Design and rationale of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study: A cluster randomized controlled trial for hypertension management in primary care.

BACKGROUND: Hypertension management in China is suboptimal with high prevalence and low control rate due to various barriers, including lack of self-management awareness of patients and inadequate capacity of physicians. Digital therapeutic interventions including mobile health and computational device algorithms such as clinical decision support systems (CDSS) are scalable with the potential to improve blood pressure (BP) management and strengthen the healthcare system in resource-constrained areas, yet their effectiveness remains to be tested. The aim of this report is to describe the protocol of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study assessing the effect of a multifaceted hypertension management system for supporting patients and physicians on BP lowering in primary care settings. MATERIALS AND METHODS: The CHESS evaluation study is a parallel-group, cluster-randomized controlled trial conducted in primary care settings in China. Forty-one primary care sites from 3 counties of China are randomly assigned to either the usual care or the intervention group with the implementation of the CHESS system, more than 1,600 patients aged 35 to 80 years with uncontrolled hypertension and access to a smartphone by themselves or relatives are recruited into the study and followed up for 12 months. In the intervention group, participants receive patient-tailored reminders and alerts via messages or intelligent voice calls triggered by uploaded home blood pressure monitoring data and participants' characteristics, while physicians receive guideline-based prescription instructions according to updated individual data from each visit, and administrators receive auto-renewed feedback of hypertension management performance from the data analysis platform. The multiple components of the CHESS system can work synergistically and have undergone rigorous development and pilot evaluation using a theory-informed approach. The primary outcome is the mean change in 24-hour ambulatory systolic BP from baseline to 12 months. DISCUSSION: The CHESS trial will provide evidence and novel insight into the effectiveness and feasibility of an implementation strategy using a comprehensive digital BP management system for reducing hypertension burden in primary care settings. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov, NCT05605418.

A Comprehensive Patient Blood Management Program During Cardiopulmonary Bypass in Patients Over 60 Years of Age.

Purpose: There is currently no consensus on the most appropriate blood transfusion strategy for older adults undergoing cardiovascular surgery. We aimed to investigate the potential benefits of the patient blood management (PBM) program specifically for advanced age patients, and to evaluate the relationship of age and PBM in cardiovascular surgery. Patients and Methods: We collected data from patients over 60 years old who underwent on-pump cardiovascular surgery. We compared transfusion and clinical outcomes between the pre-PBM and post-PBM groups using a propensity score matching method. Then, we conducted a subgroup analysis within the original cohort, specifically focusing on patients aged of 75 and above with multivariable adjusted models. Results: Data of 9703 older adults were analyzed. Red blood cell (RBC) transfusion rates during cardiopulmonary bypass (CPB) (31.6% vs 13.1%, P<0.001), during the operation (50.8% vs 39.0%, P<0.001) and after the operation (5.6% vs 3.1%, P<0.001) were significantly reduced, and mortality and the risk of some adverse events were also reduced after the PBM. Subgroup analysis showed that there was no interaction between age and PBM, and advanced age (over age 75) did not modify the effect of PBM program in reducing RBC transfusion (Pinteraction=0.245), on mortality (Pinteration=0.829) and on certain complications. Conclusion: The comprehensive PBM program could reduce RBC transfusion without adverse outcomes in older patients undergoing CPB. Even patients over age 75 may benefit from a more stringent transfusion indication. Comprehensive blood conservation measures should be applied to optimize the blood management for older patients.

The Status Quo of Internet Medical Services in China: A Nationwide Hospital Survey.

