Incidence and severity of early electrolyte abnormalities following autologous haematopoietic stem cell transplantation
Bibliographic record
Abstract
BACKGROUND: Haematopoietic stem cell transplantation (HSCT) has gained worldwide acceptance as a therapeutic option for many haematological and non-haematological conditions. Local experience supports that electrolyte abnormalities are quite common; however, the incidence and timing of these abnormalities are unknown. METHOD: We conducted a retrospective descriptive study of 48 consecutive adult patients in order to study the incidence and the timing of electrolyte abnormalities following autologous HSCT. Clinical and pharmacological data were collected by the review of patient charts. Potassium, magnesium, calcium, phosphorus and albumin levels were retrieved from the laboratory. RESULTS: HSCT was performed for multiple myeloma (28/48), lymphoma (8/48), Hodgkin disease (4/48), amyloidosis (4/48) and other neoplasia (4/48). At baseline, 21% of patients (10/48) had low electrolyte levels. Following autologous HSCT, hypokalaemia occurred in 81% (39/48), hypomagnesaemia in 67% (32/48), hypocalcaemia in 49% (17/35) and hypophosphataemia in 91% (39/43) of the patients. The nadir of the electrolyte levels occurred between day 8 and 10 after stem cell transplant while the engraftment occurred at day 11.6+/-0.6. The use of amphotericin B and furosemide was associated with more pronounced hypokalaemia and hypomagnesaemia. Hypocalcaemia was more pronounced in patients with multiple myeloma. High levels of electrolytes occurred in only 25% of the patients, none of which required specific treatment. CONCLUSION: We conclude that low electrolyte levels are extremely common after HSCT and the pathophysiology of these abnormalities are complex and multifactorial.
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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 | 0.000 |
| 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".