Healthcare-associated pneumonia among hospitalized patients in a Korean tertiary hospital

<p>Abstract</p> <p>Background</p> <p>Healthcare-associated pneumonia (HCAP) has more similarities to nosocomial pneumonia than to community-acquired pneumonia (CAP). However, there have only been a few epidemiological studies of HCAP in South Korea. We aimed to determine the differences between HCAP and CAP in terms of clinical features, pathogens, and outcomes, and to clarify approaches for initial antibiotic management.</p> <p>Methods</p> <p>We conducted a retrospective, observational study of 527 patients with HCAP or CAP who were hospitalized at Severance Hospital in South Korea between January and December 2008.</p> <p>Results</p> <p>Of these patients, 231 (43.8%) had HCAP, and 296 (56.2%) had CAP. Potentially drug-resistant (PDR) bacteria were more frequently isolated in HCAP than CAP (12.6% vs. 4.7%; <it>P </it>= 0.001), especially in the low-risk group of the PSI classes (41.2% vs. 13.9%; <it>P </it>= 0.027). In-hospital mortality was higher for HCAP than CAP patients (28.1% vs. 10.8%, <it>P </it>< 0.001), especially in the low-risk group of PSI classes (16.4% vs. 3.1%; <it>P </it>= 0.001). Moreover, tube feeding and prior hospitalization with antibiotic treatment within 90 days of pneumonia onset were significant risk factors for PDR pathogens, with odds ratios of 14.94 (95% CI 4.62-48.31; <it>P </it>< 0.001) and 2.68 (95% CI 1.32-5.46; <it>P </it>= 0.007), respectively.</p> <p>Conclusions</p> <p>For HCAP patients with different backgrounds, various pathogens and antibiotic resistance of should be considered, and careful selection of patients requiring broad-spectrum antibiotics is important when physicians start initial antibiotic treatments.</p

HIV-1 Polymerase Inhibition by Nucleoside Analogs: Cellular- and Kinetic Parameters of Efficacy, Susceptibility and Resistance Selection

Nucleoside analogs (NAs) are used to treat numerous viral infections and cancer. They compete with endogenous nucleotides (dNTP/NTP) for incorporation into nascent DNA/RNA and inhibit replication by preventing subsequent primer extension. To date, an integrated mathematical model that could allow the analysis of their mechanism of action, of the various resistance mechanisms, and their effect on viral fitness is still lacking. We present the first mechanistic mathematical model of polymerase inhibition by NAs that takes into account the reversibility of polymerase inhibition. Analytical solutions for the model point out the cellular- and kinetic aspects of inhibition. Our model correctly predicts for HIV-1 that resistance against nucleoside analog reverse transcriptase inhibitors (NRTIs) can be conferred by decreasing their incorporation rate, increasing their excision rate, or decreasing their affinity for the polymerase enzyme. For all analyzed NRTIs and their combinations, model-predicted macroscopic parameters (efficacy, fitness and toxicity) were consistent with observations. NRTI efficacy was found to greatly vary between distinct target cells. Surprisingly, target cells with low dNTP/NTP levels may not confer hyper-susceptibility to inhibition, whereas cells with high dNTP/NTP contents are likely to confer natural resistance. Our model also allows quantification of the selective advantage of mutations by integrating their effects on viral fitness and drug susceptibility. For zidovudine triphosphate (AZT-TP), we predict that this selective advantage, as well as the minimal concentration required to select thymidine-associated mutations (TAMs) are highly cell-dependent. The developed model allows studying various resistance mechanisms, inherent fitness effects, selection forces and epistasis based on microscopic kinetic data. It can readily be embedded in extended models of the complete HIV-1 reverse transcription process, or analogous processes in other viruses and help to guide drug development and improve our understanding of the mechanisms of resistance development during treatment

The MST-kNN with Paracliques

In this work, we incorporate new edges from a paraclique-identification approach to the output of theMST-kNN graph partitioning method. We present a statistical analysis of the results on a dataset originated from a computational linguistic study of 84 Indo-European languages. We also present results from a computational stylistic study of 168 plays of the Shakespearean era. For the latter, results of the Kruskal- Wallis test 1 (observed vs. all permutations) showed a p-value of a 1.62E- 11 and a Wilcoxon test a p-value of 8.1E-12. Overall, our results clearly show in both cases that the modified approach provides statistically more significant results than the use of the MST-kNN alone, thus providing a highly-scalable alternative and statistically sound approach for data clustering