Dissociation of Pharmacokinetic-Pharmacodynamic Success and Clinical Failure of Tazobactam/Piperacillin in Escherichia coli Bacteremia: A Case Report
Bibliographic record
Abstract
An 84-year-old woman presenting with fever and the right lower guardant pain was found to have ischemic colitis and left renal abscess on CT scan findings, and started on empiric antimicrobial therapy with intravenous tazobactam/piperacillin (TAZ/PIPC) 4.5 g q8h . The blood culture prior to TAZ/PIPC grew Escherichia coli ( E. coli ) with MIC of 2 g/mL. The patient’s fever still continued; however, the follow-up blood cultures on another three occasions all demonstrated intermittent E. coli bacteremia despite continuation of TAZ/PIPC (MIC ranging from less than or equal to 2 to 16 g/mL). To make sure proper distribution of the drug, the pharmacokinetic parameters were quantitated after 18 dosing based on the serum concentration of TAZ/PIPC applied to the Sawchuk-Zaske equation: the serum peak/trough levels for PIPC and TAZ were 269/11 g/mL and 41/5 g/mL, with the time above MIC (T > MIC) of PIPC ranging from 70% to 100%. The volume of distribution of PIPC was 13.82 L, total clearance 98.89 mL/min, elimination rate constant (kel) 0.43 h -1 , and resultant plasma half-life (0.693/kel) 1.6 h. Although T > MIC thus reflected optimal pharmacokinetics of TAZ/PIPC against Gram-negative blood stream infection, since blood cultures remained positive, the antimicrobial regimen was switched to intravenous pazufloxacin and tobramycin. The altered therapeutic regimen resulted in sterilization of the blood culture and gradual disappearance of the renal abscess. To the best of our literature search, this case report is the first to demonstrate on the basis of patient’s pharmacokinetic profile that the maximal attainment of pharmacological target of beta-lactam (T > MIC) does not always provide reassurance of successful treatment of blood stream infections. J Med Cases • 2013;4(12):820-824 doi: http://dx.doi.org/10.4021/jmc1494w
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".