Dataset Information

Analysis of factors associated with extended recovery time after colonoscopy.

ABSTRACT:

Background & aims

A common limiting factor in the throughput of gastrointestinal endoscopy units is the availability of space for patients to recover post-procedure. This study sought to identify predictors of abnormally long recovery time after colonoscopy performed with procedural sedation. In clinical research, this type of study would be performed using only one regression modeling approach. A goal of this study was to apply various "machine learning" techniques to see if better prediction could be achieved.

Methods

Procedural data for 31,442 colonoscopies performed on 29,905 adult patients at Massachusetts General Hospital from 2011 to 2015 were analyzed to identify potential predictors of long recovery times. These data included the identities of hospital personnel, and the initial statistical analysis focused on the impact of these personnel on recovery time via multivariate logistic regression. Secondary analyses included more information on patient vitals both to identify secondary predictors and to predict long recoveries using more complex techniques.

Results

In univariate analysis, the endoscopist, procedure room nurse, recovery room nurse, and surgical technician all showed a statistically significant relationship to long recovery times, with p-value below 0.0001 in all cases. In the multivariate logistic regression, the most significant predictor of a long recovery time was the identity of the recovery room nurse, with the endoscopist also showing a statistically significant relationship with a weaker effect. Complex techniques led to a negligible improvement over simple techniques in prediction of long recovery periods.

Conclusion

The hospital personnel involved in performing a colonoscopy show a strong association with the likelihood of a patient spending an abnormally long time recovering from the procedure, with the most pronounced effect for the nurse in the recovery room. The application of more advanced approaches to improve prediction in this clinical data set only yielded modest improvements.

SUBMITTER: Eschenfeldt PC

PROVIDER: S-EPMC6013091 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:IntroductionPost-dialysis fatigue is a common and distressing complaint in patients on hemodialysis (HD). The dialysis recovery time (DRT) is a recent and reliable method of Post-dialysis fatigue assessment. We aimed to identify factors affecting the DRT and its relation with HD patients' quality of life.Material and methodsThis is a cross-sectional study carried out on end-stage renal disease patients on regular HD. All participants underwent detailed history taking and complete physical examination, and data on dialysis and laboratory investigations were also collected. Patients were asked "How long does it take you to recover from a dialysis session?" to calculate the DRT. We used the Malnutrition-Inflammation Score (MIS) and KDQOL-36 questionnaire to assess patients' nutritional status and quality of life, respectively.ResultsTwo hundred and ten patients were screened and 191, with a median age of 47 years, completed the study. Patients had a median DRT of 300 minutes (range: 0.0-2880.0), with 55% of patients reporting a DRT of > 240 minutes and 22.5% of them reporting a DRT of < 30 minutes. Patients had a median MIS score of 7 (range: 0-17). There was a statistically significant negative relation between the DRT and symptom/ problem list (p < 0.001), effects of kidney disease (p < 0.001), burden of kidney disease (p < 0.001), SF-12 physical composite (p = 0.001), and SF-12 mental composite (p < 0.001) of KDQOL. The results of multivariate analyses showed that dialysate Na (p = 0.003), and the number of missed sessions (p < 0.001) were independently correlated with the DRT.ConclusionsDecreased dialysate Na, and increased number of missed sessions were predictors of prolonged DRT. Patients with prolonged DRT were associated with poorer quality of life. Further randomized clinical trials are needed to assess strategies to minimize the DRT and, perhaps, enhance clinical outcomes.Trials registrationClinicalTrials.gov Identifier: NCT04727281. First registration date: 27/01/2021.