Background: Internet medical services (IMS) have been rapidly promoted across China, especially since the outbreak of COVID-19. However, a nationwide study is still lacking. Objective: To unveil the whole picture of IMS across tertiary and secondary hospitals in China, and to evaluate potential influence of the hospital general characteristics, medical staff reserve, and patient visiting capacity on IMS provision. Methods: An online cross-sectional survey was conducted, and 1,995 tertiary and 2,824 secondary hospitals completed questionnaires from 31 administrative regions in China during July 1 and October 31, 2021. Those hospitals are defined having abilities of providing IMS if at least one following service are available: (1) online appointment of diagnoses and treatments; (2) online disease consultation; (3) electronic prescription; and (4) drug delivery. The logistic regression models are used to detect the possible roles on developing IMS. Results: A majority (68.9%) of tertiary hospitals and 53.0% secondary hospitals have provided IMS (p < 0.01). Tertiary hospital also had much higher proportions than secondary hospitals in online appointment of diagnoses and treatments (62.6% vs. 46.1%), online disease consultation (47.3% vs. 16.9%), electronic prescription (33.2% vs. 9.6%), and drug delivery (27.8% vs. 4.6%). In multivariate model, IMS hospitals may be associated significantly with having more licensed doctors (≥161 vs. <161: odds ratio [OR], 1.30; 1.13-1.50; p < 0.01), having more frequency of registration appointments (≥3,356 vs. <3,356: OR, 1.77; 1.54-2.03; p < 0.01), having higher frequency of patient follow-ups (≥1,160 vs. <1,160: OR, 1.36; 1.15-1.61; p < 0.01), having laboratory test appointments (Yes vs. No: OR, 1.25; 1.06-1.48; p = 0.01), and having treatment appointments (Yes vs. No: OR, 1.27; 1.11-1.46; p < 0.01) in the past 3 months. Conclusions: The coverage of IMS is appreciable in China, but the IMS market is still greatly extended and improved. The provision of IMS depends primarily on the scales of the hospitals, including medical staff reserve and patient visiting capacity.

Needle-Perc-Assisted Endoscopic Surgery in Treatment with Renal Staghorn Stones: A Prospective Randomized Controlled Study from a Large-Volume Stone Center.

INTRODUCTION: The goal of this study was to evaluate the efficacy and safety of needle-perc-assisted endoscopic surgery (NAES) in the treatment of staghorn renal stones via a single-center prospective randomized controlled study. METHODS: A total of 219 patients with partial or complete staghorn renal stones were prospectively randomized into two groups between January 2020 and April 2022. In group A (n = 112), patients were treated with traditional standard access, multiple if necessary, and in group B (n = 107), only one standard access was made, and needle-perc was assisted to remove the residual stones in the same stage. All procedures were guided under ultrasound totally. Stone size, operating time, blood loss, pain score, complications, and other related characteristics were monitored and analyzed. RESULTS: Procedures were successful in all patients. The baseline characters were similar between the groups. The mean stone size was comparable (4.5 ± 1.4 vs. 4.7 ± 1.7, p = 0.35). The 1-month stone-free status was achieved in 85 patients (75.9%) in group A and 80 (74.8%) patients in group B (p = 0.72). The operation time was shorter in group A than B (75.1 ± 28.1 min vs. 97.2 ± 20.4 min, p = 0.02). A less blood loss (p = 0.01), shorter hospital stay (p = 0.04), lower pain score (p = 0.04), and lower severe complication rates (p = 0.03) were observed in group B. CONCLUSION: NAES reveals better postoperative recurrence compared with traditional multiple tracts method for treating staghorn renal stones. The stone-free rate was comparable between the two groups.

Needle-perc-assisted endoscopic surgery (NAES) for patients with complicated solitary kidney stones: a prospective randomized study from a single center.

PURPOSE: The goal of this study is to compare traditional percutaneous nephrolithotomy (PCNL) and needle-perc-assisted endoscopic surgery (NAES) in the treatment of complicated solitary kidney stones via a single-center randomized controlled prospective study. METHODS: A total of patients with complex (Guy's score II-IV) solitary kidney stones between July 2019 to June 2022 were enrolled in the study. Participants were stratified into two groups: needle-perc-assisted endoscopic surgery group (group A) and traditional PCNL group (group B). All procedures were finished by X-ray free technique. The clinical characteristics and outcomes were analyzed. RESULTS: A total of 90 (44 in Group A and 46 in Group B) patients were finally included in our study. There were no statistically differences in terms of gender, age, body mass index (BMI), stone burden between two groups. The mean operative duration of Group A was significant higher than group B (95.1 ± 21.4 min vs 72.5 ± 29.5 min, p=0.02). The 1-month stone-free rate (SFR) was significant higher in Group A than B (90.9% vs 73.9%, p=0.03). A less hemoglobin drop (p=0.01), shorter postoperative in-hospital day (p=0.04), and lower severe complication (Clavien-Dindo III and above) rates (p=0.03) were observed in Group A. CONCLUSION: For patients with solitary kidney stones, NAES technique provides a higher one-session SFR, a better renal function recovery and compared with traditional PCNL.

