Nursing intervention including meditation and physiotherapeutic treatment in post PCI chest pain (non-ischemic)
Bibliographic record
Abstract
To determine the effectiveness of nursing educational interventions on patients with post PCI non-ischemic chest pain. METHODOLOGY: This experimental study was conducted from December 2017 to May 2018 on 100 post PCI patients. Patients who came with post PCI non-ischemic chest pain and on initial screening on the Numerical Rating Scale (NRS) patients scored 5 to 10 were included. Those who had post PCI ischemic chest pain with complications were excluded from the study. The Short McGill Pain Questionnaire (SMPQ) was used to assess the effectiveness of nursing educational interventions. Analysis of data was performed on SPSS version 21. Percentages were used for categorical variables, and inferential statistics were calculated using the Mann-Whitney Test. Mean and S.D. were calculated at baseline, week two, week four, and week six for both experimental and non-experimental groups. A P-value of 0.05 was considered significant. RESULTS: This study's findings showed that most participants (74%) were males and almost all (99%) were married. The P-value is significant at different intervals between the experimental and control groups at two, four and six weeks with P-values <0.001, <0.001, and <0.001, respectively. CONCLUSION: The findings of this study revealed that nursing interventions help reduce post PCI non-ischemic chest pain levels. This study demonstrates that after nurse-led educational interventions, there were significant differences in scores between interventional and noninterventional groups at different levels after PCI.
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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 | 0.004 | 0.001 |
| 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".