http://www.clinicalmicrobiologyandinfection.com/article/S1198743X21006364/pdf

Predictors and microbiology of respiratory and bloodstream bacterial infection in patients with COVID-19: living rapid review update and meta-regression

Acute kidney injury and renal replacement therapy in COVID-19 patients: A systematic review and meta-analysis.

Klebsiella pneumoniae has become the number one bacterial pathogen that causes high mortality in clinical settings worldwide. Clinical K. pneumoniae strains with carbapenem resistance and/or hypervirulent phenotypes cause higher mortality comparing with classical K. pneumoniae strains. Rapid differentiation of clinical K. pneumoniae with high resistance/hypervirulence from classical K. pneumoniae would allow us to develop rational and timely treatment plans. In this study, we developed a convolution neural network (CNN) as a prediction method using Raman spectra raw data for rapid identification of ARGs, hypervirulence-encoding factors and resistance phenotypes from K. pneumoniae strains. A total of 71 K. pneumoniae strains were included in this study. The minimum inhibitory concentrations (MICs) of 15 commonly used antimicrobial agents on K. pneumoniae strains were determined. Seven thousand four hundred fifty-five spectra were obtained using the InVia Reflex confocal Raman microscope and used for deep learning-based and machine learning (ML) algorithms analyses. The quality of predictors was estimated in an independent data set. The results of antibiotic resistance and virulence-encoding factors identification showed that the CNN model not only simplified the classification system for Raman spectroscopy but also provided significantly higher accuracy to identify K. pneumoniae with high resistance and virulence when compared with the support vector machine (SVM) and logistic regression (LR) models. By back-testing the Raman-CNN platform on 71 K. pneumoniae strains, we found that Raman spectroscopy allows for highly accurate and rationally designed treatment plans against bacterial infections within hours. More importantly, this method could reduce healthcare costs and antibiotics misuse, limiting the development of antimicrobial resistance and improving patient outcomes.

Identification of antibiotic resistance and virulence-encoding factors in Klebsiella pneumoniae by Raman spectroscopy and deep learning.

The novel coronavirus disease-2019 (COVID-19) is caused by a positive-sense single-stranded RNA virus which belongs to the Coronaviridae family. In March 2019 the World Health Organization declared that COVID-19 was a pandemic. COVID-19 patients typically have a fever, dry cough, dyspnea, fatigue, and anosmia. Some patients also report gastrointestinal (GI) symptoms, including diarrhea, nausea, vomiting, and abdominal pain, as well as liver enzyme abnormalities. Surprisingly, many studies have found severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA in rectal swabs and stool specimens of asymptomatic COVID-19 patients. In addition, viral receptor angiotensin-converting enzyme 2 and transmembrane protease serine-type 2, were also found to be highly expressed in gastrointestinal epithelial cells of the intestinal mucosa. Furthermore, SARS-CoV-2 can dynamically infect and replicate in both GI and liver cells. Taken together these results indicate that the GI tract is a potential target of SARS-CoV-2. Therefore, the present review summarizes the vital information available to date on COVID-19 and its impact on GI aspects.

Current understanding of the impact of COVID-19 on gastrointestinal disease: Challenges and openings.