A transfusion risk stratification score to facilitate quality management in cardiopulmonary bypass.

BACKGROUND: Our previous showed that a blood management program in the cardiopulmonary bypass (CPB) department, reduced red blood cell (RBC) transfusion and complications, but assessing transfusion practice solely based on transfusion rates was insufficient. This study aimed to design a risk stratification score to predict perioperative RBC transfusion to guide targeted measures for on-pump cardiac surgery patients. STUDY DESIGN AND METHODS: We analyzed data from 42,435 adult cardiac patients. Eight predictors were entered into the final model including age, sex, anemia, New York Heart Association classification, body surface area, cardiac surgery history, emergency surgery, and surgery type. We then simplified the score to an integer-based system. The area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and a calibration curve were used for its performance test. The score was compared to existing scores. RESULTS: The final score included eight predictors. The AUC for the model was 0.77 (95% CI, 0.76-0.77) and 0.77 (95% CI, 0.76-0.78) in the training and test set, respectively. The calibration curves showed a good fit. The risk score was finally grouped into low-risk (score of 0-13 points), medium-risk (14-19 points), and high-risk (more than 19 points). The score had better predictive power compared to the other two existing risk scores. DISCUSSION: We developed an effective risk stratification score with eight variables to predict perioperative RBC transfusion for on-pump cardiac surgery. It assists perfusionists in proactively preparing blood conservation measures for high-risk patients before surgery.

Dynamic predictive scores for cardiac surgery-associated agitated delirium: a single-center retrospective observational study.

BACKGROUND: Prevention, screening, and early treatment are the aims of postoperative delirium management. The scoring system is an objective and effective tool to stratify potential delirium risk for patients undergoing cardiac surgery. METHODS: Patients who underwent cardiac surgery between January 1, 2012, and January 1, 2019, were enrolled in our retrospective study. The patients were divided into a derivation cohort (n = 45,744) and a validation cohort (n = 11,436). The AD predictive systems were formulated using multivariate logistic regression analysis at three time points: preoperation, ICU admittance, and 24 h after ICU admittance. RESULTS: The prevalence of AD after cardiac surgery in the whole cohort was 3.6% (2,085/57,180). The dynamic scoring system included preoperative LVEF ≤ 45%, serum creatinine > 100 µmol/L, emergency surgery, coronary artery disease, hemorrhage volume > 600 mL, intraoperative platelet or plasma use, and postoperative LVEF ≤ 45%. The area under the receiver operating characteristic curve (AUC) values for AD prediction were 0.68 (preoperative), 0.74 (on the day of ICU admission), and 0.75 (postoperative). The Hosmer‒Lemeshow test indicated that the calibration of the preoperative prediction model was poor (P = 0.01), whereas that of the pre- and intraoperative prediction model (P = 0.49) and the pre, intra- and postoperative prediction model (P = 0.35) was good. CONCLUSIONS: Using perioperative data, we developed a dynamic scoring system for predicting the risk of AD following cardiac surgery. The dynamic scoring system may improve the early recognition of and the interventions for AD.

Evaluation of the effectiveness and safety of a multi-faceted computerized antimicrobial stewardship intervention in surgical settings: A single-centre cluster-randomized controlled trial.

