Cryptogenic Hypervirulent Klebsiella pneumoniae Pyogenic Liver Abscess: A Case Report
Bibliographic record
Abstract
BACKGROUND Klebsiella pneumoniae is a gram-negative organism known to cause pyogenic liver abscesses. It is most often caused by one of the hypervirulent strains, which are capable of causing metastatic infection. This occurs most commonly in Asia in patients without hepatobiliary disease; however, it is becoming increasingly recognized in North America. CASE REPORT We report a previously healthy man in his 50s who presented to hospital with 3 weeks of fever, chills, and mild abdominal pain following a minor motor vehicle collision. Ultrasound and computed tomography of his abdomen revealed a large multi-loculated liver abscess. This was drained percutaneously and grew a hypervirulent strain of Klebsiella pneumoniae known to cause metastatic infection. His blood cultures were negative. In addition to percutaneous drainage, he was treated with 8 weeks of antimicrobial therapy. Fortunately, he did not develop evidence of metastatic infection despite the hypervirulent strain. Etiology of the abscess was not clearly identified; however, it was speculated that the motor vehicle collision could have led to its development through gut translocation. CONCLUSIONS Presentation of Klebsiella pneumoniae liver abscesses is often nonspecific, and clinicians must have a high index of suspicion in order to ensure rapid diagnosis and treatment. Delay in diagnosis is associated with increased morbidity and mortality, and thus it is an important entity for clinicians to be aware of, especially as it becomes more prevalent in North American populations. Additionally, it is important that physicians are aware of the hypervirulent strains and screen patients clinically for evidence of metastatic infection.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".