Risk Patients Research Articles

A RARE COMPLICATION OF MITRAL TEER PROCEDURE: CLIP LATE DETACHMENT AND EMBOLIZATION

Abstract Intraprocedural and late complications of MitraClip implantation have already been described. This report highlights the importance of conventional surgical options in the event of percutaneous treatment failure. An 85–year–old woman with a history of chronic anemia, and thalassemia Minor was referred to our clinic for severe mitral regurgitation (MR) due to a P2 flail with significant calcification of the posterior mitral annulus. During the Heart Team discussion, age and comorbidities led to consider the patient eligible for TEER with the MitraClip system (EuroSCORE II 9,34%; STS score 7,47%). TEER procedure was uneventful: one XTW was deployed at the level of the flail (A2–P2), a second XTW was then placed more lateral to treat a separate residual jet, and one NTW was finally placed between them. MR reduction was considered acceptable (moderate MR, mean grad 6 mmHg). After two months, symptoms worsened, and TTE showed severe MR (no device detachment) with increased sPAP and associated moderate TR. A couple of weeks later, the patient was hospitalized. Chest X–ray revealed clip embolization confirmed by coronary angiography that showed an XTW Clip embolized to the Right coronary sinus with partial occlusion of the ostium. Percutaneous clip retrieval is described in the literature, but the embolized device position and the presence of recurrent severe MR led us to prefer an urgent surgical intervention. Under CPB, the embolized XTW was easily retrieved through a small aortotomy; the intervention was completed by mitral valve replacement and tricuspid valve repair. The postoperative course was uneventful. Predischarge TTE showed normal mitral bioprosthesis function, mild AR, mild TR, and preserved LV function. DISCUSSION Clip embolization is a rare but potentially critical complication of TEER and can happen periprocedurally or on early follow–up. Single leaflet detachment is more common, but complete detachment and embolization can occur. Therapeutic options are represented by surgical or transcatheter approaches according to embolization sites and patient comorbidities. In our case, the risk of potential coronary obstruction or thrombosis and the concomitant need for MR treatment have led us to consider surgery as the first option. CONCLUSION TEER can be graved by acute or late complications. The best approach has to be tailored to each patient, and surgery can be an effective and safe option even for initially discarded high–risk patients.

SEVERE SYMPTOMATIC MITRAL REGURGITATION AFTER ANNULOPLASTY FAILURE: SUCCESSFUL TRANSCATHETER EDGE TO EDGE REPAIR

Abstract Surgical mitral valve repair is the most common, feasible and preferred procedure to treat primary and secondary mitral regurgitation (MR). However, 30% of patients suffer from residue severe regurgitation 10 years after surgical intervention, resulting in a considerable number of Redo procedures. In elderly and high–risk patients with major comorbidities medical treatment is the only and often insufficient option for symptoms’ relief. Percutaneous Transcatheter Edge to Edge repair technique (TEER) with MitraClip system is emerging as an off–label valid alternative to successfully treat severe mitral regurgitation after surgical valvuloplasty failure. Transesophageal echocardiography (TEE) is essential in diagnosis, planning, intraprocedural device placement, and follow up. In the peculiar setting of failed annuloplasty, with small residual valve area, the main risk is the creation of a gradient across the mitral valve. We present two cases of severe mitral regurgitation after surgical annuloplasty with ring placement, carefully evaluated for TEER and successfully treated with this procedure: 1) a 79–year–old man presented with exertional dyspnea and orthopnea in the setting of previous surgical mitral Annuloplasty (2003) with a 32–mm Carpentier Ring. Transesophageal echocardiography demonstrated severe mitral regurgitation due to P2 prolapse and central V–shaped cut of the valve, mean diastolic gradient 1.8 mmHg. 2) a 83 year–old woman presented with dyspnea (NYHA functional class III) and severe mitral regurgitation after previous Annuloplasty with a 34–mm Edwards Ring and placement of Goretex artificial Chordae (2016). TEE showed prolapse of P2 and P3 leaflets, mean diastolic gradient 2.17 mmHg, valvular area 3.5 cmq. Both patients underwent transfemoral and transseptal implantation of one MitraClip device (XTw and XT, respectively) under Transesophageal echocardiography guidance with successful reduction of mitral regurgitation to mild level and symptoms relief. In the first case post procedural mean diastolic gradient was 3.7 mmHg, in the second case it was 3.16 mmHg.