BACKGROUND: Inappropriate antimicrobial use is common among patients undergoing surgery. It remains unclear whether a multi-faceted computerized antimicrobial stewardship programme is effective and safe in reducing inappropriate antimicrobial use in surgical settings. METHODS: A multi-faceted computerized antimicrobial stewardship intervention system was developed, and an open-label, cluster-randomized, controlled trial was conducted among 18 surgical teams that enrolled 2470 patients for open chest cardiovascular surgery. The surgical teams were divided at random into intervention and control groups at a ratio of 1:1. The primary endpoints were days of therapy (DOT)/1000 patient-days, defined daily dose (DDD)/1000 patient-days and length of therapy (LOT)/1000 patient-days. RESULTS: Mean DOT, DDD and LOT per 1000 patient-days were significantly lower in the intervention group compared with the control group (472.2 vs 539.8, 459.5 vs 553.8, and 438.4 vs 488.7; P<0.05), with reductions of 14.2% [95% confidence interval (CI) 11.8-16.7%], 18.7% (95% CI 15.9-21.4%) and 11.9% (95% CI 9.6-14.1%), respectively. The daily risk of inappropriate antimicrobial use after discharge from the intensive care unit decreased by 23.9% [95% CI 15.5-31.5% (incidence risk ratio 0.76, 95% CI 0.69-0.85)] in the intervention group. There was no significant difference in rates of infection or surgical-related complications between the groups. Median antimicrobial costs were significantly lower in the intervention group {873.4 [interquartile range (IQR) 684.5-1255.4] RMB vs 1178.7 (IQR 869.1-1814.5) RMB; P<0.001} (1 RMB approximately equivalent to 0.16 US$ in 2022). CONCLUSIONS: The multi-faceted computerized antimicrobial stewardship interventions reduced inappropriate antimicrobial use safely. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov: NCT04328090.

Automated ICD coding for coronary heart diseases by a deep learning method.

Automated ICD coding via machine learning that focuses on some specific diseases has been a hot topic. As one of the leading causes of death, coronary heart diseases (CHD) have seldom been specifically studied by related research, probably due to lack of data concretely targeting at the diseases. Based on Fuwai-CHD and MIMIC-III-CHD, which are a private dataset from Fuwai Hospital and the CHD-related subset of a public dataset named MIMIC-III respectively, this study aimed at automated CHD coding by a deep learning method, which mainly consists of three modules. The first is a B ERT variant module responsible for encoding clinical text. In the module, we fine-tuned BERT variants with masked language model on clinical text, and proposed a truncation method to tackle the problem that BERT variants generally cannot handle sequences containing more than 512 tokens. The second is a word2vec module for encoding code titles and the third is a label-attention module for integrating the embeddings of clinical text and code titles. In short, we named the method BW_att. We compared BW_att against some widely studied baselines, and found that BW_att performed best in most of the coding missions. Specifically, BW_att reached a Macro-F1 of 96.2% and a Macro-AUC of 98.9% for the top-100 most frequent codes in Fuwai-CHD, which covered 89.2% of the total code occurrences. When predicting the top-50 most frequent codes in MIMIC-III-CHD, BW_att reached a Macro-F1 of 40.5% and a Macro-AUC of 66.1%. Moreover, BW_att was capable of locating informative tokens from clinical text for predicting the target codes. In summary, BW_att can not only suggest CHD codes accurately, but also possess robust interpretability, hence has great potential in facilitating CHD coding in practice.

Dose-dependent influence of red blood cell transfusion volume on adverse outcomes in cardiac surgery.

INTRODUCTION: Red blood cell (RBC) transfusion is associated with adverse outcomes, but there are few studies on the RBC volume. This study aimed to evaluate the relationship between intraoperative RBC volume and postoperative adverse outcomes for on-pump cardiac surgery. METHODS: Adult patients undergoing on-pump cardiac surgery from 1 January 2017 to 31 December 2018 were included. Those transfused with more than 6 units of RBC were excluded. The clinical characteristics of four groups with various RBC volume were compared. We analyzed the relationship between RBC volume and adverse outcomes through multivariable logistic regression. RESULTS: 12,143 patients were analyzed, of which 3353 (27.6%) were transfused with 1-6U RBC intraoperatively. The incidence of death, overall morbidity, acute kidney injury and prolonged mechanical ventilation were increased stepwise along with incremental RBC volume. After adjusting for possible confounders, patients transfused with 1-2U were associated with a 1.42-fold risk of death (99% CI, 1.21-2.34, p = 0.01) compared with patients without RBC, patients with 3-4U were associated with a 1.57-fold risk (99% CI, 1.32-2.80, p = 0.005) and patients with 5-6U had a 2.26-fold risk of death (99% CI, 1.65-3.88, p < 0.001). Similarly, the incidence of overall morbidity, acute kidney injury and prolonged mechanical ventilation increased several folds as the RBC numbers increased. CONCLUSIONS: There was a significant dose-dependent influence of incremental intraoperative RBC volume on increased risk of adverse outcomes for on-pump cardiac surgery patients. Patient blood management practice should aim to reduce not only transfusion rate but also the volume of blood use.

