Nosocomial Infections and Epidemiology of Antibiotic Resistance in Teaching Hospitals in South East of Iran
Bibliographic record
Abstract
AIM: Antibiotic resistance as one of the most serious health threats worldwide leading to a high rate of morbidity and mortality. The aim of present study was to examine the prevalence of nosocomial infections (NIs) and pattern of antibiotic resistance in teaching hospitals in Iran. METHODS: This cross-sectional descriptive study was conducted in a period of one year in three teaching hospitals and all patients with suspected NIs symptoms were chooses. Among these patients who showed antibiotic resistance were included in the study. The samples for clinical test in laboratory were obtained with using standard methods and aseptic technique by trained personnel. Antibiotic susceptibility testing was performed by Kirby-Bauer's disk diffusion method on Muller-Hinton agar (Hi Media, Mumbai, India) in accordance with the standards of the Clinical Laboratory Standards Institute. RESULTS: During one year study, 561 patients with nosocomial infections were recognized and among them 340 patients (60.6%) showed some level of antibiotic resistance. The most common cause of NIs in present study was Acinetobacter and the most type of infection was respiratory system infections (52.7%). The highest resistance rate was against Ciprofloxacin (61.8%) followed by Imipenem (50.3%). CONCLUSION: Rate of NIs and antibiotics resistance is high in Iranian hospital. So Iranian health ministry should provide guideline and suitable programs for prevention of NIs and antibiotic therapy in hospitals.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".