Bacteriological profile of neonatal septicemia: A retrospective analysis from a tertiary care hospital in Loni
Bibliographic record
Abstract
Septicemia continues to be a major cause of neonatal mortality and morbidity worldwide. Epidemiology and surveillance of neonatal sepsis helps in implementation of rational empirical antibiotic strategy. To study the bacteriological profile and antibiotic sensitivity pattern and types of neonatal septicemia among the suspected blood & CSF samples coming to Microbiology Department of Pravara Rural Hospital. All the reports fulfilling the eligibility criteria were studied for Percentage of neonatal sepsis in suspected blood and CSF samples, Percentage of bacteriological sepsis (Gram-positive and Gramnegative sepsis), Bacterialogical profile, Percentage of EOS (Early Onset Sepsis) and LOS (Late Onset Sepsis) in confirmed cases, Antibiotic Sensitivity Tests. The study showed a culture positivity of 259 blood culture samples (23.31%) for bacterial growth out of 1111 and 36 (5.99%) positive out of 601 C.S.F culture samples. Early onset sepsis (92.54%) was found to be predominant with Klebsiella the predominant EOS pathogens and Coagulase Negative Staphylococci (CONS) as predominant LOS pathogen. Gram Negative sepsis (59.32%) predominated in this study. In this study the predominant organisms were found to be Klebsiella (28.81%). The antibiotic sensitivity testing showed that gram negative isolates were sensitive to Meropenem and gram positive isolates to Linezolid, Netilmicin and Chloramphenicol. The most common bacteria causing neonatal sepsis was found to be Klebsiella and the gram negative samples showed highest sensitivity for Meropenem and Cefazolin was found to be most resistant. The gram positive samples showed highest sensitivity for Linezolid and Penicillin and Ampicillin were found to be most resistant.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".