Establishment and Validation of a Nomogram to Predict Hospital-Acquired Infection in Elderly Patients After Cardiac Surgery.

BACKGROUND: Hospital-acquired infection (HAI) after cardiac surgery is a common clinical concern associated with adverse prognosis and mortality. The objective of this study is to determine the prevalence of HAI and its associated risk factors in elderly patients following cardiac surgery and to build a nomogram as a predictive model. METHODS: We developed and internally validated a predictive model from a retrospective cohort of 6405 patients aged ≥70 years, who were admitted to our hospital and underwent cardiac surgery. The primary outcome was HAI. Multivariable logistic regression analysis was used to identify independent factors significantly associated with HAI. The performance of the established nomogram was assessed by calibration, discrimination, and clinical utility. Internal validation was achieved by bootstrap sampling with 1000 repetitions to reduce the overfit bias. RESULTS: Independent factors derived from the multivariable analysis to predict HAI were smoking, myocardial infarction, cardiopulmonary bypass use, intraoperative erythrocytes transfusion, extended preoperative hospitalization days and prolonged duration of mechanical ventilation postoperatively. The derivation model showed good discrimination, with a C-index of 0.706 [95% confidence interval 0.671-0.740], and good calibration [Hosmer-Lemeshow test P = 0.139]. Internal validation also maintained optimal discrimination and calibration. The decision curve analysis revealed that the nomogram was clinically useful. CONCLUSIONS: We developed a predictive nomogram for postoperative HAIs based on routinely available data. This predictive tool may enable clinicians to achieve better perioperative management for elderly patients undergoing cardiac surgery but still requires further external validation.

Quality Management of a Comprehensive Blood Conservation Program During Cardiopulmonary Bypass.

BACKGROUND: Red blood cell transfusion is common and associated with adverse outcomes for cardiac surgery, while present blood conservation guidelines have not been fully implemented until now. This study evaluated our comprehensive blood conservation program after quality management and explored its impact on blood transfusion and outcomes in patients undergoing cardiopulmonary bypass (CPB). METHODS: We retrospectively compared blood transfusions and outcomes of patients from 2 different periods, before and after initiation of the quality management of the comprehensive blood conservation program. The comprehensive program included restrictive transfusion protocols, conventional ultrafiltration, cell salvage, residual pump blood ultrafiltration, and a modified minimal extracorporeal circulation system. A 1:1 propensity score matching and subgroup analysis were conducted. RESULTS: There were 3977 pairs. A significant decrease of red blood cell transfusion was observed before vs after the comprehensive blood conservation program during CPB (28.4% vs 18.6%, P < .001), in the operation (40.7% vs 34.3%, P < .001), and after the operation (6.2% vs 4.3%, P < .001). Also reduced were 30-day mortality and some major complications. Subgroup analysis showed that the comprehensive blood conservation program was more beneficial for patients aged >60 years, male, and with a medium-risk European System for Cardiac Operative Risk Evaluation (EuroSCORE) of score 3 to 5. CONCLUSIONS: The comprehensive blood conservation program during CPB is safe and effective in adult cardiac operations, reducing blood use, with no adverse outcomes. For patients who are older, male, and have a EuroSCORE of 3 to 5, blood transfusion should be more cautious.

Prediction of acute kidney injury after cardiac surgery from preoperative N-terminal pro-B-type natriuretic peptide.

