Genetic Susceptibility Toward Nausea and Vomiting in Surgical Patients

Gloor, Yvonne; Czarnetzki, Christoph; Curtin, François; Gil-Wey, Béatrice; Tramèr, Martin R.; Desmeules, Jules Alexandre

doi:10.3389/fgene.2021.816908

Cited by 7 publications

(2 citation statements)

References 99 publications

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“…We validate novel DPIs with DGIdb database [41]; DGIdb supports 1,705 known + 1,379 novel DPIs. Among top 60 DGIdb-validated predictions in Supplementary Table S4, we find that many of them can also be supported by the previously known experimental or clinical evidence in the literature [42]- [51].…”

Section: Mvae-dfdpnet Reveals Novel Dpissupporting

confidence: 67%

Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions

Xia,

Wu,

Zhao

et al. 2024

IEEE J. Biomed. Health Inform.

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Precisely predicting drug-protein interactions (DPIs) is pivotal for drug discovery and advancing precision medicine. A significant challenge in this domain is the highdimensional and heterogeneous data characterizing drug and protein attributes, along with their intricate interactions. In our study, we introduce a novel deep learning architecture: the Multi-view Variational Auto-Encoder embedded within a cascade Deep Forest (MVAE-DFDPnet). This framework adeptly learns ultra-low-dimensional embedding for drugs and proteins. Notably, our t-SNE analysis reveals that two-dimensional embedding can clearly define clusters corresponding to diverse drug classes and protein families. These ultra-low-dimensional embedding likely contribute to the enhanced robustness and generalizability of our MVAE-DFDPnet. Impressively, our model surpasses current leading methods on benchmark datasets, functioning in significantly reduced dimensional spaces. The model's resilience is further evidenced by its sustained accuracy in predicting interactions involving novel drugs, proteins, and drug classes. Additionally, we have corroborated several newly identified DPIs with experimental evidence from the scientific literature. The code used to generate and analyze these results can be accessed from https://github.com/Macau-LYXia/MVAE-DFDPnet-V2.

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Section: Mvae-dfdpnet Reveals Novel Dpissupporting

confidence: 67%

Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions

Xia,

Wu,

Zhao

et al. 2024

IEEE J. Biomed. Health Inform.

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show abstract

“…PONV is an unsatisfactory experience and painful adverse event for patients, especially in the first day after surgery. Its incidence is approximately 30% and up to 80% without prevention 1 10. Moreover, some surgical types were associated with the high occurrence of PONV, especially in gynaecological surgery, otolaryngology surgery and neurosurgery 3.…”

Section: Discussionmentioning

confidence: 99%

Effect of dexmedetomidine on postoperative nausea and vomiting in patients under general anaesthesia: an updated meta-analysis of randomised controlled trials

Zhao,

Li,

Wang

et al. 2023

BMJ Open

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ObjectivesTo explore the effect of dexmedetomidine (DEX) on postoperative nausea and vomiting (PONV) in adult patients after general anaesthesia.DesignSystematic review and meta-analysis.Eligibility criteria for selecting studiesRandomised controlled trials (RCTs) comparing the efficacy of DEX with placebo or a single drug on PONV in adult patients after general anaesthesia.Data sourcesWe searched the PubMed, the Web of Science, the Cochrane Library and Embase (1 January 2000 to 30 June 2022) to select the relevant RCTs.Data analysisAll the relevant data were analysed by using RevMan V.5.4. Heterogeneity was tested for each outcome, and random-effect or fixed-effect models was selected according to the level of heterogeneity. The primary outcome was the incidence of PONV. The secondary outcomes were the incidence of bradycardia, perioperative opioid consumption, extubation time and the length of hospitalisation.ResultsA total of 18 trials involving 2018 patients were included in this meta-analysis. Notably, 15 updated studies were not involved in the previous meta-analysis. The incidence of PONV in DEX group was lower than that in the control group (OR=0.49, 95% CI: 0.36 to 0.67) and the perioperative opioid consumption in DEX group was also decreased significantly (standard mean difference (SMD)=−1.04, 95% CI: −1.53 to −0.54). Moreover, the length of hospitalisation (SMD=−2.29, 95% CI: −4.31 to −0.28) and the extubation time (SMD=−0.75, 95% CI: −1.26 to −0.25) in DEX group were shorter. Whereas, more number of patients receiving DEX might increase the occurrence of bradycardia (OR=1.60, 95% CI: 1.13 to 2.27).ConclusionsDEX could decrease the occurrence of PONV in adult patients under general anaesthesia and promote the recovery after surgery. However, DEX might increase the occurrence of bradycardia.PROSPERO registration numberCRD 42022341548.

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Sex/Gender Differences in Postoperative Nausea and Vomiting

Lee

2024

Sex/Gender-Specific Medicine in Clinical Areas

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Genetic Susceptibility Toward Nausea and Vomiting in Surgical Patients

Cited by 7 publications

References 99 publications

Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions

Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions

Effect of dexmedetomidine on postoperative nausea and vomiting in patients under general anaesthesia: an updated meta-analysis of randomised controlled trials

Sex/Gender Differences in Postoperative Nausea and Vomiting

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