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Patients undergoing colectomy are at risk of numerous major complications. However, existing binary risk stratification models do not predict when a patient may be at highest risks of each complication. Accurate prediction of the timing of complications facilitates targeted, resource-efficient monitoring. We sought to develop and internally validate Cox proportional hazards models to predict time-to-complication of major complications within 30 days after elective colectomy. We studied a retrospective cohort from the multicentered American College of Surgeons National Surgical Quality Improvement Program procedure-targeted colectomy dataset. Patients aged 18 years or above, who underwent elective colectomy between January 1, 2014 and December 31, 2019 were included. A priori candidate predictors were selected based on variable availability, literature review, and multidisciplinary team consensus. Outcomes were mortality, hospital readmission, myocardial infarction, cerebral vascular events, pneumonia, venous thromboembolism, acute renal failure, and sepsis or septic shock within 30 days after surgery. The cohort consisted of 132145 patients (mean ± SD age, 61 ± 15 years; 52% females). Complication rates ranged between 0.3% (n = 383) for cardiac arrest and acute renal failure to 5.3% (n = 6986) for bleeding requiring transfusion, with readmission rate of 8.6% (n = 11415). We observed distinct temporal patterns for each complication: the median [quartiles] postoperative day of complication diagnosis ranged from 1 [0, 2] days for bleeding requiring transfusion to 12 [6, 18] days for venous thromboembolism. Models for mortality, myocardial infarction, pneumonia, and renal failure showed good discrimination with a concordance > 0.8, while models for readmission, venous thromboembolism, and sepsis performed poorly with a concordance of 0.6 to 0.7. Models exhibited good calibration but ranges were limited to low probability areas. We developed and internally validated time-to-event prediction models for complications after elective colectomy. Once further validated, the models can facilitate tailored monitoring of high risk patients during high risk periods. Clinicaltrials.gov (NCT05150548; Principal Investigator: Janny Xue Chen Ke, M.D., M.Sc., F.R.C.P.C.; initial posting: November 25, 2021).

Patients with COVID-19 undergoing hip fracture surgeries have a 30-day mortality of up to 34%. We aimed to evaluate the association between anesthesia technique and 30-day mortality after hip fracture surgery in patients with COVID-19. After ethics approval, we performed a retrospective cohort analysis of the American College of Surgeons National Surgical Quality Improvement Program data set from January to December 2021. Inclusion criteria were age ≥ 19 yr, laboratory-confirmed SARS-CoV-2 infection within 14 days preoperatively, and hip fracture surgery under general anesthesia (GA) or spinal anesthesia (SA). Exclusion criteria were American Society of Anesthesiologists Physical Status V, ventilator dependence, international normalized ratio ≥ 1.5, partial thromboplastin time > 35 sec, and platelet count < 80 × 10  L . The primary outcome was all-cause 30-day mortality. The adjusted association between anesthetic technique and 30-day mortality was analyzed using multivariable logistic regression. Of 23,045 patients undergoing hip fracture surgery, 331 patients met the study criteria. The median [interquartile range] age was 82 [74-88] yr, and 32.3% were male. The 30-day mortality rate was 10.0% (33/331) for the cohort (10.7%, 29/272 for GA vs 6.8%, 4/59 for SA; P = 0.51; standardized mean difference, 0.138). The use of SA, compared with GA, was not associated with decreased mortality (adjusted odds ratio, 0.61; 95% confidence interval, 0.21 to 1.8; E-value, 2.49). Anesthesia technique was not associated with mortality in patients with COVID-19 undergoing hip fracture surgery. The findings were limited by a small sample size. www. gov (NCT05133648); registered 24 November 2021.

PurposeNovel devices such as the barrier enclosure were developed in hopes of improving provider safety by limiting SARS-CoV-2 transmission during tracheal intubation. Nevertheless, concerns arose regarding a lack of rigorous efficacy and safety data for these devices. We conducted a randomized controlled trial to evaluate the impact of the barrier enclosure on time to tracheal intubation.MethodAfter Research Ethics Board approval, elective surgical patients with normal airway predictors were randomly allocated 1:1 to tracheal intubation with or without a barrier enclosure. The primary outcome was time to tracheal intubation. Secondary outcomes included first-pass success rate, total time of airway manipulation, anesthesiologists’ perception of intubation difficulty, likelihood of use in SARS-CoV-2-positive patients, and patients’ perception of comfort and acceptability.ResultsThere were 48 participants in the barrier enclosure group and 46 participants in the control group. The mean (standard deviation [SD]) time to tracheal intubation was 62 (29) sec with barrier closure and 53 (27) sec without barrier enclosure (mean difference, 9 sec; 95% confidence interval, − 3 to 20; P = 0.14). Anesthesiologists rated the difficulty of intubation higher with barrier enclosure (mean [SD] visual analogue scale score, 27 [26] mm vs 9 [17] mm; P < 0.001). There were no significant differences in other secondary outcomes.ConclusionIn healthy surgical patients with normal airway predictors, the use of a barrier enclosure during tracheal intubation did not significantly prolong time to intubation or decrease first-pass intubation success. Nevertheless, there was an increase in difficulty of intubation perceived by the anesthesiologists with use of a barrier enclosure.Trial registrationwww.clinicaltrials.gov (NCT04366141); registered 28 April 2020.

Purpose Patients with COVID-19 undergoing hip fracture surgeries have a 30-day mortality of up to 34%. We aimed to evaluate the association between anesthesia technique and 30-day mortality after hip fracture surgery in patients with COVID-19. Methods After ethics approval, we performed a retrospective cohort analysis of the American College of Surgeons National Surgical Quality Improvement Program data set from January to December 2021. Inclusion criteria were age ≥ 19 yr, laboratory-confirmed SARS-CoV-2 infection within 14 days preoperatively, and hip fracture surgery under general anesthesia (GA) or spinal anesthesia (SA). Exclusion criteria were American Society of Anesthesiologists Physical Status V, ventilator dependence, international normalized ratio ≥ 1.5, partial thromboplastin time > 35 sec, and platelet count < 80 × 10 9  L −1 . The primary outcome was all-cause 30-day mortality. The adjusted association between anesthetic technique and 30-day mortality was analyzed using multivariable logistic regression. Results Of 23,045 patients undergoing hip fracture surgery, 331 patients met the study criteria. The median [interquartile range] age was 82 [74–88] yr, and 32.3% were male. The 30-day mortality rate was 10.0% (33/331) for the cohort (10.7%, 29/272 for GA vs 6.8%, 4/59 for SA; P  = 0.51; standardized mean difference, 0.138). The use of SA, compared with GA, was not associated with decreased mortality (adjusted odds ratio, 0.61; 95% confidence interval, 0.21 to 1.8; E-value, 2.49). Conclusion Anesthesia technique was not associated with mortality in patients with COVID-19 undergoing hip fracture surgery. The findings were limited by a small sample size. Study registration www.ClinicalTrials.gov (NCT05133648); registered 24 November 2021.

BackgroundPatients undergoing colectomy are at risk of numerous major complications. However, existing binary risk stratification models do not predict when a patient may be at highest risks of each complication. Accurate prediction of the timing of complications facilitates targeted, resource-efficient monitoring. We sought to develop and internally validate Cox proportional hazards models to predict time-to-complication of major complications within 30 days after elective colectomy.MethodsWe studied a retrospective cohort from the multicentered American College of Surgeons National Surgical Quality Improvement Program procedure-targeted colectomy dataset. Patients aged 18 years or above, who underwent elective colectomy between January 1, 2014 and December 31, 2019 were included. A priori candidate predictors were selected based on variable availability, literature review, and multidisciplinary team consensus. Outcomes were mortality, hospital readmission, myocardial infarction, cerebral vascular events, pneumonia, venous thromboembolism, acute renal failure, and sepsis or septic shock within 30 days after surgery.ResultsThe cohort consisted of 132145 patients (mean ± SD age, 61 ± 15 years; 52% females). Complication rates ranged between 0.3% (n = 383) for cardiac arrest and acute renal failure to 5.3% (n = 6986) for bleeding requiring transfusion, with readmission rate of 8.6% (n = 11415). We observed distinct temporal patterns for each complication: the median [quartiles] postoperative day of complication diagnosis ranged from 1 [0, 2] days for bleeding requiring transfusion to 12 [6, 18] days for venous thromboembolism. Models for mortality, myocardial infarction, pneumonia, and renal failure showed good discrimination with a concordance > 0.8, while models for readmission, venous thromboembolism, and sepsis performed poorly with a concordance of 0.6 to 0.7. Models exhibited good calibration but ranges were limited to low probability areas.ConclusionsWe developed and internally validated time-to-event prediction models for complications after elective colectomy. Once further validated, the models can facilitate tailored monitoring of high risk patients during high risk periods.Trial registrationClinicaltrials.gov (NCT05150548; Principal Investigator: Janny Xue Chen Ke, M.D., M.Sc., F.R.C.P.C.; initial posting: November 25, 2021).

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1 , RBM20 , IRS2 , MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6 , SLAMF1 , APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D. Our understanding of the functional link between differential DNA methylation and type 2 diabetes and obesity remains limited. Here the authors present a blood-based EWAS of fasting glucose and insulin among 4808 non-diabetic Europeans and identify nine CpGs not previously implicated in glucose, insulin homeostasis and diabetes.

Resistance to TGF-β is frequently observed in ovarian cancer, and disrupted TGF-β/SMAD4 signaling results in the aberrant expression of downstream target genes in the disease. Our previous study showed that ADAM19, a SMAD4 target gene, is downregulated through epigenetic mechanisms in ovarian cancer with aberrant TGF-β/SMAD4 signaling. In this study, we investigated the mechanism of downregulation of FBXO32, another SMAD4 target gene, and the clinical significance of the loss of FBXO32 expression in ovarian cancer. Expression of FBXO32 was observed in the normal ovarian surface epithelium, but not in ovarian cancer cell lines. FBXO32 methylation was observed in ovarian cancer cell lines displaying constitutive TGF-β/SMAD4 signaling, and epigenetic drug treatment restored FBXO32 expression in ovarian cancer cell lines regardless of FBXO32 methylation status, suggesting that epigenetic regulation of this gene in ovarian cancer may be a common event. In advanced-stage ovarian tumors, a significant (29.3%; P<0.05) methylation frequency of FBXO32 was observed and the association between FBXO32 methylation and shorter progression-free survival was significant, as determined by both Kaplan–Meier analysis (P<0.05) and multivariate Cox regression analysis (hazard ratio: 1.003, P<0.05). Reexpression of FBXO32 markedly reduced proliferation of a platinum-resistant ovarian cancer cell line both in vitro and in vivo, due to increased apoptosis of the cells, and resensitized ovarian cancer cells to cisplatin. In conclusion, the novel tumor suppressor FBXO32 is epigenetically silenced in ovarian cancer cell lines with disrupted TGF-β/SMAD4 signaling, and FBXO32 methylation status predicts survival in patients with ovarian cancer.