Increase in Penicillin and multidrug resistance in Streptococcus pneumoniae (1993-2016): report from a tertiary care hospital laboratory, Pakistan
Bibliographic record
Abstract
Background: Streptococcus pneumoniae is a major cause of morbidity and mortality worldwide. With the emergence of penicillin-resistant S. pneumoniae (PRSP), treatment has become challenging. The Clinical and Laboratory Standards Institute (CLSI) in 2008 revised its guidelines for S. pneumoniae and recommended separate penicillin breakpoints for meningeal and non-meningeal strains. Similar to penicillin’s, resistance to other classes of antibiotics has emerged globally. Objective: The objective of this study is to determine the trend of resistance to antimicrobials in S. pneumoniae infections and the impact of new CLSI guidelines on penicillin susceptibility among meningeal isolates. Methodology: Twenty-four years (1993-2016) data from S. pneumoniae isolates and their antimicrobial susceptibility was retrieved from the computerized database. Data was divided into two groups for analysis, pre-2008 and post 2008. Results: Penicillin resistance remained unchanged in non-meningeal isolates during both study periods. A significant rise in penicillin resistance in meningeal isolates was observed in the second period 2008-2016 (2.9% vs 36.2%). High resistance rates were observed for co-trimoxazole, tetracycline and erythromycin. Increased trend of multi-drug resistant (MDR) strains were also noted, from 11% in 1999 to 36% in 2016. Conclusion: The emergence of MDR strains is evident from our dataset. It seems like the rise in PRSP in meningeal isolates is due to revised CLSI guidelines. Overall low resistance to penicillin in non-meningeal isolates and no resistance to ceftriaxone is encouraging and will assist in drafting local guidelines. Cautious use of antimicrobials are essential to reduce further emergence of antimicrobial resistance in indigenous isolates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".