THE “BACK TO THE FUTURE” OF CARDIOTHORACIC SURGERY: HIGH–RISK INTERVENTIONAL PROCEDURE TURNED DOWN TO CONVENTIONAL CARDIAC SURGERY

Abstract Background Structural interventional cardiology has been introduced at the beginning of our century to address high–risk patient suffering from severe aortic stenosis. Since then several technique and technology have been proposed to address an increasing population of patients and mitral valve diseases have been also addressed. While several authors are pushing up the indications for structural interventional procedures, however, we are experiencing some situations were conventional surgery is considered an alternative to high risk interventional procedures. Here we present a peculiar case of “back to the future” in cardiothoracic surgery. Case Description A 76 yo female patient, was referred to our Division from a peripheral Hospital suffering from severe aortic stenosis and coronary artery diseases. Medical history of the patient included persistent AF, COPD, arterial peripheral vascular disease, moderate chronic renal insufficiency and moderate dilatation of ascending aorta. Patient was previously assessed by another Centre and a percutaneous treatment (PTCA+TAVI) was proposed. Due to further admission for cardiac failure–related symptoms, however, patient was urgently referred to our Division. Fig 1 and 2 summarized clinical findings. “Heart team” evaluation, based also on the product specialist evaluation, considered the patient not suitable for interventional procedure due to the high risk of sub–optimal medium–term prognosis. Due to further clinical deterioration an extremely high–risk surgical procedure was mandatory. Results Surgical procedure included a sutureless aortic valve replacement, a MV plasty, a double coronary graft + a cpmbined carotid endoarterectomy. Postoperative course was free from significant complications and the patient was discharged to rehabilitation clinic on 15th postoperative days. Conclusion Despite interventional procedure are continuing to increase either as number of procedure either as complexity of diseases treated, conventional cardiac surgery remains still the only option for treatment in many clinical scenario. As a sort of “back to the future” situation, patient originally referred for interventional procedures are turned down due to the high risk of sub–optimal results. In such condition conventional cardiac surgery, performed with high level of accuracy could represent the last and only treatment option for high risk patients.

CCT‘S CRYSTAL BALL: PREDICTING CARDIOVASCULAR RISK IN AORTIC VALVE STENOSIS PATIENTS UNDERGOING VALVE REPLACEMENT

Abstract Background and Aims Currently, computed tomography cardiac imaging (CTCI) plays a fundamental role in the pre–procedural planning of degenerative–calcific aortic valve stenosis(AS) correction. However, its prognostic role in assessing mortality and major adverse cardiovascular events (MACE) has not been extensively explored. CTCI allows for the evaluation of coronary artery calcification(CAC), mitral annular calcifications (MAC), aortic valve calcifications (CVA), and thoracic aorta calcifications (CAT). The aim of our study was to assess whether the presence and extent of CAC, MAC, CVA, and CAT could influence non–cardiovascular mortality (NCM), cardiovascular mortality (CM), and MACE in patients undergoing valve replacement(VR). Materials and Methods We collected retrospectivelly clinical and instrumental data and reviewed CTCI using a semi–quantitative approach. CACs were classified according to the visual 2022 Coronary Artery Disease–Reporting and Data System. MACs were defined following the Guerrero et al. study, CVAs according to the Win Registry and CATs were assessed in the ascending aorta, aortic arch, and descending aorta according to the Vos classification. Results 244 patients(59% male, mean age 80.1±6.6 years), with 91% undergoing transfemoral VR, were enrolled(2016–2018). CM was significantly higher in patients with hypertension,cerebro/peripheral vascular disease, stage IV–V renal insufficiency and history of atrial fibrillation (p=0.012,p<0.001,p=0.005, p=0.034 and p=0.024, respectively). CM was also more pronounced in patients with STS SCORE≥6.7±5.2 and EuroSCOREII≥ 5.5±5.8(p=0.016 and p=0.037). Extensive CAC(p=0.019), a MAC score>7(p=0.051), moderate and severe AVC (p=0.029 and p=0.053) and TAC>270° in aortic arch(p=0.019) were linked to CM. In multivariate analysis, a high MAC score and the presence of moderate AVC persisted as risk factors for CM. The presence of a MAC score >7(p=0.006) and the extension of descending TAC >1.5 mm (p=0.034) were associated with an increased risk of NCM.The presence of extensive TAC (≥270°) measured in the aortic arch and descending aorta were associated with MACE (p=0.034 and p=0.0504 respectively). Conclusions CTCI emerges as a crucial tool for evaluating prognostic risk in patients undergoing VR for AS. This type of evaluation can assist clinicians in pre–procedural planning and patient management, allowing for better identification of high–risk patients and optimization of therapeutic strategies

Identifying and Validating an Angiogenesis-related Signature for the Prognosis of Head and Neck Squamous Cell Carcinoma.

