Coagulopathy and mesenteric ischaemia in severe <scp>SARS</scp>‐<scp>CoV</scp>‐2 infection
Bibliographic record
Abstract
We read with interest the recently published literature detailing coronavirus disease 2019 (COVID-19) and thrombotic complications.1 Patients with COVID-19 can develop coagulopathy,2 which is related to poor outcomes.3, 4 We describe a case of mesenteric thrombosis presenting as a late complication of severe COVID-19. A 40-year-old man presented with COVID-19 symptoms – severe dyspnoea, fever and cough. His medical history is relevant for obesity. Initial laboratory tests demonstrated a normal leucocyte and lymphocyte count (8.6 and 1.7 × 109/L, respectively), a raised d-dimer of 13.75 mg/L (reference range 0–0.5 mg/L), which rose to >35 mg/L after 48 h, and a raised ferritin of 633 μg/L (reference range 30–400 μg/L). Chest radiograph demonstrated features of severe acute respiratory syndrome coronavirus 2 infection and polymerase chain reaction was positive. He deteriorated over 24 h requiring intubation and ventilation. After 9 days in the critical care unit, he developed abdominal distension, increasing inotrope requirements, rising blood lactate and haemodynamic instability. A computed tomography pulmonary angiogram of the abdomen and pelvis with contrast was performed, which demonstrated hypoperfusion of the distal small bowel with intramural gas (Fig. 1). Clotting studies were deranged: prothrombin time 17.1 (reference range 9–13 s), thrombin time 46.0 (reference range 13–17 s), activated partial thromboplastin time 44.9 (reference range 20–33 s) and fibrinogen 5.48 (reference range 1.5–4 g/L). Over 24 h, platelet count dropped from 516 to 124 (reference range 150–400 × 109/L). He was receiving unfractionated heparin as anticoagulation (5000 U three times daily). The patient underwent emergency damage control laparotomy; ischaemic distal small bowel was resected. Given the haemodynamic instability, a laparostomy was performed. After 48 h, he returned to theatre for abdominal wall closure and stoma formation, which was uneventful. We add further evidence that there can be significant coagulopathy with severe acute respiratory syndrome coronavirus 2 infection, which can lead to arterial thrombi. Clinicians should investigate these patients thoroughly for thrombotic complications of COVID-19.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".