BACKGROUND: Acute kidney injury (AKI) is common after cardiac surgery and is difficult to predict. N-terminal pro-B-type natriuretic peptide (NT-proBNP) is highly predictive for perioperative cardiovascular complications and may also predict renal injury. We therefore tested the hypothesis that preoperative NT-proBNP concentration is associated with renal injury after major cardiac surgery. METHODS: We included 35 337 patients who had cardiac surgery and measurements of preoperative NT-proBNP and postoperative creatinine. The primary outcome was Kidney Disease: Improving Global Outcomes Stages 1-3 AKI. We also separately considered severe AKI, including Stage 2, Stage 3, and new-onset dialysis. RESULTS: Postoperative AKI occurred in 11 999 (34.0%) patients. Stage 2 AKI occurred in 1200 (3.4%) patients, Stage 3 AKI in 474 (1.3%) patients, and new-onset dialysis was required in 241 (0.7%) patients. The NT-proBNP concentrations (considered continuously or in quartiles) were significantly correlated with any-stage AKI and severe AKI (all adjusted P<0.01). Including NT-proBNP significantly improved AKI prediction (net reclassification improvement: 0.24 [0.22-0.27]; P<0.001) beyond basic models derived from other baseline factors in the overall population. Reclassification was especially improved for higher grades of renal injury: 0.30 (0.25-0.36) for Stage 2, 0.46 (0.37-0.55) for Stage 3, and 0.47 (0.35-0.60) for dialysis. CONCLUSIONS: Increased preoperative NT-proBNP concentrations were associated with postoperative AKI in patients having cardiac surgery. Including NT-proBNP substantially improves AKI predictions based on other preoperative factors.

Automated ICD coding for primary diagnosis via clinically interpretable machine learning.

BACKGROUND: Computer-assisted clinical coding (CAC) based on automated coding algorithms has been expected to improve the International Classification of Disease, tenth version (ICD-10) coding quality and productivity, whereas studies oriented to primary diagnosis auto-coding are limited in the Chinese context. OBJECTIVE: This study aims at developing a machine learning (ML) model for automated primary diagnosis ICD-10 coding. METHODS: A total of 71,709 admissions in Fuwai hospital were included to carry out this study, corresponding to 168 primary diagnosis ICD-10 codes. Based on clinical implications, two feature engineering methods were used to process discharge diagnosis and procedure texts into sequential features and sequential grouping features respectively by which two kinds of models were built and compared. One baseline model using one-hot encoding features was considered. Light Gradient Boosting Machine (LightGBM) was adopted as the classifier, and grid search and cross-validation were used to select the optimal hyperparameters. SHapley Additive exPlanations (SHAP) values were applied to give the interpretability of models. RESULTS: Our best prediction model was developed based on sequential grouping features. It showed good performance in the test phase with accuracy and macro-averaged F1 (Macro-F1) of 95.2% and 88.3% respectively. The comparison of the models demonstrated the effectiveness of the sequential information and the grouping strategy in boosting model performance (P-value < 0.01). Subgroup analysis of the best model on each individual code manifested that 91.1% of the codes achieved the F1 over 70.0%. CONCLUSIONS: Our model has been demonstrated its effectiveness for automated primary diagnosis coding in the Chinese context and its results are interpretable. Hence, it has the potential to assist clinical coders to improve coding efficiency and quality in Chinese inpatient settings.

Using NLP in openEHR archetypes retrieval to promote interoperability: a feasibility study in China.

BACKGROUND: With the development and application of medical information system, semantic interoperability is essential for accurate and advanced health-related computing and electronic health record (EHR) information sharing. The openEHR approach can improve semantic interoperability. One key improvement of openEHR is that it allows for the use of existing archetypes. The crucial problem is how to improve the precision and resolve ambiguity in the archetype retrieval. METHOD: Based on the query expansion technology and Word2Vec model in Nature Language Processing (NLP), we propose to find synonyms as substitutes for original search terms in archetype retrieval. Test sets in different medical professional level are used to verify the feasibility. RESULT: Applying the approach to each original search term (n = 120) in test sets, a total of 69,348 substitutes were constructed. Precision at 5 (P@5) was improved by 0.767, on average. For the best result, the P@5 was up to 0.975. CONCLUSIONS: We introduce a novel approach that using NLP technology and corpus to find synonyms as substitutes for original search terms. Compared to simply mapping the element contained in openEHR to an external dictionary, this approach could greatly improve precision and resolve ambiguity in retrieval tasks. This is helpful to promote the application of openEHR and advance EHR information sharing.

Trends of Coronary Artery Bypass Grafting Performance in a Cohort of Hospitals in China Between 2013 and 2018.

