Objective: We studied the primary hypothesis that the training level of anesthesiology residents (first clinical anesthesia year, CA1 vs CA2/3 residents) is associated with early postoperative desaturation (oxygen saturation < 90%). We also analyzed the change in the rate (trajectory) of desaturation during the resident's development from CA1 to CA2/3 resident, and its effects on postoperative respiratory complications.
Design: Retrospective hospital registry study.
Setting: Two university-affiliated hospitals networks (MA and NY, USA).
Patients: 140,818 adults undergoing non-cardiac surgery under general anesthesia and extubation in the operating room by residents (n = 378) between 2005 and 2021.
Measurements: Multivariate logistic and quantile regression were used in the analyses. The secondary outcome was major respiratory complication within 7 days after surgery.
Main Results: In 6.5% and 1.6% of cases, early postoperative desaturation to < 90% and 80% occurred. Compared to CA2/3 residents, CA1 residents had higher odds of experiencing early postoperative desaturation to < 90% and 80% (adjusted odds ratio [ORadj], 1.07; 95%CI 1.03-1.12; p = 0.002, and ORadj 1.10; 95%CI 1.01-1.20; p = 0.037, respectively). The change in postoperative desaturation rate during the transition from CA1 to CA2/3 status varied substantially from ORadj 0.80 (decreased risk) to 1.33 (increased risk). Major respiratory complication did not differ between experience levels (p = 0.52). However, a strong decline in improvement regarding the rate of postoperative desaturation during the transition from CA1 to CA2/3, was paralleled by an increased odds of major respiratory complication for CA2/3 residents (ORadj 1.20; 95%CI 1.02-1.42; p = 0.026, p-for-interaction = 0.056).
Conclusion: Patients treated by CA1 residents have an increased risk of postoperative desaturation. Some residents show an improvement and others a decline in postoperative desaturation rate. Our secondary analysis suggests that there should be more focus on those residents who had a declining performance in postoperative desaturation despite becoming more experienced.
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http://dx.doi.org/10.1016/j.jclinane.2023.111238 | DOI Listing |
BMC Genomics
January 2025
Department of Agronomy, Horticulture, and Plant Science, South Dakota State University (SDSU), Brookings, SD, 57007, USA.
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January 2025
Department of Pediatric Dentistry, School of Dentistry, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil.
Background: The impact of ankyloglossia (tongue-tie) on breastfeeding outcomes may be overestimated and surgical treatment in newborns remains a controversial topic. The aim of the present study was to assess and quantify the impact of ankyloglossia in newborns on breastfeeding self-efficacy at 14 days of life.
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Sci Rep
January 2025
School of Mathematics and Computer Science, Tongling University, Tongling, 244061, China.
The application of artificial neural networks (ANNs) can be found in numerous fields, including image and speech recognition, natural language processing, and autonomous vehicles. As well, intrusion detection, the subject of this paper, relies heavily on it. Different intrusion detection models have been constructed using ANNs.
View Article and Find Full Text PDFSci Data
January 2025
Centre for Automation and Robotics (CAR), Spanish National Research Council (CSIC), 28006, Madrid, Spain.
This study highlights the vital role of high-resolution (HR), open-source land cover maps for food security, land use planning, and environmental protection. The scarcity of freely available HR datasets underscores the importance of multi-spectral HR aerial images. We used unmanned aerial vehicle (UAV) to capture images for a centimeter-level orthomosaics, facilitating advanced remote sensing and spatial analysis.
View Article and Find Full Text PDFMed Phys
January 2025
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, USA.
Purpose: In locations where the proton energy spectrum is broad, lineal energy spectrum-based proton biological effects models may be more accurate than dose-averaged linear energy transfer (LET) based models. However, the development of microdosimetric spectrum-based biological effects models is hampered by the extreme computational difficulty of calculating microdosimetric spectra. Given a precomputed library of lineal energy spectra for monoenergetic protons, a weighted summation can be performed which yields the lineal energy spectrum of an arbitrary polyenergetic beam.
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