Prevalence and Antibiotic Susceptibility of Gram-Negative Bacteria: A Study in ICU of Lahore General Hospital, Lahore with Mac Conkey Growth Medium
Bibliographic record
Abstract
Aim: Antibiotic sensitivity of gram-negative bacteria responsible for infections on Mac Conkey medium Methodology: Blood samples were cultured on MacConkey medium and antibiotic sensitivity was done by the technique called disk diffusion. Sample size: 200 subjects Duration of research: Four months i.e. 01-09-2022 to 31-12-2022 Results: 148 were gram-negative bacteria, 25 having growth of mixed types and there was no growth in 27cases. In 148 subjects, resistance for ceftriaxone, ceftazidime, imipenem, meropenem, and doxycycline was 79%, 75.6%, 58.7%, 65.5% and 51.3% respectively. Gram-negative bacteria had high resistance %age of cefotaxime and the low for doxycycline. Conclusion: By gram staining technique, cases were all gram-ve bacteria. A species of Klebsiella was originated frequently in blood sample i.e. 18.5%. Keywords: Incidence, antibiotic sensitivity, infection in blood, gram-ve species
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".