BACKGROUND: China has witnessed a rapid increase in the volume of coronary artery bypass grafting (CABG) but substantial gaps in the performance for CABG across the nation. The present study aimed to investigate the change in CABG performance after years of quality improvement measures in a national registry in China. METHODS: The study included 66 971 patients who underwent isolated CABG in a cohort of 74 tertiary hospitals in China between January 2013 and December 2018. Data were collected from the Chinese Cardiac Surgery Registry. Outcomes were in-hospital mortality and postoperative length of stay. Five process measures for surgical technique and secondary prevention were also analyzed. We described the changes in the overall performance and interhospital heterogeneity across the years. RESULTS: The in-hospital mortality declined from 0.9% in 2013 to 0.6 in 2018, with a risk-adjusted odds ratio of 0.66 (95% CI, 0.46-0.93; P<0.001). The standard mean difference for risk-standardized mortality rate between hospitals in the lowest and highest quartile narrowed from 1.63 in 2013 to 1.35 in 2018. The median (interquartile range) hospital-level rate of using arterial graft increased from 93.9% (86.0%-97.8%) to 94.6% (83.3%-99.2%), but the difference was not statistically significant. Meanwhile, the rate of free from blood transfusion increased from 17.0% (2.6%-32.0%) to 34.1% (8.8%-52.9%). The hospital-level rate of prescribing ß-blockers at discharge significantly increased from 82.8% (66.7%-90.3%) to 91.1% (82.1%-97.1%), statin from 75.8% (55.7%-88.9%) to 88.9% (75.0%-96.0%), and aspirin from 90.3% (83.9%-95.2%) to 95.3% (88.9%-98.1%). CONCLUSIONS: In the Chinese Cardiac Surgery Registry, there were notable improvements in the treatment process related to CABG and decline of in-hospital mortality with reduced interhospital heterogeneity.

Prediction Scores for Any-Stage and Stage-3 Acute Kidney Injury After Adult Cardiac Surgery in a Chinese Population.

OBJECTIVES: This study was performed to internally derive and then validate risk score systems using preoperative and intraoperative variables to predict the occurrence of any-stage (stage 1, 2, 3) and stage-3 acute kidney injury (AKI) within seven days of cardiac surgery. DESIGN: Single-center, retrospective, observational study. SETTING: Single, large, tertiary care center. PARTICIPANTS: Adult patients undergoing open cardiac surgery between January 1, 2012, and January 1, 2019. MEASUREMENTS AND MAIN RESULTS: The clinical data were divided into the following two groups: a derivation cohort (n = 43,799) and a validation cohort (n = 14,600). AKI was defined using the Kidney Disease: Improving Global Outcomes criteria. Multivariate logistic regression analysis was used to develop the prediction models. The overall prevalence of any-stage AKI and stage-3 AKI after cardiac surgery were 34.3% and 1.7%, respectively. The discriminatory ability of the any-stage AKI prediction model measured with the area under the curve (AUC) was acceptable (AUC = 0.69, 95% confidence interval 0.68-0.69), and the calibration measured with the Hosmer-Lemeshow test was good (p = 0.95). The AUC for the stage-3 AKI prediction model was 0.84 (95% confidence interval 0.83-0.85), and the Hosmer-Lemeshow test also indicated a good calibration (p = 0.73). CONCLUSIONS: This research study, which used preoperative and intraoperative variables, derived and internally validated two predictive scoring systems for any-stage AKI and stage-3 AKI as defined by modified Kidney Disease: Improving Global Outcomes criteria using a very large cohort of Chinese cardiac surgical patients.

Prediction of adverse drug reactions based on knowledge graph embedding.

BACKGROUND: Adverse drug reactions (ADRs) are an important concern in the medication process and can pose a substantial economic burden for patients and hospitals. Because of the limitations of clinical trials, it is difficult to identify all possible ADRs of a drug before it is marketed. We developed a new model based on data mining technology to predict potential ADRs based on available drug data. METHOD: Based on the Word2Vec model in Nature Language Processing, we propose a new knowledge graph embedding method that embeds drugs and ADRs into their respective vectors and builds a logistic regression classification model to predict whether a given drug will have ADRs. RESULT: First, a new knowledge graph embedding method was proposed, and comparison with similar studies showed that our model not only had high prediction accuracy but also was simpler in model structure. In our experiments, the AUC of the classification model reached a maximum of 0.87, and the mean AUC was 0.863. CONCLUSION: In this paper, we introduce a new method to embed knowledge graph to vectorize drugs and ADRs, then use a logistic regression classification model to predict whether there is a causal relationship between them. The experiment showed that the use of knowledge graph embedding can effectively encode drugs and ADRs. And the proposed ADRs prediction system is also very effective.

