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In this study, we examined the cellular infectivity and ultrastructural changes due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the various cells of bronchoalveolar fluid (BALF) from intubated patients of different age groups (≥60 years and <60 years) and with common comorbidities such as diabetes, liver and kidney diseases, and malignancies. BALF of 79 patients (38 cases >60 and 41 cases <60 years) were studied by light microscopy, immunofluorescence, scanning, and transmission electron microscopy to evaluate the ultrastructural changes in the ciliated epithelium, type II pneumocytes, macrophages, neutrophils, eosinophils, lymphocytes, and anucleated granulocytes. This study demonstrated relatively a greater infection and better preservation of subcellular structures in these cells from BALF of younger patients (<60 years compared with the older patients (≥60 years). The different cells of BALF from the patients without comorbidities showed higher viral load compared with the patients with comorbidities. Diabetic patients showed maximum ultrastructural damage in BALF cells in the comorbid group. This study highlights the comparative effect of SARS-CoV-2 infection on the different airway and inflammatory cells of BALF at the subcellular levels among older and younger patients and in patients with comorbid conditions.
Background: Linezolid an oxazolidinone drug available in both parenteral and oral formulations has emerged as a novel alternative to vancomycin and other second-generation drugs for the treatment of infections from gram-positive cocci. Clinical isolates of linezolid-resistant staphylococci and enterococci were reported. Since then, linezolid-resistant strains have become an increasing problem worldwide. The most frequently reported mechanisms of linezolid resistance include the mutation in 23S ribosomal nucleic acid and presence of cfr gene. Methicillin-resistant coagulase-negative staphylococci (MR-CoNS) and vancomycin-resistant Enterococcus (VRE) have become a worrisome clinical problem. Objective: Therefore, we aimed to determine the distribution of linezolid-resistant strains in an inpatient setting of a tertiary-care hospital in India and to evaluate the resistance mechanisms among these isolates. In addition, the clonal diversity of the isolates was determined by pulsed-field gel electrophoresis (PFGE). Methods: The distribution, clonal diversity, and resistance mechanism of linezolid resistant-Staphylococcus haemolyticus (LRSH) strains were determined. The isolates were identified by MALDI-TOF. The mechanism of resistance was determined by sequence analysis of the domain V of 23SrRNA and screening for cfr gene. Clonal relatedness was defined by PFGE. Results: In total, 13 LRSH isolates were recovered from pus specimens. The 13 LRSH strains isolated had an linezolid MIC of 256 g/mL. Sequencing results revealed G2576T mutations in 7 (53.8%), G2447U in 4 (30.7%) and C2534U in 1 (7.6%) isolate of S. haemolyticus. One isolate of S. haemolyticus showed 2 simultaneous mutations (G2576T and G2447U) in the domain V region of 23Sr RNA gene. PFGE of the LR-SH isolates revealed the presence of 11 clones. Of the 11 clones, clones I and II had 2 isolates each. Isolates of clone I exhibited a band pattern identical with the previous isolates of LRSH isolated from the orthopedic unit. Similarly, isolates of clone II also shared the same band pattern with the previous LRSH isolates from the dermatology unit of our center. Conclusions: This study highlights the importance of continuous monitoring of vigilance of linezolid resistance in staphylococci. Rationalizing the use of linezolid and implementing methods to control the spread of hospital clones is of paramount importance to prevent further dissemination of these strains.
Background: Healthcare-associated infections (HAIs) are a major global threat to patient safety. Systematic surveillance is crucial for understanding HAI rates and antimicrobial resistance trends and to guide infection prevention and control (IPC) activities based on local epidemiology. In India, no standardized national HAI surveillance system was in place before 2017. Methods: Public and private hospitals from across 21 states in India were recruited to participate in an HAI surveillance network. Baseline assessments followed by trainings ensured that basic microbiology and IPC implementation capacity existed at all sites. Standardized surveillance protocols for central-line–associated bloodstream infections (CLABSIs) and catheter-associated urinary tract infections (CAUTIs) were modified from the NHSN for the Indian context. IPC nurses were trained to implement surveillance protocols. Data were reported through a locally developed web portal. Standardized external data quality checks were performed to assure data quality. Results: Between May 2017 and April 2019, 109 ICUs from 37 hospitals (29 public and 8 private) enrolled in the network, of which 33 were teaching hospitals with >500 beds. The network recorded 679,109 patient days, 212,081 central-line days, and 387,092 urinary catheter days. Overall, 4,301 bloodstream infection (BSI) events and 1,402 urinary tract infection (UTI) events were reported. The network CLABSI rate was 9.4 per 1,000 central-line days and the CAUTI rate was 3.4 per 1,000 catheter days. The central-line utilization ratio was 0.31 and the urinary catheter utilization ratio was 0.57. Moreover, 3,542 (73%) of 4,742 pathogens reported from BSIs and 868 (53%) of 1,644 pathogens reported from UTIs were gram negative. Also, 1,680 (26.3%) of all 6,386 pathogens reported were Enterobacteriaceae. Of 1,486 Enterobacteriaceae with complete antibiotic susceptibility testing data reported, 832 (57%) were carbapenem resistant. Of 951 Enterobacteriaceae subjected to colistin broth microdilution testing, 62 (7%) were colistin resistant. The surveillance platform identified 2 separate hospital-level HAI outbreaks; one caused by colistin-resistant K. pneumoniae and another due to Burkholderia cepacia. Phased expansion of surveillance to additional hospitals continues. Conclusions: HAI surveillance was successfully implemented across a national network of diverse hospitals using modified NHSN protocols. Surveillance data are being used to understand HAI burden and trends at the facility and national levels, to inform public policy, and to direct efforts to implement effective hospital IPC activities. This network approach to HAI surveillance may provide lessons to other countries or contexts with limited surveillance capacity.
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