MIC versus MBEC to Determine the Antibiotic Sensitivity of <i>Staphylococcus aureus</i> in Peritoneal Dialysis Peritonitis
Bibliographic record
Abstract
BACKGROUND: Peritoneal dialysis (PD)-related peritonitis is a common and morbid complication of PD. Bacteria are able to create a biofilm on the PD catheter, which can be a source of recurrent infection. Biofilms undergo a phenotypic change resulting in increased antibiotic resistance. ♢ METHODS: 21 clinical isolates of different patients with PD peritonitis secondary to Staphylococcus aureus were collected. They were analyzed for their antibiotic susceptibility in the planktonic form using the standard minimum inhibitory concentration (MIC) and in a biofilm using minimum biofilm eradication concentration (MBEC). Chi-square was used to compare the sensitivity results. ♢ RESULTS: The isolates were susceptible to all the antibiotics tested using MIC. Every antibiotic except gentamicin lost its efficacy when the bacteria were grown in a biofilm (p > 0.05). The change in susceptibility was statistically significant to a level of p < 0.001 for all antibiotics tested. ♢ DISCUSSION: In PD peritonitis that is long standing, recurrent, or not responsive to therapy, MBEC testing should be considered as a biofilm may be present. Gentamicin should be strongly considered over other agents for empiric gram-negative coverage as it may be providing synergy in the setting of Staphylococcus aureus. Also, the newer anti-staphylococcal drugs should be tested for their performance in a biofilm using the MBEC method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".