The present study aimed todevelop a prognostic model for HNSCC treatment on the basis of angiogenesis-related signatures. Head and Neck Squamous Cell Carcinoma (HNSCC) is the most frequent malignancy with poor prognostic outcomes in the head and neck. Angiogenesis plays a critical role in tumorigenesis and is expected to be an effective therapeutic target. The RNA-seq dataset TCGA-HNSCC and the hallmark gene set were used for angiogenesis-related RiskScore model construction. The RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA), and the hallmark gene set was used to measure the angiogenesis score using the GSVA R package. Then, the optimal cutoff point for prognostic classification was calculated by the survminer package, and Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify angiogenesis gene modules . Multi/univariable and Lasso Cox analyses were performed to develop the RiskScore model, and the classifier efficiency was evaluated by the Receiver Operating Characteristic curve (ROC). Furthermore, a nomogram was designed for survival probability prediction, and the immune infiltration and immunotherapy differences among different risk patients were assessed. After calculating the angiogenesis score, we found that this indicator and patients' prognosis were closely correlated, especially when patients with a high angiogenesis score had a poor prognosis. Then, WGCNA identified a blue gene module positively correlated with angiogenesis. Multivariate and Lasso Cox analysis further identified 9 risk model genes for developing a RiskScore, which was used to divide low- and high- -risk groups of patients. Those with a high risk tended to show poor prognosis, immune infiltration, and higher immune escape. Finally, a nomogram was developed to optimize the risk model, and it exhibited excellent short- and long-term survival prediction performance. We constructed a reliable RiskScore model for the prognostic prediction of HNSCC patients, contributing to precise therapeutic intervention of the cancer.

Predictive biomarkers in lymphoma: a systematic research review

Lymphoma is a diverse group of blood cancers originating in the lymphatic system, with varying clinical presentations and prognoses. Identifying and utilizing predictive biomarkers in lymphoma can significantly impact the management and outcome of patients. For instance, the presence of the BCL2 gene rearrangement in follicular lymphoma is associated with a poorer prognosis, while the expression of the CD20 protein in diffuse large B-cell lymphoma is a predictor of response to rituximab. These biomarkers are molecular or cellular indicators that can help forecast disease progression, therapeutic response, and patient prognosis. This abstract provides an overview of the current landscape of predictive biomarkers in lymphoma, focusing on their role which can help physicians to build personalized treatment strategies. We explore key types of biomarkers, including genetic mutations, protein expressions, and cellular markers, that have shown potential in predicting treatment response and survival outcomes across different lymphoma subtypes. Furthermore, we delve into recent advancements in biomarker discovery through high-throughput technologies such as next-generation sequencing and their strategic integration into clinical practice. The use of predictive biomarkers not only enhances the precision of treatment regimens but also contributes to better risk stratification and patient monitoring. The future of this field involves the refinement of biomarker panels for improved predictive accuracy and the exploration of novel targets for therapy. The strategic application of predictive biomarkers in lymphoma presents promising opportunities for optimizing patient care and advancing precision medicine in hematological malignancies.

Development, content validation and standardization of an adult patient prioritization tool for hospital clinical pharmacy services

