Resistance Pattern of Antibiotics in Patient Underwent Open Heart Surgery With Nosocomial Infection in North of Iran
Bibliographic record
Abstract
BACKGROUND: Patients who undergo cardiac surgery appear to be at increased risk for the development of Nosocomial infections (NIs). The development of antibiotic-resistant infections has been associated with significantly greater hospital mortality rates compared to similar infections caused by antibiotic-sensitive pathogens. OBJECTIVES: The purpose of this study is survey of Nis and antibiotic resistance patterns of causative bacteria among patients who underwent open heart surgery in the north of Iran during a 2-year period between September 2012 and September 2014. METHODS: In this cross-sectional study we evaluated 187 patients that underwent open heart surgery with NIs. Demographic feature, clinical characteristics and risk factors of each infection were recorded. The antibiotic susceptibility test was performed using the Minimum inhibitory concentration (MIC) method according to the standard protocol of Clinical & Laboratory Standards Institute (CLSI). Detection of Extended-spectrum beta-lactamase (ESBL) producing bacteria was performed by the double-disk synergy (DDS) test; also Methicillin-resistant Staphylococcus (MRSA) strains were identified by MRSA Screen Agar. The collected data were analyzed using the SPSS software (ver. 16) and, descriptive statistics were used. RESULTS: Out Of total of 2253 hospitalized patients who underwent open heart surgery, 187(5.05%) patients had NIs. 51.9% of the patients were female. The rates of surgical site infection (SSI), respiratory tract infection, endocarditis, Urinary tract infection (UTI), blood Infection and mediastinitis were 27.80, 25.66%, 17.64, 17.11% 8.55% and 3.20% respectively. E.coli and S.aureus were the most causative agents of NIs. The rate of ESBL-producing bacteria was 14.28- 71.42% among enterobacteriaceae and the rate of MRSA was 54.2% among S.aureus strains. All isolated Acinetobacter.spp were Multi-drug resistance (MDR). CONCLUSIONS: We showed that the rate of NIs among these high-risk patients was in the average level. But the emergence of MRSA and ESBL bacteria is increasing in our region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".