To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
Background: Globally, surgical site infections (SSIs) not only complicate the surgeries but also lead to $5–10 billion excess health expenditures, along with the increased length of hospital stay. SSI rates have become a universal measure of quality in hospital-based surgical practice because they are probably the most preventable of all healthcare-associated infections. Although, many national regulatory bodies have made it mandatory to report SSI rates, the burden of SSI is still likely to be significant underestimated due to truncated SSI surveillance as well as underestimated postdischarge SSIs. A WHO survey found that in low- to middle-income countries, the incidence of SSIs ranged from 1.2 to 23.6 per 100 surgical procedures. This contrasted with rates between 1.2% and 5.2% in high-income countries. Objectives: We aimed to leverage the existing surveillance capacities at our tertiary-care hospital to estimate the incidence of SSIs in a cohort of trauma patients and to develop and validate an indigenously developed, electronic SSI surveillance system. Methods: A prospective cohort study was conducted at a 248-bed apex trauma center for 18 months. This project was a part of an ongoing multicenter study. The demographic details were recorded, and all the patients who underwent surgery (n = 770) were followed up until 90 days after discharge. The associations of occurrence of SSI and various clinico-microbiological variables were studied. Results: In total, 32 (4.2%) patients developed SSI. S. aureus (28.6%) were the predominant pathogen causing SSI, followed by E. coli (14.3%) and K. pneumoniae (14.3%). Among the patients who had SSI, higher SSI rates were associated in patients who were referred from other facilities (P = .03), had wound class-CC (P < .001), were on HBOT (P = .001), were not administered surgical antibiotics (P = .04), were not given antimicrobial coated sutures (P = .03) or advanced dressings (P = .02), had a resurgery (P < .001), had a higher duration of stay in hospital from admission to discharge (P = .002), as well as from procedure to discharge (P = .002). SSI was cured in only 16 patients (50%) by 90 days. SSI data collection, validation, and analyses are essential in developing countries like India. Thus, it is very crucial to implement a surveillance system and a system for reporting SSI rates to surgeons and conduct a robust postdischarge surveillance using trained and committed personnel to generate, apply, and report accurate SSI data.
Resistance to colistin, a last resort antibiotic, has emerged in India. We investigated colistin-resistant Klebsiella pneumoniae(ColR-KP) in a hospital in India to describe infections, characterize resistance of isolates, compare concordance of detection methods, and identify transmission events.
Retrospective observational study.
Case-patients were defined as individuals from whom ColR-KP was isolated from a clinical specimen between January 2016 and October 2017. Isolates resistant to colistin by Vitek 2 were confirmed by broth microdilution (BMD). Isolates underwent colistin susceptibility testing by disk diffusion and whole-genome sequencing. Medical records were reviewed.
Of 846 K. pneumoniae isolates, 34 (4%) were colistin resistant. In total, 22 case-patients were identified. Most (90%) were male; their median age was 33 years. Half were transferred from another hospital; 45% died. Case-patients were admitted for a median of 14 days before detection of ColR-KP. Also, 7 case-patients (32%) received colistin before detection of ColR-KP. All isolates were resistant to carbapenems and susceptible to tigecycline. Isolates resistant to colistin by Vitek 2 were also resistant by BMD; 2 ColR-KP isolates were resistant by disk diffusion. Moreover, 8 multilocus sequence types were identified. Isolates were negative for mobile colistin resistance (mcr) genes. Based on sequencing analysis, in-hospital transmission may have occurred with 8 case-patients (38%).
Multiple infections caused by highly resistant, mcr-negative ColR-KP with substantial mortality were identified. Disk diffusion correlated poorly with Vitek 2 and BMD for detection of ColR-KP. Sequencing indicated multiple importation and in-hospital transmission events. Enhanced detection for ColR-KP may be warranted in India.