Background: Maintenance of stable blood pressure (BP) during cerebrovascular bypass surgery is crucial to prevent cerebral ischemia. We compared the effect of remimazolam anesthesia with that of propofol-induced and desflurane-maintained anesthesia on intraoperative hemodynamic stability and the need for vasoactive agents in patients undergoing cerebrovascular bypass surgery. Methods: Sixty-five patients were randomized into remimazolam (n = 31, remimazolam-based intravenous anesthesia) and control groups (n = 34, propofol-induced and desflurane-maintained anesthesia). The primary outcome was the occurrence of intraoperative hypotension. The secondary outcomes included hypotension duration, lowest mean BP (MBP), generalized average real variability (ARV) of MBP, and consumption of phenylephrine, norepinephrine, or remifentanil. Results: Occurrence rate and duration of hypotension were significantly lower in the remimazolam group (38.7% vs. 73.5%, P = 0.005; 0 [0, 10] vs. 7.5 [1.25, 25] min, P = 0.008). Remimazolam also showed better outcomes for lowest MBP (78 [73, 84] vs. 69.5 [66.25, 75.8] mmHg, P < 0.001) and generalized ARV of MBP (1.42 ± 0.49 vs. 1.66 ± 0.52 mmHg/min, P = 0.036). The remimazolam group required less phenylephrine (20 [0, 65] vs. 100 [60, 130] μg, P < 0.001), less norepinephrine (162 [0, 365.5] vs. 1335 [998.5, 1637.5] μg, P < 0.001), and more remifentanil (1750 [1454.5, 2184.5] vs. 531 [431, 746.5] μg, P < 0.001) than the control group. Conclusions Remimazolam anesthesia may provide better hemodynamic stability during cerebrovascular bypass surgery than propofol-induced and desflurane-maintained anesthesia.

Background: Maintenance of stable blood pressure (BP) during cerebrovascular bypass surgery is crucial to prevent cerebral ischemia. We compared the effect of remimazolam anesthesia with that of propofol-induced and desflurane-maintained anesthesia on intraoperative hemodynamic stability and the need for vasoactive agents in patients undergoing cerebrovascular bypass surgery. Methods: Sixty-five patients were randomized into remimazolam (n = 31, remimazolam-based intravenous anesthesia) and control groups (n = 34, propofol-induced and desflurane-maintained anesthesia). The primary outcome was the occurrence of intraoperative hypotension. The secondary outcomes included hypotension duration, lowest mean BP (MBP), generalized average real variability (ARV) of MBP, and consumption of phenylephrine, norepinephrine, or remifentanil. Results: Occurrence rate and duration of hypotension were significantly lower in the remimazolam group (38.7% vs. 73.5%, P = 0.005; 0 [0, 10] vs. 7.5 [1.25, 25] min, P = 0.008). Remimazolam also showed better outcomes for lowest MBP (78 [73, 84] vs. 69.5 [66.25, 75.8] mmHg, P < 0.001) and generalized ARV of MBP (1.42 ± 0.49 vs. 1.66 ± 0.52 mmHg/min, P = 0.036). The remimazolam group required less phenylephrine (20 [0, 65] vs. 100 [60, 130] μg, P < 0.001), less norepinephrine (162 [0, 365.5] vs. 1335 [998.5, 1637.5] μg, P < 0.001), and more remifentanil (1750 [1454.5, 2184.5] vs. 531 [431, 746.5] μg, P < 0.001) than the control group. Conclusions Remimazolam anesthesia may provide better hemodynamic stability during cerebrovascular bypass surgery than propofol-induced and desflurane-maintained anesthesia.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Purpose: The Korean Cancer Study Group (KCSG) is a nationwide cancer clinical trial group dedicated to advancing investigator-initiated trials (IITs) by conducting and supporting clinical trials. This study aims to review IITs conducted by KCSG and quantitatively evaluate the survival and financial benefits of IITs for patients. Materials and Methods: We reviewed IITs conducted by KCSG from 1998 to 2023, analyzing progression-free survival (PFS) and overall survival (OS) gains for participants. PFS and OS benefits were calculated as the difference in median survival times between the intervention and control groups, multiplied by the number of patients in the intervention group. Financial benefits were assessed based on the cost of investigational products provided. Results: From 1998 to 2023, KCSG conducted 310 IITs, with 133 completed and published. Of these, 21 were included in the survival analysis. The analysis revealed that 1,951 patients in the