mortality for mother and fetus, and an informed decision should be made. In this review, we present an up-to-date overview of VTE management in pregnancy and the postpartum period. Keywords: Anticoagulants; Deep venous thrombosis; Pregnancy; Pulmonary embolism; Venous thromboembolism