Evaluation of the quality and quantity of artificial intelligence-generated responses about anesthesia and surgery: using ChatGPT 3.5 and 4.0.

Introduction: The large-scale artificial intelligence (AI) language model chatbot, Chat Generative Pre-Trained Transformer (ChatGPT), is renowned for its ability to provide data quickly and efficiently. This study aimed to assess the medical responses of ChatGPT regarding anesthetic procedures. Methods: Two anesthesiologist authors selected 30 questions representing inquiries patients might have about surgery and anesthesia. These questions were inputted into two versions of ChatGPT in English. A total of 31 anesthesiologists then evaluated each response for quality, quantity, and overall assessment, using 5-point Likert scales. Descriptive statistics summarized the scores, and a paired sample t-test compared ChatGPT 3.5 and 4.0. Results: Regarding quality, "appropriate" was the most common rating for both ChatGPT 3.5 and 4.0 (40 and 48%, respectively). For quantity, responses were deemed "insufficient" in 59% of cases for 3.5, and "adequate" in 69% for 4.0. In overall assessment, 3 points were most common for 3.5 (36%), while 4 points were predominant for 4.0 (42%). Mean quality scores were 3.40 and 3.73, and mean quantity scores were - 0.31 (between insufficient and adequate) and 0.03 (between adequate and excessive), respectively. The mean overall score was 3.21 for 3.5 and 3.67 for 4.0. Responses from 4.0 showed statistically significant improvement in three areas. Conclusion: ChatGPT generated responses mostly ranging from appropriate to slightly insufficient, providing an overall average amount of information. Version 4.0 outperformed 3.5, and further research is warranted to investigate the potential utility of AI chatbots in assisting patients with medical information.

Tailoring the Structure-Property Relationship of Ring-Opened Metathesis Copolymers for CO2-Selective Membranes.

In this work, we explore the use of ring-opening metathesis polymerization (ROMP) facilitated by a second-generation Grubbs catalyst (G2) for the development of advanced polymer membranes aimed at CO2 separation. By employing a novel copolymer blend incorporating 4,4'-oxidianiline (ODA), 1,6-hexanediamine (HDA), 1-adamantylamine (AA), and 3,6,9-trioxaundecylamine (TA), along with a CO2-selective poly(ethylene glycol)/poly(propylene glycol) copolymer (Jeffamine2003) and polydimethylsiloxane (PDMS) units, we have synthesized membranes under ambient conditions with exceptional CO2 separation capabilities. The strategic inclusion of PDMS, up to a 20% composition within the PEG/PPG matrix, has resulted in copolymer membranes that not only surpass the 2008 upper limit for CO2/N2 separation but also meet the commercial targets for CO2/H2 separation. Comprehensive analysis reveals that these membranes adhere to the mixing rule and exhibit percolation behavior across the entire range of compositions (0-100%), maintaining robust antiplasticization performance even under pressures up to 20 atm. Our findings underscore the potential of ROMP in creating precisely engineered membranes for efficient CO2 separation, paving the way for their application in large-scale environmental and industrial processes.

Preoperative C-reactive protein/albumin ratio and mortality of off-pump coronary artery bypass graft.

Background: We sought to investigate the prognostic value of preoperative C-reactive protein (CRP)-to-albumin ratio (CAR) for the prediction of mortality in patients undergoing off-pump coronary artery bypass grafting (OPCAB). Methods: From January 2010 to August 2016, adult patients undergoing OPCAB were analyzed retrospectively. In a total of 2,082 patients, preoperative inflammatory markers including CAR, CRP, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio were recorded. Receiver operating characteristic (ROC) curves were used to determine the optimal threshold and compare the predictive values of the markers. The patients were divided into two groups according to the cut-off value of CAR, and then the outcomes were compared. The primary end point was 1-year mortality. Results: During the 1-year follow-up period, 25 patients (1.2%) died after OPCAB. The area under the curve of CAR for 1-year mortality was 0.767, which was significantly higher than other inflammatory markers. According to the calculated cut-off value of 1.326, the patients were divided into two groups: 1,580 (75.9%) patients were placed in the low CAR group vs. 502 (24.1%) patients in the high CAR group. After adjustment with inverse probability weighting, high CAR was significantly associated with increased risk of 1-year mortality after OPCAB (Hazard ratio, 5.01; 95% Confidence interval, 2.01-12.50; p < 0.001). Conclusions: In this study, we demonstrated that preoperative CAR was associated with 1-year mortality following OPCAB. Compared to previous inflammatory markers, CAR may offer superior predictive power for mortality in patients undergoing OPCAB. For validation of our findings, further prospective studies are needed.

PolyMOF nanoparticles constructed from intrinsically microporous polymer ligand towards scalable composite membranes for CO2 separation.

Integrating different modification strategies into a single step to achieve the desired properties of metal-organic frameworks (MOFs) has been very synthetically challenging, especially in developing advanced MOF/polymer mixed matrix membranes (MMMs). Herein, we report a polymer-MOF (polyMOF) system constructed from a carboxylated polymer with intrinsic microporosity (cPIM-1) ligand. This intrinsically microporous ligand could coordinate with metals, leading to ~100 nm-sized polyMOF nanoparticles. Compared to control MOFs, these polyMOFs exhibit enhanced ultramicroporosity for efficient molecular sieving, and they have better dispersion properties in casting solutions to prepare MMMs. Ultimately, integrating coordination chemistries through the cPIM-1 and polymer-based functionality into porous materials results in polyMOF/PIM-1 MMMs that display excellent CO2 separation performance (surpassing the CO2/N2 and CO2/CH4 upper bounds). In addition to exploring the physicochemical and transport properties of this polyMOF system, scalability has been demonstrated by converting the developed MMM material into large-area (400 cm2) thin-film nanocomposite (TFN) membranes.