Beneficial Effects of the Novel Digital Incentive Spirometer Device and Incentive Spirometer in Patients Undergoing Open-Heart Surgery: Randomized Controlled Trial
Bibliographic record
Abstract
Background: The number of patients undergoing open-heart surgery (OHS) is persistently increasing. Additionally, postoperative pulmonary complications have been reported after OHS, and an incentive spirometer has been suggested to prevent postoperative pulmonary complications. However, no commercial incentive spirometer provides the precise inhalation volume. We developed a digital incentive spirometer (DIS) that displays the relevant data. Objective: In this study, we aimed to explore the beneficial effects of a DIS on respiratory function in patients who underwent OHS. Methods: A randomized controlled trial was designed with 32 patients scheduled for OHS: 16 individuals each were assigned to the DIS and the flow-oriented incentive spirometer (ie, Triflow incentive spirometer) groups, respectively. The patients were requested to use the DIS and Triflow incentive spirometer 15 times/set, two sets/day, from day 1 to 5 postextubation. All participants underwent lung function and respiratory muscle strength assessments prior to OHS and on day 5 postextubation postoperatively. For comparison between and within the groups, we performed an intention-to-treat analysis with a two-way mixed analysis of variance. Results: In both the DIS and Triflow incentive spirometer groups, pulmonary function parameters and maximal respiratory pressure were markedly reduced on day 5 postextubation when compared with those prior to OHS (P<.05). There were no significant differences in pulmonary function or respiratory muscle strength between the two groups (P>.05). Conclusions: Pulmonary function and respiratory muscle strength did not differ significantly between the DIS and Triflow incentive spirometer groups among patients who underwent OHS.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".