Candida glabrata infection of a pancreatic pseudocyst in a COVID-19 patient: A case report and review of the literature
Bibliographic record
Abstract
Introduction: Pancreatic pseudocysts remain a feared complication of acute or chronic pancreatitis and are often characterized by collections of fluids due to underlying damage to the pancreatic ducts, culminating in a walled-off region bereft of an epithelial layer but surrounded by granulation tissue. While fungal infections of pancreatic pseudocysts are rarely encountered, candida albicans remains the most frequently implicated organism. Case presentation: A 55-year-old male presented with pain in the left-hypochondriac region, accompanied by non-bilious emesis and nausea. Interestingly, the patient also tested positive for a COVID-19 infection. Investigative workup divulged enhancing pancreatic walls with a radiologic impression consistent with a pancreatic pseudocyst. An ultrasound-guided external drainage was performed; the drainage was conducted unremarkably, with the resultant fluid collection revealing the presence of Candida Glabrata. The patient was commenced on antifungal therapy and continues to do well to date. Discussion: Infectious ailments of pancreatic pseudocysts remain a widely known complication of acute pancreatitis. While it is rare, fungal infection is a crucial consideration for patients with pancreatic pseudocysts, especially in the context of a lack of an adequate response to antibiotics, deterioration, comorbidities, and immunocompromised states. Conclusion: Rapid identification of the microbe responsible for pancreatic pseudocyst infection is vital for time-sensitive treatment and a more rapid recovery, curbing associated morbidity and mortality. HIGHLIGHTS Fungal infections of pancreatic pseudocysts remain a rare but well-characterized complication, culminating in significant morbidity and mortality. Telltale signs include unresponsiveness to antibiotics and worsening clinical symptoms. Rapid identification of the responsible microbe is vital for time-sensitive treatment and a more rapid recovery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".