Successful Management of a Rare Incidence of Potassium Chloride Extravasation in a Dog Receiving Intermittent Hemodialysis
Bibliographic record
Abstract
Aims: To ensure the safe administration of intravenous potassium chloride in patients with hypokalemia, emphasizing the prompt identification and management of extravasation to prevent serious complications. Presentation of Case: A 08 year-old male Labrador Retriever was presented with a 4-day history of anorexia, lethargy, severe vomiting, abdominal pain, weight loss, polyuria, polydipsia, and melena. Based on clinical findings and diagnostic evaluations, the dog was diagnosed acute kidney injury (AKI) and managed using intermittent hemodialysis (IHD). Following the first session of hemodialysis, the patient developed hypokalemia, and a constant rate infusion (CRI) of potassium chloride (Kcl) was initiated to correct the electrolyte imbalance. However, due to dislodgement of the intravenous cannula, a portion of the potassium chloride was inadvertently administered subcutaneously. This led to extensive swelling of the left hind-limb, indicative of extravasation. To manage the localized tissue reaction and minimize further damage, diluted lignocaine in normal saline was administered subcutaneously over the affected area. Discussion: Extravasation of potassium chloride is a serious complication that can result in localized tissue necrosis and significant damage to surrounding structures. In this case, inadequate monitoring of the intravenous site led to the accidental subcutaneous administration of potassium chloride, causing soft tissue swelling and a risk of necrosis. Conclusion: This incident underscores the critical importance of vigilant observation during intravenous infusions, especially when administering irritant solutions like potassium chloride. To prevent such occurrences, it is essential to implement strict monitoring protocols and ensure that all clinical staff is adequately trained in the safe handling and administration of intravenous medications.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".