Preoperative Pulmonary Function test and Pulse Oximetry among Patients Recovered from COVID-19 Who Were Candidates for Elective Surgery
Bibliographic record
Abstract
Background: This descriptive study aimed to assess preoperative pulmonary function test (PFT) results and pulse oximetry readings in patients recovered from COVID-19 who were candidates for elective surgery. Materials and Methods: This is a descriptive study. A total of 110 patients (men = 51) with a mean age of 52.6 years were enrolled in the study. The study protocol was presented to the ethics committee and received approval. Participants included patients with a positive SARS-CoV-2 PCR test history, with a recovery period of at least 6-8 weeks for symptomatic patients and four weeks for asymptomatic patients. Data collection involved a random selection, obtaining informed consent, and conducting a history and physical examination. Pulmonary function capacity and oxygen saturation were assessed, and frailty was evaluated using the Edmonton Frail Scale. Echocardiography and electrocardiography were performed on all patients. Results: The study participants mainly underwent trans-ureteral lithotripsy (TUL), laparoscopic cholecystectomy (LC), and percutaneous nephrolithotomy (PCNL). Symptomatic patients exhibited lower pulse oximetry readings than asymptomatic patients (91.18% vs. 96.13%, p-value = 0.005). Although the average ejection fraction was slightly lower in symptomatic patients (44.25%) compared to asymptomatic patients (48.18%), the difference was insignificant. Symptomatic patients also had higher rates of abnormalities in chest X-rays, electrocardiograms, pulmonary function tests, and fasting blood sugar levels, as well as a higher rate of ICU admission. Conclusion: Comprehensive preoperative evaluations, including pulmonary function and oxygenation assessment, are crucial for COVID-19 survivors undergoing elective surgery. Symptomatic patients showed lower pulse oximetry readings and higher respiratory and cardiovascular abnormalities rates. These findings emphasize the importance of optimizing perioperative management and minimizing complications by thoroughly assessing patients' preoperative health status.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".