Evidence map›Paper›PMID 38707171›Full record

ArticleCureus2024

Antimicrobial Resistance Profile in ICU Patients Across India: A Multicenter, Retrospective, Observational Study.

Vandana Verma, Chithra Valsan, Preety Mishra, Kalpana Mund, Soma Dutta, Geethanjali Anke, Harsha Sasi, Dhara Shah

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Vandana VermaDepartment of Microbiology, Christian Medical College & Hospital, Ludhiana, IND.
Chithra ValsanDepartment of Microbiology, Jubilee Mission Medical College and Research Institute, Thrissur, IND.
Preety MishraDepartment of Microbiology, Kalinga Institute of Medical Sciences, Bhubaneswar, IND.
Kalpana MundDepartment of Microbiology, Kalinga Institute of Medical Sciences, Bhubaneswar, IND.
Soma DuttaDepartment of Microbiology, Apollo Multispeciality Hospitals, Kolkata, IND.
Geethanjali AnkeDepartment of Microbiology, KIMS SAVEERA Hospital, Anantapur, IND.
Harsha SasiDepartment of Medical Affairs, Viatris, India, Bangalore, IND.
Dhara ShahDepartment of Medical Affairs, Viatris, India, Bangalore, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The pattern of antimicrobial resistance (AMR) changes with time and varies in countries and between hospitals within the same country. Physicians might thus benefit from information on regional resistance patterns of clinically significant bacterial isolates when deciding on the best empirical treatment. Numerous nosocomial infections are caused by multidrug-resistant (MDR) strains, notably methicillin-resistant Staphylococcus aureus (MRSA) strains, which are also linked to higher morbidity and death. Aim Evaluation of AMR profile in intensive care unit (ICU) patients of multiple tertiary care centers across India. Methods This was a multicenter, retrospective study based on electronic laboratory records of microbial isolates from clinical specimens from ICUs analyzed at microbiology laboratories of identified hospitals. Data of invasive sample records was collected from Microbiology labs of the identified hospitals within India and were aligned to WHO 5 Net standard reporting and as per Clinical & Laboratory Standards Institute (CLSI-2014) Guidelines for assessment. Data from 21556 samples were collected retrospectively from December 2021 to January 2010. Antibiotic susceptibility testing was done by using both the Kirby Baur disk diffusion method and the automated method (using the Vitek 2 compact system) as per CLSI (2014) guidelines. Results Of 21,556 enrolled patients, the majority (54.12%) were males and adults (62.07%). The median age was 58 years. Of 815 gram-positive bacteria reports, the commonest were S. aureus (552, 67.73%), Coagulase-negative Staphylococci (107, 13.13%), and Enterococcus spp. (105, 12.88%). For Coagulase-negative Staphylococci-positive samples, resistance was to penicillin (79, 73.83%), and erythromycin (73, 68.22%); and for S. aureus was to ciprofloxacin (361, 65.4%), and erythromycin (315,57.07%). Enterococcus spp. showed maximum resistance to erythromycin (73, 69.52%), followed by ampicillin, ciprofloxacin (68,64.76% each). Of 4,183 gram-negative bacteria reports, the commonest were Klebsiella pneumoniae (1,531, 36.6%), Escherichia coli (1,269, 30.34%), and Acinetobacter spp. (589, 14.08%), Pseudomonas aeruginosa (438, 14.08%), other Klebsiella spp. (174, 4.16%) and Enterobacter spp. (161, 3.85%). K. pneumoniae showed resistance to ciprofloxacin (1,001, 65.38%). E. coli showed resistance to ampicillin (918, 72.34%), and ciprofloxacin (798,62.88%); and Acinetobacter spp. to ceftazidime (525, 89.13%), and ciprofloxacin (507, 86.08%), while P. aeruginosa showed resistance to imipenem (234, 53.42%). Enterobacter spp. showed resistance to cefotaxime (129, 80.12%). MRSA samples showed resistance to phenoxymethylpenicillin (188, 35.54%) and benzylpenicillin (178, 33.46%). Conclusion Gram-negative bacteria were more common than gram-positive bacteria in causing antibiotic-resistant infections in ICU, with beta-lactams, fluoroquinolones, macrolides, and cephalosporins showing varied percentages of resistance. Fluoroquinolones, macrolides, and penicillin were noted to be highly resistant against gram-positive species. This indicates that evaluation based on MDR and antibiotic consumption patterns is imperative.

Indexed as

antimicrobial resistanceeskapegram negative bacteriagram positive bacteriamrsa

Identifiers

PMID38707171
PMCPMC11066456

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.