Purpose: To investigate antimicrobial resistance and risk factors for mortality of Klebsiella pneumoniae (KP) pneumonia in diabetics and nondiabetics. Patients and methods: A retrospective study was conducted among inpatients of KP pneumonia via electronic medical records in a territory hospital between January 2016 and June 2018. Antimicrobial resistance in KP pneumonia was compared between diabetics and nondiabetics. Independent risk factors for mortality in KP pneumonia were identified by univariate and multivariate logistic regression among diabetics and nondiabetics separately. Results: In this study, 456 patients with KP pneumonia were included. There were 156 cases with diabetes and 300 without diabetes. KP showed a lower antimicrobial resistance to a multitude of antimicrobials in pneumonia among diabetics than nondiabetics, namely aztreonam, cefotetan, sulperazone, meropenem, amikacin, tobramycin, sulfamethoxazole, and fosfomycin. In addition, carbapenem-resistant Klebsiella pneumoniae (CRKP) was more prevalent among nondiabetics than diabetics who were admitted to intensive care unit (ICU) (63.0% vs 45.1%, P = 0.038). Multivariable analysis showed that independent risk factors for in-hospital mortality (IHM) in KP pneumonia among diabetics differed from that among nondiabetics as well. Independent predictors for IHM of KP pneumonia among diabetics were male (OR: 5.89, 95% CI: 1.34-25.93, P = 0.019), albumin (ALB) < 35 g/L (OR: 7.00, 95% CI: 2.02-24.28, P = 0.002), bloodstream infection (BSI) (OR: 21.14, 95% CI: 3.18-140.72, P = 0.002), and invasive ventilation during hospitalization (OR: 8.00, 95% CI: 2.99-21.42, P < 0.001). In nondiabetics, independent predictors were higher CURB-65 score (OR: 1.92, 95% CI: 1.29-2.86, P = 0.001), CRKP (OR: 2.72, 95% CI: 1.07-6.90, P = 0.035), BSI (OR: 4.98, 95% CI: 1.34-18.50, P = 0.017), and ICU admission (OR: 4.06, 95% CI: 1.57-10.47, P = 0.004). Conclusion: In KP pneumonia, diabetics showed lower antimicrobial resistance and different independent risk factors for mortality compared with nondiabetics, in line with previous studies. Importantly, further attention should be paid on rational and effective antibiotic and supportive treatments in order to reduce mortality without aggravating antimicrobial resistance and metabolic damage among diabetics.

/pdf/antimicrobial-resistance-and-risk-factors-for-mortality-of-3hau4y7una.pdf

Antimicrobial resistance and risk factors for mortality of pneumonia caused by Klebsiella pneumoniae among diabetics: a retrospective study conducted in Shanghai, China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) emerged in December 2019 and has spread globally. Diabetics are at increased risk of infections caused by a variety of pathogens including viruses. The present research aims to describe clinical characteristics and outcomes of COVID-19 patients with diabetes. METHODS: A retrospective multicenter study of COVID-19 patients with diabetes was conducted in four hospitals in Wuhan, Shanghai, and Anhui Province. Reverse transcription polymerase chain reaction or next-generation sequencing was carried out to confirm the existence of severe acute respiratory syndrome coronavirus 2 from respiratory specimens. RESULTS: A total of 54 diabetics (10.36%) were recruited from among 521 COVID-19 patients, with a median age of 63 (interquartile range, 52-70) years. Among them, 51 had been previously diagnosed with diabetes and 3 had been newly diagnosed based on glycosylated hemoglobin over 6.5%. For COVID-19, 47 of the 54 patients had an exposure history. Fever (47/54, 87.04%), dry cough (36/54, 66.67%), and expectoration (21/53, 39.62%) were among the top three symptoms. Lung infiltration was bilateral (46/52, 88.46%) and multilobe (47/52, 90.38%), and ground-glass opacity (36/37, 97.30%) was the most common pattern in radiological images. Moreover, COVID-19 patients with diabetes were prone to be classified as severe or critical cases (46.30%, 25/54) and had complications such as acute lung injury, acute respiratory distress syndrome, and acute kidney injury. The proportions of intensive care unit (ICU) admissions and deaths among the COVID-19 diabetics were 14.81% (8/54) and 12.96% (7/54), respectively. CONCLUSIONS: With older age, diabetics diagnosed as having COVID-19 were prone to develop into severe cases and exhibited a high rate of ICU admission and mortality.

Clinical characteristics and outcomes of coronavirus disease 2019 infections among diabetics: A retrospective and multicenter study in China.

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Antimicrobial resistance and risk factors for mortality of pneumonia caused by Klebsiella pneumoniae among diabetics: a retrospective study conducted in Shanghai, China.

Clinical characteristics and outcomes of coronavirus disease 2019 infections among diabetics: A retrospective and multicenter study in China.