The annual trend in the MDR rate in <i>A</i>. <i>baumannii</i> complex bacteremia from January 2009 to December 2013.

<p>The annual trend in the MDR rate in <i>A</i>. <i>baumannii</i> complex bacteremia from January 2009 to December 2013.</p

The distribution of <i>A</i>. <i>baumannii</i> complex isolates from blood samples with their MDR constituent ratios across different hospital department.

<p>ICU, intensive care unit; GSD, general surgery department; NSD, neurosurgery department; HD, hematological department; TSD, thoracic neurosurgery department; NepD, nephrological department; GD, gastroenterological department; OrD, orthopedics department; NeuD, neurological department; USD, urinary neurosurgery department; OnD, oncological department; ED, emergency department; ID, infectious department; BD, burn department; PnD, pneumological department; CD, cardiological department; DD, dermatological department; PsD, psychiatry department.</p

Risk and Prognostic Factors for Multidrug-Resistant <i>Acinetobacter Baumannii</i> Complex Bacteremia: A Retrospective Study in a Tertiary Hospital of West China

<div><p>Background</p><p>The increasing prevalence and mortality of multidrug-resistant (MDR) <i>Acinetobacter baumannii</i> complex-associated infections, especially bacteremia, in health care settings poses a great threat to public health. We proceeded to investigate the risk and prognostic factors for MDR <i>A</i>. <i>baumannii</i> complex bacteremia in mainland China.</p><p>Methods</p><p>This retrospective study was conducted at West China Hospital from January 2009 to December 2013. Using a computer-assisted microbiology laboratory database, patients with MDR <i>A</i>. <i>baumannii</i> complex bacteremia were included as the case group, while those infected with non-MDR <i>A</i>. <i>baumannii</i> complex were selected as the control group. The clinical data were collected and analyzed.</p><p>Results</p><p>There were 241 non-duplicated <i>A</i>. <i>baumannii</i> complex blood isolates identified in our research, with the overall rate of multidrug resistance reaching 75.52% over the past five years. Using multivariate logistic analysis, being in the intensive care unit (ICU) (adjusted odds ratio [aOR], 5.84; 95% confidence interval [CI], 1.67-20.44), increased Pittsburgh bacteremia score (aOR, 6.55; 95% CI, 1.27-33.70) and use of carbapenem (aOR, 8.90; 95% CI, 1.71-46.30) were independent risk factors for MDR acquisition among patients with <i>A</i>. <i>baumannii</i> complex bacteremia. Older age (aOR, 1.02; 95% CI, 1.00-1.04), being post-transplantation (aOR, 5.21; 95% CI, 1.13-24.04), having a higher Pittsburgh bacteremia score (aOR, 2.19; 95% CI, 1.08-4.47) and having a lower level of albumin (aOR, 0.93; 95% CI, 0.88-0.99) were identified as independent risk factors for 30-day mortality in patients with MDR <i>A</i>. <i>baumannii</i> complex bacteremia.</p><p>Conclusion</p><p>In conclusion, our research revealed the risk factors associated with acquisition of and mortality from MDR <i>A</i>. <i>baumannii</i> complex bacteremia, which may be used to prioritize infection control practices and prognostic evaluations.</p></div

Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples

BACKGROUND: COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. METHODS: We applied a novel multiplex PCR amplicon (amplicon)-based and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. RESULTS: We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. CONCLUSIONS: This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses