Comparative investigation of neoadjuvant immunotherapy versus adjuvant immunotherapy in perioperative patients with cancer: a global-scale, cross-sectional, large-sample informatics study.

BACKGROUND: Neoadjuvant and adjuvant immunotherapies for cancer have evolved through a series of remarkable and critical research advances; however, addressing their similarities and differences is imperative in clinical practice. Therefore, this study aimed to examine their similarities and differences from the perspective of informatics analysis. METHODS: This cross-sectional study retrospectively analyzed extensive relevant studies published between 2014 and 2023 using stringent search criteria, excluding non-peer-reviewed and non-English documents. The main outcome variables are publication volume, citation volume, connection strength, occurrence frequency, relevance percentage, and development percentage. Furthermore, an integrated comparative analysis was conducted using unsupervised hierarchical clustering, spatiotemporal analysis, regression statistics, and Walktrap algorithm analysis. RESULTS: This analysis included 1,373 relevant studies. Advancements in neoadjuvant and adjuvant immunotherapies have been promising over the last decade, with an annual growth rate of 25.18% vs. 6.52% and global collaboration (International Co-authorships) of 19.93% vs. 19.84%. Respectively, five dominant research clusters were identified through unsupervised hierarchical clustering based on machine learning, among which Cluster 4 (Balance of neoadjuvant immunotherapy efficacy and safety) and Cluster 2 (Adjuvant immunotherapy clinical trials) (Average Publication Year [APY]: 2021.70±0.70 vs. 2017.54±4.59) are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including microsatellite instability (R2=0.7500, P=0.0025) and biomarkers (R2=0.6505, P=0.0086) in neoadjuvant scenarios, and the tumor microenvironment (R2=0.5571, P=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "neoadjuvant immunotherapy, non-small cell lung cancer (NSCLC), immune checkpoint inhibitors, melanoma" and "adjuvant immunotherapy, melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs. 100%, Development Percentage: 37.5% vs. 17.1%) are extremely relevant to this field but remain underdeveloped, highlighting the need for further investigation. CONCLUSION: This study identified pivotal research signatures and provided substantial predictions for neoadjuvant and adjuvant cancer immunotherapies. In addition, comprehensive quantitative comparisons revealed a notable shift in focus within this field, with neoadjuvant immunotherapy taking precedence over adjuvant immunotherapy after 2020; such a qualitative finding facilitate proper decision-making for subsequent research and mitigate the wastage of healthcare resources.

Repurposing sodium stibogluconate as an uracil DNA glycosylase inhibitor against prostate cancer using a time-resolved oligonucleotide-based drug screening platform.

Repurposing drugs can significantly reduce the time and costs associated with drug discovery and development. However, many drug compounds possess intrinsic fluorescence, resulting in aberrations such as auto-fluorescence, scattering and quenching, in fluorescent high-throughput screening assays. To overcome these drawbacks, time-resolved technologies have received increasing attention. In this study, we have developed a rapid and efficient screening platform based on time-resolved emission spectroscopy in order to screen for inhibitors of the DNA repair enzyme, uracil-DNA glycosylase (UDG). From a database of 1456 FDA/EMA-approved drugs, sodium stibogluconate was discovered as a potent UDG inhibitor. This compound showed synergistic cytotoxicity against 5-fluorouracil-resistant cancer cells. This work provides a promising future for time-resolved technologies for high-throughput screening (HTS), allowing for the swift identification of bioactive compounds from previously overlooked scaffolds due to their inherent fluorescence properties.

Covalent inhibition of epidermal growth factor receptor using a long-lived iridium(III)-afatinib probe.

The overexpression and overactivation of epidermal growth factor receptor (EGFR) are frequently observed in human cancers, including squamous cell carcinoma and adenocarcinoma. In this study, a covalent EGFR probe was developed by conjugating afatinib to an iridium(III) scaffold. Complex 1 showed enhanced luminescence in living epidermoid squamous carcinoma A431 cells compared to other cell lines, via engaging EGFR as confirmed via CETSA and knockdown experiments. Moreover, complex 1 inhibited downstream targets of EGFR in cellulo with repression persisting after removal of the complex, indicating an irreversible mode of inhibition. Finally, complex 1 showed potent antiproliferative activity against A431 cells with comparable potency to afatinib alone. To our knowledge, complex 1 is the first EGFR covalent inhibitor based on an iridium scaffold reported in the literature, with the potential to be further explored as a theranostic agent in the future.

Preoperative Nomogram and Risk Calculator for Postoperative Hypoxemia and Related Clinical Outcomes Following Stanford Type A Acute Aortic Dissection Surgery.

Background: Hypoxemia is a common complication after Stanford type A acute aortic dissection surgery (AADS), however, few studies about hypoxemia after AADS exist. The aims of this study were to identify independent risk factors for hypoxemia after AADS and to clarify its association with clinical outcomes. Methods: Patients undergoing AADS from 2016 to 2019 in our hospital were identified and used as a training set. Preoperative variables were first screened by univariate analysis and then entered into a multivariate logistic regression analysis to identify independent risk factors. A nomogram and an online risk calculator were constructed based on the logistic model to facilitate clinical practice and was externally validated in an independent dataset. Results: Severe hypoxemia developed in 119 of the 492 included patients (24.2%) and poorer clinical outcomes were observed in these patients. Five independent risk factors for severe hypoxemia after AADS were identified by multivariate analysis, including older age, smoking history, renal insufficiency, higher body mass index, and white blood cell count. The model showed good calibration, discrimination, and clinical utility in the training set, and was well validated in the validation set. Risk stratification was performed and three risk groups were defined as low, medium, and high risk groups. Hypertension was identified as an independent risk factor for moderate hypoxemia besides the five predictors mentioned above, and renal insufficiency was not significant for mild hypoxemia by multivariate analysis. In addition, although frozen elephant trunk was associated with increased risk of postoperative hypoxemia in the univariate analysis, frozen elephant trunk was also not identified as an independent risk factor for postoperative hypoxemia in the multivariate analysis. Conclusion: Hypoxemia was frequent following AADS, related to poorer clinical outcomes. Predictors were identified and a nomogram as well as an online risk calculator predicting severe hypoxemia after AADS was developed and validated, which may be helpful for risk estimation and perioperative management.

B-cell lymphoma 6 alleviates nonalcoholic fatty liver disease in mice through suppression of fatty acid transporter CD36.

Nonalcoholic fatty liver disease (NAFLD) is an ubiquitous disease that exists across a wide spectrum ranging from steatosis, steatohepatitis, advanced fibrosis, and liver cirrhosis. Hallmarks of NAFLD are lipid accumulation, insulin resistance, and chronic low-grade inflammation. However, there currently are no medications approved for NAFLD. B-cell lymphoma 6 (BCL6) is a transcriptional inhibitor that is vital for germinal center B-cell formation. Our study identified BCL6 as a critical modulator of hepatic lipid metabolism and appears to contribute to the initiation and progression of NAFLD. In our research, we induced hepatic BCL6 overexpression using adeno-associated virus (AAV), as well as conditional liver-specific BCL6 knockout mice (BCL6-CKO). With these models, we noted that BCL6 overexpression improved insulin resistance and hepatic steatosis in mice models maintained on a HFD diet. Conversely, these parameters worsened in the livers of mice with downregulated BCL6 levels. Mechanistically, the translocase fatty acid CD36 was determined to be a transcriptional target of BCL6 that influences its role in hepatic steatosis. BCL6 bound directly to the CD36 promoter region, restraining CD36 transcription under physiological conditions. We conclude that the hepatocyte BCL6 inhibits the NAFLD progression in mice, including deranged lipid accumulation and glucose metabolism, through a CD36-dependent manner. These results indicate that BCL6 may potentially be targeted in NAFLD treatment.

Nomogram for Postoperative Headache in Adult Patients Undergoing Elective Cardiac Surgery.

Background Postoperative headache (POH) is frequent after cardiac surgery; however, few studies on risk factors for POH exist. The aims of the current study were to explore risk factors related to POH after elective cardiac surgery and to establish a predictive system. Methods and Results Adult patients undergoing elective open-heart surgery under cardiopulmonary bypass from 2016 to 2020 in 4 cardiac centers were retrospectively included. Two thirds of the patients were randomly allocated to a training set and one third to a validation set. Predictors for POH were selected by univariate and multivariate analysis. POH developed in 3154 of the 13 440 included patients (23.5%) and the overall mortality rate was 2.3%. Eight independent risk factors for POH after elective cardiac surgery were identified, including female sex, younger age, smoking history, chronic headache history, hypertension, lower left ventricular ejection fraction, longer cardiopulmonary bypass time, and more intraoperative transfusion of red blood cells. A nomogram based on the multivariate model was constructed, with reasonable calibration and discrimination, and was well validated. Decision curve analysis revealed good clinical utility. Finally, 3 risk intervals were divided to better facilitate clinical application. Conclusions A nomogram model for POH after elective cardiac surgery was developed and validated using 8 predictors, which may have potential application value in clinical risk assessment, decision-making, and individualized treatment associated with POH.

Development and validation of a risk prediction model for postoperative pneumonia in adult patients undergoing Stanford type A acute aortic dissection surgery: a case control study.

BACKGROUND: Pneumonia is a common complication after Stanford type A acute aortic dissection surgery (AADS) and contributes significantly to morbidity, mortality, and length of stay. The purpose of this study was to identify independent risk factors associated with pneumonia after AADS and to develop and validate a risk prediction model. METHODS: Adults undergoing AADS between 2016 and 2019 were identified in a single-institution database. Patients were randomly divided into training and validation sets at a ratio of 2:1. Preoperative and intraoperative variables were included for analysis. A multivariate logistic regression model was constructed using significant variables from univariate analysis in the training set. A nomogram was constructed for clinical utility and the model was validated in an independent dataset. RESULTS: Postoperative pneumonia developed in 170 of 492 patients (34.6%). In the training set, multivariate analysis identified seven independent predictors for pneumonia after AADS including age, smoking history, chronic obstructive pulmonary disease, renal insufficiency, leucocytosis, low platelet count, and intraoperative transfusion of red blood cells. The model demonstrated good calibration (Hosmer-Lemeshow χ2 = 3.31, P = 0.91) and discrimination (C-index = 0.77) in the training set. The model was also well calibrated (Hosmer-Lemeshow χ2 = 5.73, P = 0.68) and showed reliable discriminatory ability (C-index = 0.78) in the validation set. By visual inspection, the calibrations were good in both the training and validation sets. CONCLUSION: We developed and validated a risk prediction model for pneumonia after AADS. The model may have clinical utility in individualized risk evaluation and perioperative management.

Development and validation of a nomogram model for pneumonia after redo cardiac surgery.

AIMS: Postoperative pneumonia (POP) after redo cardiac surgery is prevalent, associated with poor outcome. The aim of this study was to identify independent risk factors for POP after redo cardiac surgery and to develop and validate a prediction model. METHODS: Adults undergoing redo cardiac surgery from 2016 to 2019 were identified in a single-institution database. Using a 2: 1 ratio, the patients were randomly divided into training and validation sets. Univariate and multivariate analyses were applied to identify independent predictors for POP in the training set. A nomogram model was constructed for clinical utility and was validated in the validation set. RESULTS: POP developed in 72 of the 376 patients (19.1%). Four independent risk factors were identified, including age, chronic obstructive pulmonary disease, serum creatinine level and intraoperative blood transfusion volume. A nomogram based on the four predictors was constructed, with good discrimination in both the training (c-index: 0.86) and validation sets (c-index: 0.78). The model was well calibrated, with a Hosmer-Lemeshow χ 2 -value of 7.31 ( P   =  0.50) in the training set and 7.41 ( P   =  0.49) in the validation set. The calibration was also good by visual inspection. The decision and clinical impact curves of the nomogram indicated good clinical utility. Three risk intervals were identified based on the nomogram for better risk stratification. CONCLUSION: We developed and validated a nomogram model for POP after redo cardiac surgery. The model may have good clinical utility in risk evaluation and individualized treatment to reduce adverse events. Graphical abstract Incidence, risk factor, and outcomes of postoperative pneumonia after redo cardiac surgery: http://links.lww.com/JCM/A445 .

Nomogram Models to Predict Postoperative Hyperlactatemia in Patients Undergoing Elective Cardiac Surgery.

Objectives: Postoperative hyperlactatemia (POHL) is common in patients undergoing cardiac surgery and is associated with poor outcomes. The purpose of this study was to develop and validate two predictive models for POHL in patients undergoing elective cardiac surgery (ECS). Methods: We conducted a multicenter retrospective study enrolling 13,454 adult patients who underwent ECS. All patients involved in the analysis were randomly assigned to a training set and a validation set. Univariate and multivariate analyses were performed to identify risk factors for POHL in the training cohort. Based on these independent predictors, the nomograms were constructed to predict the probability of POHL and were validated in the validation cohort. Results: A total of 1,430 patients (10.6%) developed POHL after ECS. Age, preoperative left ventricular ejection fraction, renal insufficiency, cardiac surgery history, intraoperative red blood cell transfusion, and cardiopulmonary bypass time were independent predictors and were used to construct a full nomogram. The second nomogram was constructed comprising only the preoperative factors. Both models showed good predictive ability, calibration, and clinical utility. According to the predicted probabilities, four risk groups were defined as very low risk (<0.05), low risk (0.05-0.1), medium risk (0.1-0.3), and high risk groups (>0.3), corresponding to scores of ≤ 180 points, 181-202 points, 203-239 points, and >239 points on the full nomogram, respectively. Conclusions: We developed and validated two nomogram models to predict POHL in patients undergoing ECS. The nomograms may have clinical utility in risk estimation, risk stratification, and targeted interventions.

Development and validation of a nomogram model for early postoperative hyperlactatemia in patients undergoing cardiac surgery.

BACKGROUND: Postoperative hyperlactatemia (POHL) is common in patients undergoing cardiac surgery, associated with adverse outcomes. The aim of this study was to identify predictors for POHL after cardiac surgery and to develop and validate a predictive model. METHODS: Adult patients who underwent open heart surgery at our institution between 2016 and 2019 were retrospectively included. The patients were randomly divided into training and validation groups at a 2:1 ratio. Multivariate logistic regression was performed to identify independent predictors for POHL in the training set. A nomogram was then constructed and was validated in the validation set. RESULTS: POHL developed in 713 of the 5,323 patients (13.4%). The mortality rate was higher in patients with POHL compared with patients without that (9.5% vs. 2.1%, P<0.001). Age, white blood cell (WBC) count, left ventricular ejection fraction, renal insufficiency, cardiac surgery history, red blood cell (RBC) transfusion, and cardiopulmonary bypass (CPB) time were identified as independent risk factors. The nomogram based on these predictors indicated good discrimination in both the training (c-index: 0.787) and validation (c-index: 0.820) sets. The calibration was reasonable by both visual inspection and goodness-of-fit test. The decision and clinical impact curves demonstrated good clinical utility. CONCLUSIONS: We identified 7 independent risk factors and derived a prediction model for POHL in patients undergoing cardiac surgery. The model may contribute significantly to early risk assessment and clinical intervention.

Development and Validation of Nomogram Models for Postoperative Pneumonia in Adult Patients Undergoing Elective Cardiac Surgery.

Background: Postoperative pneumonia (POP) is a frequent complication following cardiac surgery, related to increased morbidity, mortality and healthcare costs. The objectives of this study were to investigate the risk factors associated with POP in adults undergoing elective cardiac surgery and to develop and validate nomogram models. Methods: We conducted a multicenter retrospective study in four cardiac centers in China. Adults operated with elective open-heart surgery from 2016 to 2020 were included. Patients were randomly allocated to training and validation sets by 7:3 ratio. Demographics, comorbidities, laboratory data, surgical factors, and postoperative outcomes were collected and analyzed. Risk factors for POP were identified by univariate and multivariate analysis. Nomograms were constructed based on the multivariate logistic regression models and were evaluated with calibration, discrimination and decision curve analysis. Results: A total of 13,380 patients meeting the criteria were included and POP developed in 882 patients (6.6%). The mortality was 2.0%, but it increased significantly in patients with POP (25.1 vs. 0.4%, P < 0.001). Using preoperative and intraoperative variables, we constructed a full nomogram model based on ten independent risk factors and a preoperative nomogram model based on eight preoperative factors. Both nomograms demonstrated good calibration, discrimination, and were well validated. The decision curves indicated significant clinical usefulness. Finally, four risk intervals were defined for better clinical application. Conclusions: We developed and validated two nomogram models for POP following elective cardiac surgery using preoperative and intraoperative factors, which may be helpful for individualized risk evaluation and prevention decisions.

Clinical risk score for postoperative pneumonia following heart valve surgery.

BACKGROUND: Postoperative pneumonia (POP) is one of the most common infections following heart valve surgery (HVS) and is associated with a significant increase in morbidity, mortality, and health care costs. This study aimed to identify the major risk factors associated with the occurrence of POP following HVS and to derive and validate a clinical risk score. METHODS: Adults undergoing open HVS between January 2016 and December 2019 at a single institution were enrolled in this study. Patients were randomly assigned to the derivation and validation sets at 1:1 ratio. A prediction model was developed with multivariable logistic regression analysis in the derivation set. Points were assigned to independent risk factors based on their regression coefficients. RESULTS: POP occurred in 316 of the 3853 patients (8.2%). Multivariable analysis identified ten significant predictors for POP in the derivation set, including older age, smoking history, chronic obstructive pulmonary disease, diabetes mellitus, renal insufficiency, poor cardiac function, heart surgery history, longer cardiopulmonary bypass, blood transfusion, and concomitant coronary and/or aortic surgery. A 22-point risk score based on the multivariable model was then generated, demonstrating good discrimination (C-statistic: 0.81), and calibration (Hosmer-Lemeshow χ2 = 8.234, P = 0.312). The prediction rule also showed adequate discriminative power (C-statistic: 0.83) and calibration (Hosmer-Lemeshow χ2 = 5.606, P = 0.691) in the validation set. Three risk intervals were defined as low-, medium-, and high-risk groups. CONCLUSION: We derived and validated a 22-point risk score for POP following HVS, which may be useful in preventive interventions and risk management. TRIAL REGISTRATION: Chictr.org, ChiCTR1900028127; http://www.chictr.org.cn/showproj.aspx?proj=46932.

Risk factors and in-hospital mortality of postoperative hyperlactatemia in patients after acute type A aortic dissection surgery.

BACKGROUND: Hyperlactatemia may be caused by increased production due to tissue hypoxia or non-hypoxia. The aim of this study was first to identify risk factors for postoperative hyperlactatemia (POHL) after Stanford type A acute aortic dissection surgery (AADS) and construct a predictive model, and second to evaluate the impact of POHL on prognosis. METHODS: This retrospective study involved patients undergoing AADS from January 2016 to December 2019 in Wuhan Union Hospital. Multivariate logistic regression analysis was performed to identify independent risk factors for POHL. A nomogram predicting POHL was established based on these factors and was validated in the original dataset. The receiver operating characteristic curve was drawn to assess the ability of postoperative lactate levels to predict the in-hospital mortality. RESULTS: A total of 188 patients developed POHL after AADS (38.6%). Male gender, surgery history, red blood cell transfusion and cardiopulmonary bypass time were identified as independent predictors. The C-index of the prediction model for POHL was 0.72, indicating reasonable discrimination. The model was well calibrated by visual inspection and goodness-of-fit test (Hosmer-Lemeshow χ2 = 10.25, P = 0.25). Decision and clinical impact curves of the model showed good clinical utility. The overall in-hospital mortality rate was 10.1%. Postoperative lactate levels showed a moderate predictive power for postoperative in-hospital mortality (C-index: 0.72). CONCLUSION: We developed and validated a prediction model for POHL in patients undergoing AADS, which may have clinical utility in personal risk evaluation and preventive interventions. The POHL could be a good predictor for in-hospital mortality.

Ablation of Survivin in T Cells Attenuates Acute Allograft Rejection after Murine Heterotopic Heart Transplantation by Inducing Apoptosis.

Although studies in oncology have well explored the pharmacological effects of Birc5, little is known about its role in allogeneic T-cell responses. Therefore, the present study used a mouse model of acute heart allograft rejection to investigate the protective effect and mechanism of conditional knockout of Birc5 in T cells. Survivin (encoded by Birc5) was up-regulated in T cells activated in vivo and in vitro. Deletion of Birc5 in T cells attenuated acute heart allograft rejection by reducing the ratio of effector to naive T cells and Th1 to Tregs. In addition, deletion of Birc5 had no noticeable effect on proliferation but on apoptosis and the secretion of IFN-γ. The results revealed a significant increase in the percentage of Annexin V positive CD4+ T cells in the Birc5-/- group, compared to the WT. Moreover, there was significant increase in early apoptotic alloreactive T cells in Birc5-/- mice and this was partly mediated by caspase-3. Furthermore, treatment with YM155 inhibited acute heart allograft rejection in vivo and increased T-cell apoptosis in healthy human PBMCs in vitro. The results highlight a potential therapeutic target for the prevention and treatment of acute transplant rejection.

Predictors and nomogram models for postoperative headache in patients undergoing heart valve surgery.

BACKGROUND: Headache is a frequent complication after cardiac surgery. However, studies on the risk factors of postoperative headache (POH) are rare. The purpose of this study was to identify independent risk factors for POH in patients undergoing heart valve surgery (HVS) and to develop and validate risk prediction models. METHODS: Consecutive patients undergoing open HVS from 2016 to 2019 were enrolled in this study. Patients were randomly assigned to training and validation sets at a 2:1 ratio. Univariate and multivariate analysis were applied to identify independent predictors for POH in the training set. A nomogram predicting POH was developed based on these factors, and was validated in the independent validation set. RESULTS: POH developed in 1,061 of the 3,853 patients (27.5%). The overall mortality was 2.9%, and it was significantly higher in patients with POH (4.3% versus 2.4%, P<0.001). In the training set, six independent predictors were identified by multivariate analysis, including female, smoking history, hypertension, headache history, left ventricular ejection fraction, and cardiopulmonary bypass time. The model demonstrated good discrimination in both the training (c-index: 0.811) and validation sets (c-index: 0.814), and calibration was assessed by visual inspection. A second nomogram was also constructed including only preoperative predictors, with good discrimination (c-index: 0.792) and calibration. The decision and clinical impact curves of the models showed good clinical utility. CONCLUSIONS: We developed and validated two risk prediction models for POH in patients undergoing HVS. The models may have clinical utility in individualized risk assessment and preventive interventions.

Risk factors for postoperative pneumonia after cardiac surgery: a prediction model.

BACKGROUND: Postoperative pneumonia is the main infectious complication following cardiac surgery and is associated with significant increases in morbidity, mortality and health care costs. The aim of this study was to identify potential risk factors related to the occurrence of postoperative pneumonia in adult patients undergoing cardiac surgery and to develop a predictive system. METHODS: Adult patients who underwent open heart surgery in our institution between 2016 and 2019 were enrolled in this study. Preoperative and intraoperative variables were collected and analyzed. A multivariate prediction model for evaluating the risk of postoperative pneumonia was established using logistic regression analysis via forward stepwise selection, and points were assigned to significant risk factors based on their regression coefficient values. RESULTS: Postoperative pneumonia occurred in 530 of the 5,323 patients (9.96%). Prolonged stays in the postoperative intensive care unit (ICU) and hospital, as well as higher mortality (25.66% versus 0.65%), were observed in patients with postoperative pneumonia. Multivariate analysis identified 13 independent risk factors including patient demographics, comorbidities, cardiac function, cardiopulmonary bypass (CPB) duration, and blood transfusion. The prediction model showed good discrimination (C-statistic: 0.80) and was well calibrated (Hosmer-Lemeshow χ2=7.907, P value =0.443). A 32-point risk score was generated, and then three risk intervals were defined. CONCLUSIONS: We derived and validated a prediction model for postoperative pneumonia after cardiac surgery incorporating 13 easily discernible risk factors. The scoring system may be helpful for individualized risk estimations and clinical decision-making.

Incidence, Risk Factors and Outcomes of Postoperative Headache After Stanford Type a Acute Aortic Dissection Surgery.

Background: Postoperative headache (POH) is common in clinical practice, however, no studies about POH after Stanford type A acute aortic dissection surgery (AADS) exist. This study aims to describe the incidence, risk factors and outcomes of POH after AADS, and to construct two prediction models. Methods: Adults who underwent AADS from 2016 to 2020 in four tertiary hospitals were enrolled. Training and validation sets were randomly assigned according to a 7:3 ratio. Risk factors were identified by univariate and multivariate logistic regression analysis. Nomograms were constructed and validated on the basis of independent predictors. Results: POH developed in 380 of the 1,476 included patients (25.7%). Poorer outcomes were observed in patients with POH. Eight independent predictors for POH after AADS were identified when both preoperative and intraoperative variables were analyzed, including younger age, female sex, smoking history, chronic headache history, cerebrovascular disease, use of deep hypothermic circulatory arrest, more blood transfusion, and longer cardiopulmonary bypass time. White blood cell and platelet count were also identified as significant predictors when intraoperative variables were excluded from the multivariate analysis. A full nomogram and a preoperative nomogram were constructed based on these independent predictors, both demonstrating good discrimination, calibration, clinical usefulness, and were well validated. Risk stratification was performed and three risk intervals were defined based on the full nomogram and clinical practice. Conclusions: POH was common after AADS, portending poorer outcomes. Two nomograms predicting POH were developed and validated, which may have clinical utility in risk evaluation, early prevention, and doctor-patient communication.

A Predictive Scoring Model for Postoperative Tracheostomy in Patients Who Underwent Cardiac Surgery.

BACKGROUND: A subset of patients require a tracheostomy as respiratory support in a severe state after cardiac surgery. There are limited data to assess the predictors for requiring postoperative tracheostomy (POT) in cardiac surgical patients. METHODS: The records of adult patients who underwent cardiac surgery from 2016 to 2019 at our institution were reviewed. Univariable analysis was used to assess the possible risk factors for POT. Then multivariable logistic regression analysis was performed to identify independent predictors. A predictive scoring model was established with predictor assigned scores derived from each regression coefficient divided by the smallest one. The area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the discrimination and calibration of the risk score, respectively. RESULTS: A total of 5,323 cardiac surgical patients were included, with 128 (2.4%) patients treated with tracheostomy after cardiac surgery. Patients with POT had a higher frequency of readmission to the intensive care unit (ICU), longer stay, and higher mortality (p < 0.001). Mixed valve surgery and coronary artery bypass grafting (CABG), aortic surgery, renal insufficiency, diabetes mellitus, chronic obstructive pulmonary disease (COPD), pulmonary edema, age >60 years, and emergent surgery were independent predictors. A 9-point risk score was generated based on the multivariable model, showing good discrimination [the concordance index (c-index): 0.837] and was well-calibrated. CONCLUSIONS: We established and verified a predictive scoring model for POT in patients who underwent cardiac surgery. The scoring model was conducive to risk stratification and may provide meaningful information for clinical decision-making.

Clinical study on the surgical treatment of atypical Lisfranc joint complex injury.

BACKGROUND: Lisfranc injuries have not received much attention by orthopedic doctors in the past, and there is little related research on the diagnosis and treatment of these injuries. In recent years with the rise in foot and ankle surgery, doctors are now paying more attention to this type of injury. However, there is still a high rate of missed diagnosis due to insufficient attention causing treatment delays or inadequate treatments, which eventually result in greater sequelae; including long-term pain, arthritis, foot deformity etc. In particular, for cases with a mild Lisfranc joint complex injury, the incidence of sequelae is higher. AIM: To select an active surgical treatment for an atypical Lisfranc joint complex injury and to evaluate the clinical efficacy of the surgical treatment. METHODS: The clinical data of 18 patients, including 10 males and 8 females aged 20-64 years with Lisfranc injuries treated in our department from January 2017 to September 2019 were retrospectively analyzed. All patients were treated with an open reduction and internal fixation method using locking titanium mini-plates and hollow screws or Kirschner wires. X-ray images were taken and follow-up was performed monthly after the operation; the internal fixation was then removed 4-5 mo after the operation; and the American Orthopedic Foot and Ankle Society (AOFAS) score was used for evaluation on the last follow-up. RESULTS: All patients were followed up for 6-12 mo. A good/excellent AOFAS score was observed in 88.9% of patients. CONCLUSION: For atypical Lisfranc joint complex injuries, active open reduction and internal fixation can be performed to enable patients to obtain a good prognosis and satisfactory functional recovery.

Autophagy-lysosome inhibitor chloroquine prevents CTLA-4 degradation of T cells and attenuates acute rejection in murine skin and heart transplantation.

Background: The immune checkpoint cytotoxic T lymphocyte antigen-4 (CTLA-4), induced upon T cell activation but degraded quickly, has been targeted in the clinical therapy of advanced cancers and autoimmune diseases. However, whether inhibiting CTLA-4 degradation ameliorates transplant rejection remains unknown. Methods: The CTLA-4 expression in activated murine T cells treated with the inhibitors mediating protein degradation was detected by flow cytometry (FCM). CD45.1 mice, which received TEa T cells and underwent heart transplantation, were administrated with the inhibitor. Subsequently, CTLA-4 expression of TEa T cells was analyzed. Murine skin and heart transplantation models were built, then the survival and histopathology of the allografts, and T cell subsets in the spleens of each group were compared. Results: Chloroquine (CQ) was identified as an inhibitor of CTLA-4 degradation, which augmented both surface and total CTLA-4 expression in T cells. It considerably prolonged the skin and heart allograft survival time and reduced the infiltration of inflammatory cells in allografts. Besides decreasing the frequencies of the CD4+ and CD8+ effector T cells, especially IFN-γ producing T cells, CQ also increased the proportion of regulatory T cells in the spleen. The CTLA-4 blockade abrogated the benefits of CQ on the survival of heart allografts. Moreover, CQ enhanced CTLA-4 expression in activated human T cells and reduced the secretion of IFN-γ in human mixed lymphocyte reaction. Conclusion: Targeting CTLA-4 degradation provides a novel means to prevent transplant rejection and induce transplant tolerance.