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- Enlund, Mats, et al.
(författare)
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Impact of general anaesthesia on breast cancer survival: a 5-year follow up of a pragmatic, randomised, controlled trial, the CAN-study, comparing propofol and sevoflurane
- 2023
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Ingår i: EClinicalMedicine. - : Elsevier. - 2589-5370. ; 60
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Tidskriftsartikel (refereegranskat)abstract
- Background Anaesthesia may impact long-term cancer survival. In the Cancer and Anaesthesia study, we hypothesised that the hypnotic drug propofol will have an advantage of at least five percentage points in five-year survival over the inhalational anaesthetic sevoflurane for breast cancer surgery. Methods From 2118 eligible breast cancer patients scheduled for primary curable, invasive breast cancer surgery, 1764 were recruited after ethical approval and individual informed consent to this open label, single-blind, randomised trial at four county- and three university hospitals in Sweden and one Chinese university hospital. Of surveyed patients, 354 were excluded, mainly due to refusal to participate. Patients were randomised by computer at the monitoring organisation to general anaesthesia maintenance with either intravenous propofol or inhaled sevoflurane in a 1:1 ratio in permuted blocks. Data related to anaesthesia, surgery, oncology, and demographics were registered. The primary endpoint was five-year overall survival. Data are presented as Kaplan-Meier survival curves and Hazard Ratios based on Cox univariable regression analyses by both intention-to-treat and perprotocol. EudraCT, 2013-002380-25 and ClinicalTrials.gov, NCT01975064. Findings Of 1764 patients, included from December 3, 2013, to September 29, 2017, 1670 remained for analysis. The numbers who survived at least five years were 773/841 (91.9% (95% CI 90.1-93.8)) in the propofol group and 764/829 (92.2% (90.3-94.0)) in the sevoflurane group, (HR 1.03 (0.73-1.44); P = 0.875); the corresponding results in the per-protocol-analysis were: 733/798 (91.9% (90.0-93.8)) and 653/710 (92.0% (90.0-94.0)) (HR = 1.01 (0.71-1.44); P = 0.955). Survival after a median follow-up of 76.7 months did not indicate any difference between the groups (HR 0.97, 0.72-1.29; P = 0.829, log rank test). Interpretation No difference in overall survival was found between general anaesthesia with propofol or sevoflurane for breast cancer surgery. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd.
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| 3. |
- Flisberg, A., et al.
(författare)
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Prognostic capacity of automated quantification of suppression time in the EEG of post-asphyctic full-term neonates
- 2011
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Ingår i: Acta Paediatrica. - : Wiley-Blackwell. - 0803-5253 .- 1651-2227. ; 100:10, s. 1338-1343
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To evaluate the prognostic capacity of a new method for automatic quantification of the length of suppression time in the electroencephalogram (EEG) of a group of asphyxiated newborn infants. Methods: Twenty-one full-term newborn infants who had been resuscitated for severe birth asphyxia were studied. Eight channel continuous EEG was recorded for prolonged time periods during the first days of life. Artefact detection or rejection was not applied to the signals. The signals were fed through a pretrained classifier and then segmented into burst and suppression periods. Total suppression length per hour was calculated. All surviving patients were followed with structured neurodevelopmental assessments to at least 18 months of age. Results: The patients who developed neurodevelopmental disability or died had significant suppression periods in their EEG during the first days of life while the patients who had a normal follow-up had no or negligible amount of suppression. Conclusions: This new method for automatic quantification of suppression periods in the raw, neonatal EEG discriminates infants with good from those with poor outcome.
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| 5. |
- Löfhede, J., et al.
(författare)
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Classifying burst and suppression in the EEG of post asphyctic newborns using a support vector machine
- 2007
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Ingår i: Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering. - : IEEE. - 9781424407910 ; , s. 630-633
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Konferensbidrag (refereegranskat)abstract
- A Support Vector Machine (SVM) was trained to distinguish bursts from suppression in burst-suppression EEG, using Ave features inherent in the electro-encephalogram (EEG) as input. The study was based on data from six full term infants who had suffered from perinatal asphyxia, and the machine was trained with reference classifications made by an experienced electroencephalographer. The results show that the method may be useful, but that differences between patients in the data set makes optimization of the system difficult.
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