intervention groups gained a total of 2,558.4 months (213.2 years) of PFS and 2,501.6 months (208.5 years) of OS, with median gains of 1.31 months in PFS and 1.58 months in OS per patient. When analyzing only statistically significant results, PFS and OS gain per patients was 1.69 months and 3.02 months, respectively. Investigational drug cost analysis from six available IITs indicated that investigational products provided to 252 patients were valued at 10,400,077,294 won (approximately 8,046,481 US dollars), averaging about 41,270,148 won (approximately 31,930 US dollars) per patient. Conclusion Our findings, based on analysis of published research, suggest that IITs conducted by KCSG led to survival benefits for participants and, in some studies, may have provided financial benefits by providing investment drugs.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Purpose: The Korean Cancer Study Group (KCSG) is a nationwide cancer clinical trial group dedicated to advancing investigator-initiated trials (IITs) by conducting and supporting clinical trials. This study aims to review IITs conducted by KCSG and quantitatively evaluate the survival and financial benefits of IITs for patients. Materials and Methods: We reviewed IITs conducted by KCSG from 1998 to 2023, analyzing progression-free survival (PFS) and overall survival (OS) gains for participants. PFS and OS benefits were calculated as the difference in median survival times between the intervention and control groups, multiplied by the number of patients in the intervention group. Financial benefits were assessed based on the cost of investigational products provided. Results: From 1998 to 2023, KCSG conducted 310 IITs, with 133 completed and published. Of these, 21 were included in the survival analysis. The analysis revealed that 1,951 patients in the intervention groups gained a total of 2,558.4 months (213.2 years) of PFS and 2,501.6 months (208.5 years) of OS, with median gains of 1.31 months in PFS and 1.58 months in OS per patient. When analyzing only statistically significant results, PFS and OS gain per patients was 1.69 months and 3.02 months, respectively. Investigational drug cost analysis from six available IITs indicated that investigational products provided to 252 patients were valued at 10,400,077,294 won (approximately 8,046,481 US dollars), averaging about 41,270,148 won (approximately 31,930 US dollars) per patient. Conclusion Our findings, based on analysis of published research, suggest that IITs conducted by KCSG led to survival benefits for participants and, in some studies, may have provided financial benefits by providing investment drugs.

Background: Maintenance of stable blood pressure (BP) during cerebrovascular bypass surgery is crucial to prevent cerebral ischemia. We compared the effect of remimazolam anesthesia with that of propofol-induced and desflurane-maintained anesthesia on intraoperative hemodynamic stability and the need for vasoactive agents in patients undergoing cerebrovascular bypass surgery. Methods: Sixty-five patients were randomized into remimazolam (n = 31, remimazolam-based intravenous anesthesia) and control groups (n = 34, propofol-induced and desflurane-maintained anesthesia). The primary outcome was the occurrence of intraoperative hypotension. The secondary outcomes included hypotension duration, lowest mean BP (MBP), generalized average real variability (ARV) of MBP, and consumption of phenylephrine, norepinephrine, or remifentanil. Results: Occurrence rate and duration of hypotension were significantly lower in the remimazolam group (38.7% vs. 73.5%, P = 0.005; 0 [0, 10] vs. 7.5 [1.25, 25] min, P = 0.008). Remimazolam also showed better outcomes for lowest MBP (78 [73, 84] vs. 69.5 [66.25, 75.8] mmHg, P < 0.001) and generalized ARV of MBP (1.42 ± 0.49 vs. 1.66 ± 0.52 mmHg/min, P = 0.036). The remimazolam group required less phenylephrine (20 [0, 65] vs. 100 [60, 130] μg, P < 0.001), less norepinephrine (162 [0, 365.5] vs. 1335 [998.5, 1637.5] μg, P < 0.001), and more remifentanil (1750 [1454.5, 2184.5] vs. 531 [431, 746.5] μg, P < 0.001) than the control group. Conclusions Remimazolam anesthesia may provide better hemodynamic stability during cerebrovascular bypass surgery than propofol-induced and desflurane-maintained anesthesia.