Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach
Introduction Data concerning anaesthesia for endourology are rare, and options for it are numerous. Thus, identifying the optimal anaesthesia regimen remains challenging. With this study we aimed to provide the means for selecting optimal anaesthesia for endourology procedures. Material and methods...
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Termedia Publishing House
2025-01-01
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| Series: | Anaesthesiology Intensive Therapy |
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| Online Access: | https://www.ait-journal.com/Process-optimisation-spinal-versus-general-anaesthesia-for-endourological-surgery,196606,0,2.html |
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| author | Kornel Skitek Gregor A. Schittek Jens Soukup |
| author_facet | Kornel Skitek Gregor A. Schittek Jens Soukup |
| author_sort | Kornel Skitek |
| collection | DOAJ |
| description | Introduction
Data concerning anaesthesia for endourology are rare, and options for it are numerous. Thus, identifying the optimal anaesthesia regimen remains challenging. With this study we aimed to provide the means for selecting optimal anaesthesia for endourology procedures.
Material and methods
This was a randomised, open-label, controlled study conducted in a single tertiary hospital. Inclusion criteria: American Society of Anesthesiologists (ASA) physical status/risk category I–III, and scheduled surgery time < 60 minutes. Exclusion criteria: contraindications or lack of consent for one of the anaesthesia types, intellectual disabilities, pregnancy, breastfeeding, and refusal to participate. The participants were divided into 3 groups: G1, spinal anaesthesia (SPA) with bupivacaine; G2, SPA with prilocaine; G3, total intravenous anaesthesia (TIVA) with remifentanil and propofol. The primary outcome measure was time to ambulation, while the secondary outcome measures included perioperative hypotension. The results are presented as mean ± SD or median [IQR].
Results
In total, 117 patients completed the study. The time to ambulation (minutes) was significantly different between all groups: 187.95 ± 49.82, 161.05 ± 46.28, and 129.14 ± 63.75 min, for G1, G2 and G3, respectively. The mean arterial pressure drop from baseline during the procedure was most pronounced in G3 (35% [30–44], P < 0.001) and lowest in G2 (18% [12–27], P < 0.001 vs. G3, NS vs. bupivacaine). Machine-learning models were trained and demonstrated satisfactory performance in predicting the time spent in recovery.
Conclusions
In the context of endourological surgery, the time required for ambulation was shortest when using TIVA, while SPA with hyperbaric prilocaine provides the closest approximation to optimal anaesthesia. |
| format | Article |
| id | doaj-art-8f4c4f8e6cae4e1fb0e8c275788a4c0a |
| institution | Kabale University |
| issn | 1642-5758 1731-2531 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Termedia Publishing House |
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| series | Anaesthesiology Intensive Therapy |
| spelling | doaj-art-8f4c4f8e6cae4e1fb0e8c275788a4c0a2025-08-20T03:49:45ZengTermedia Publishing HouseAnaesthesiology Intensive Therapy1642-57581731-25312025-01-0156528529410.5114/ait.2024.146716196606Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approachKornel Skitek0Gregor A. Schittek1Jens Soukup2Department of Anaesthesiology and Intensive Care Medicine, Jena University Hospital, Jena, GermanyDepartment of Anaesthesiology and Intensive Care Medicine, Medical University Graz, Graz, AustriaDepartment of Anaesthesiology, Intensive Care Medicine and Palliative Care Medicine, Medical University Lausitz – Carl Thiem, Cottbus, GermanyIntroduction Data concerning anaesthesia for endourology are rare, and options for it are numerous. Thus, identifying the optimal anaesthesia regimen remains challenging. With this study we aimed to provide the means for selecting optimal anaesthesia for endourology procedures. Material and methods This was a randomised, open-label, controlled study conducted in a single tertiary hospital. Inclusion criteria: American Society of Anesthesiologists (ASA) physical status/risk category I–III, and scheduled surgery time < 60 minutes. Exclusion criteria: contraindications or lack of consent for one of the anaesthesia types, intellectual disabilities, pregnancy, breastfeeding, and refusal to participate. The participants were divided into 3 groups: G1, spinal anaesthesia (SPA) with bupivacaine; G2, SPA with prilocaine; G3, total intravenous anaesthesia (TIVA) with remifentanil and propofol. The primary outcome measure was time to ambulation, while the secondary outcome measures included perioperative hypotension. The results are presented as mean ± SD or median [IQR]. Results In total, 117 patients completed the study. The time to ambulation (minutes) was significantly different between all groups: 187.95 ± 49.82, 161.05 ± 46.28, and 129.14 ± 63.75 min, for G1, G2 and G3, respectively. The mean arterial pressure drop from baseline during the procedure was most pronounced in G3 (35% [30–44], P < 0.001) and lowest in G2 (18% [12–27], P < 0.001 vs. G3, NS vs. bupivacaine). Machine-learning models were trained and demonstrated satisfactory performance in predicting the time spent in recovery. Conclusions In the context of endourological surgery, the time required for ambulation was shortest when using TIVA, while SPA with hyperbaric prilocaine provides the closest approximation to optimal anaesthesia.https://www.ait-journal.com/Process-optimisation-spinal-versus-general-anaesthesia-for-endourological-surgery,196606,0,2.htmlspinal anaesthesiamachine learningcost analysisendourological surgerytotal intravenous anaesthesiamachine learningcost analysis |
| spellingShingle | Kornel Skitek Gregor A. Schittek Jens Soukup Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach Anaesthesiology Intensive Therapy spinal anaesthesia machine learning cost analysis endourological surgery total intravenous anaesthesia machine learning cost analysis |
| title | Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach |
| title_full | Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach |
| title_fullStr | Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach |
| title_full_unstemmed | Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach |
| title_short | Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach |
| title_sort | process optimisation spinal versus general anaesthesia for endourological surgery a randomised controlled trial and machine learning approach |
| topic | spinal anaesthesia machine learning cost analysis endourological surgery total intravenous anaesthesia machine learning cost analysis |
| url | https://www.ait-journal.com/Process-optimisation-spinal-versus-general-anaesthesia-for-endourological-surgery,196606,0,2.html |
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