Effect of applying nurses driven electrolyte repletion protocol on electrolyte disturbances control among critically ill patients
Bibliographic record
Abstract
Background and objective: Electrolyte disturbances remain a common lifesaving issue in the intensive care units. They are associated with increased morbidity and mortality. They are mostly resulted secondary to critical illness itself or associated treatment modalities. Therefore, electrolytes repletion should be done effectively and timely. This could be ensured using nurse driven protocols rather than traditional methods of repletion. These protocols are nurse initiated and collaboratively developed. They have been shown to improve patient care outcomes through the provision of high quality care. They are increasingly being used in the critical care setting. Objective: Determine the effect of applying nurses driven electrolytes repletion protocol on electrolytes disturbance control among critically ill patients.Methods: Quasi experimental research design was used. Sixty two critically ill patients with electrolytes loss were enrolled in the study at Alexandria Main University Hospital intensive care units, Egypt. All episodes of electrolyte loss were evaluated. Repletion of electrolyte loss was done according to unit routine for the control group and nurses driven electrolytes repletion protocol for the study group. Episodes of electrolyte disturbances, adverse events and timing of repletion were evaluated.Results: Neurological disorders represent the most encountered diagnosis. The most common cause of electrolyte loss in was the use of diuretics. Furthermore, there was a highly statistical difference between the two groups as regard electrolytes levels, effectiveness and timing of replacement.Conclusions: Application of nurses driven electrolyte repletion protocol resulted in improvements in the effectiveness and timeliness of electrolyte replacement.
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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 | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".