Situation-specific theory of surgical site infection-related stimuli in patients undergoing heart transplantation
Bibliographic record
Abstract
Background and objective: Heart transplant is a life-saving treatment and currently is the definitive gold-standard in the treatment of refractory heart failure. Surgical site infection is a serious complication of heart transplantation. A nursing theory predicting consequences related to the management of risk factors for surgical site infection in patients undergoing heart transplantation can be useful to nursing practice. The objective of this study was to develop a situation-specific theory of surgical site infection-related stimuli in patients undergoing heart transplantation.Methods: It was adopted an integrative strategy to develop the theory. Multiple sources of knowledge were accessed. The Roy Adaptation Model was adopted as the foundation for the development of this situation-specific theory in a nursing perspective. A literature review on risk factors for surgical site infection in patients undergoing heart transplantation was conducted. By configuring those sources with practice expertise in a collaborative effort, risk factors for surgical site infection in patients undergoing heart transplantation were classified as contextual or residual stimuli, focal stimulus was defined, and seven theory propositions were developed.Results: Heart transplant surgery was considered as focal stimulus. The contextual stimuli were classified as preoperative, intraoperative, and postoperative contextual stimuli. The residual stimuli were classified as preoperative and intraoperative residual stimuli. No postoperative residual stimulus was identified. Ten theory propositions were created.Conclusions: The emerging theory can help nurses to prevent surgical site infections in patients undergoing heart transplantation. Further developments must be made in order to consider nurse-patient interactions during the prevention of surgical site infections.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".