An Application of Machine Learning to Etiological Diagnosis of Secondary Hypertension: Retrospective Study Using Electronic Medical Records.

BACKGROUND: Secondary hypertension is a kind of hypertension with a definite etiology and may be cured. Patients with suspected secondary hypertension can benefit from timely detection and treatment and, conversely, will have a higher risk of morbidity and mortality than those with primary hypertension. OBJECTIVE: The aim of this study was to develop and validate machine learning (ML) prediction models of common etiologies in patients with suspected secondary hypertension. METHODS: The analyzed data set was retrospectively extracted from electronic medical records of patients discharged from Fuwai Hospital between January 1, 2016, and June 30, 2019. A total of 7532 unique patients were included and divided into 2 data sets by time: 6302 patients in 2016-2018 as the training data set for model building and 1230 patients in 2019 as the validation data set for further evaluation. Extreme Gradient Boosting (XGBoost) was adopted to develop 5 models to predict 4 etiologies of secondary hypertension and occurrence of any of them (named as composite outcome), including renovascular hypertension (RVH), primary aldosteronism (PA), thyroid dysfunction, and aortic stenosis. Both univariate logistic analysis and Gini Impurity were used for feature selection. Grid search and 10-fold cross-validation were used to select the optimal hyperparameters for each model. RESULTS: Validation of the composite outcome prediction model showed good performance with an area under the receiver-operating characteristic curve (AUC) of 0.924 in the validation data set, while the 4 prediction models of RVH, PA, thyroid dysfunction, and aortic stenosis achieved AUC of 0.938, 0.965, 0.959, and 0.946, respectively, in the validation data set. A total of 79 clinical indicators were identified in all and finally used in our prediction models. The result of subgroup analysis on the composite outcome prediction model demonstrated high discrimination with AUCs all higher than 0.890 among all age groups of adults. CONCLUSIONS: The ML prediction models in this study showed good performance in detecting 4 etiologies of patients with suspected secondary hypertension; thus, they may potentially facilitate clinical diagnosis decision making of secondary hypertension in an intelligent way.

Open-label, single-centre, cluster-randomised controlled trial to Evaluate the Potential Impact of Computerisedantimicrobial stewardship (EPIC) on the antimicrobial use after cardiovascular surgeries: EPIC trial study original protocol.

INTRODUCTION: Inappropriate antimicrobial use increases the prevalence of antimicrobial-resistant bacteria. Surgeons are reluctant to implement recommendations of guidelines in clinical practice. Antimicrobial stewardship (AMS) is effective in antimicrobial management, but it remains labour intensive. The computerised decision support system (CDSS) has been identified as an effective way to enable key elements of AMS in clinical settings. However, insufficient evidence is available to evaluate the efficacy of computerised AMS in surgical settings. METHODS AND ANALYSIS: The Evaluate of the Potential Impact of Computerised AMS trial is an open-label, single-centre, two-arm, cluster-randomised, controlled trial, which aims to determine whether a multicomponent CDSS intervention reduces overall antimicrobial use after cardiovascular surgeries compared with usual clinical care in a specialty hospital with a big volume of cardiovascular surgeries. Eighteen cardiovascular surgical teams will be randomised 1:1 to either the intervention or the control arm. The intervention will consist of (1) re-evaluation alerts and decision support for the duration of antimicrobial treatment decision, (2) re-evaluation alerts and decision support for the choice of antimicrobial, (3) quality control audit and feedback. The primary outcome will be the overall systemic antimicrobial use measured in days of therapy (DOT) per admission and DOT per 1000 patient-days over the whole intervention period (6 months). Secondary outcomes include a series of indices to evaluate antimicrobial use, microbial resistance, perioperative infection outcomes, patient safety, resource consumption, and user compliance and satisfaction. ETHICS AND DISSEMINATION: The Ethics Committee in Fuwai Hospital approved this study (2020-1329). The results of the trial will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT04328090.