BackgroundPatient prioritization is a effective strategy to identify high risk patients for targeted Clinical Pharmacy Service (CPS) in hospital pharmacy. However, there is a paucity of patient prioritization tool to use in clinical practice. ObjectivesDescribe the development, content validation and standardization of an adult patient prioritization tool for hospital CPS named, PrioFarClinH. MethodsThe tool was developed using a stepwise design multi: Scoping Review to identify prioritization criteria/sub-criteria; Delphi technique to obtain consensus under the identified criteria/sub-criteria; Survey with pharmacists evaluating applicability of the criteria/sub-criteria obtained from Delphi; Definition of criteria/sub-criteria to be included in PrioFarClinH attribution of scores. Content validation was performed by a panel of experts evaluating relevance, feasibility, clarity and adequacy of the score. Content Validity Index (CVI) was calculated. Standardization occurred through a retrospective observational study carried out at 24 and 72 h and median of the patient's hospital stay. An intragroup norm was performed, determining percentile ranks of the instrument's total scores. Patients with a P90 score were classified with a high level of prioritization for CPS. ResultsPrioFarClinH is divided into three sections, with prioritization criteria for health issues; therapeutic classes; laboratory parameters. It comprises 51 criteria with specific scores with simple total calculation. None of the criteria presented CVI <0.78, maintaining the items from the initial version of PrioFarClinH. The scores were adjusted per suggestions from the panel of judges. Data were collected from 393 patients. The P90 percentile in the three hospitalization stages (24 h, 72 h, and median) was found, respectively, in the following scores: 18.0, 20.0, and 22.6. ConclusionsPrioFarClinH is a comprehensive tool to target and to prioritize adults patients most likely to benefit from CPS. Evidence for adequate content validity was provided. However, further validation of this tool is necessary to establish tool performance.

Clinical evaluation of a machine learning-based dysphagia risk prediction tool

PurposeThe rise of digitization promotes the development of screening and decision support tools. We sought to validate the results from a machine learning based dysphagia risk prediction tool with clinical evaluation.Methods149 inpatients in the ENT department were evaluated in real time by the risk prediction tool, as well as clinically over a 3-week period. Patients were classified by both as patients at risk/no risk.ResultsThe AUROC, reflecting the discrimination capability of the algorithm, was 0.97. The accuracy achieved 92.6% given an excellent specificity as well as sensitivity of 98% and 82.4% resp. Higher age, as well as male sex and the diagnosis of oropharyngeal malignancies were found more often in patients at risk of dysphagia.ConclusionThe proposed dysphagia risk prediction tool proved to have an outstanding performance in discriminating risk from no risk patients in a prospective clinical setting. It is likely to be particularly useful in settings where there is a lower incidence of patients with dysphagia and less awareness among staff.

Machine Learning Approach to Metabolomic Data Predicts Type 2 Diabetes Mellitus Incidence.

Metabolomics, with its wealth of data, offers a valuable avenue for enhancing predictions and decision-making in diabetes. This observational study aimed to leverage machine learning (ML) algorithms to predict the 4-year risk of developing type 2 diabetes mellitus (T2DM) using targeted quantitative metabolomics data. A cohort of 279 cardiovascular risk patients who underwent coronary angiography and who were initially free of T2DM according to American Diabetes Association (ADA) criteria was analyzed at baseline, including anthropometric data and targeted metabolomics, using liquid chromatography (LC)-mass spectroscopy (MS) and flow injection analysis (FIA)-MS, respectively. All patients were followed for four years. During this time, 11.5% of the patients developed T2DM. After data preprocessing, 362 variables were used for ML, employing the Caret package in R. The dataset was divided into training and test sets (75:25 ratio) and we used an oversampling approach to address the classifier imbalance of T2DM incidence. After an additional recursive feature elimination step, identifying a set of 77 variables that were the most valuable for model generation, a Support Vector Machine (SVM) model with a linear kernel demonstrated the most promising predictive capabilities, exhibiting an F1 score of 50%, a specificity of 93%, and balanced and unbalanced accuracies of 72% and 88%, respectively. The top-ranked features were bile acids, ceramides, amino acids, and hexoses, whereas anthropometric features such as age, sex, waist circumference, or body mass index had no contribution. In conclusion, ML analysis of metabolomics data is a promising tool for identifying individuals at risk of developing T2DM and opens avenues for personalized and early intervention strategies.

The feasibility, acceptability and appropriateness of screening for frailty in Australians aged 75 years and over attending Australian general practice

Background Globally, frailty is associated with a high prevalence of avoidable hospital admissions and emergency department visits, with substantial associated healthcare and personal costs. International guidelines recommend incorporation of frailty identification and care planning into routine primary care workflow to support patients who may be identified as pre-frail/frail. Our study aimed to: (1) determine the feasibility, acceptability, appropriateness and determinants of implementing a validated FRAIL Scale screening Tool into general practices in two disparate Australian regions (Sydney North and Brisbane South); and (2) map the resources and referral options required to support frailty management and potential reversal. Methods Using the FRAIL Scale Tool, practices screened eligible patients (aged ≥75 years) for risk of frailty and referred to associated management options. The percentage of patients identified as frail/pre-frail, and management options and referrals made by practice staff for those identified as frail/pre-frail were recorded. Semi-structured qualitative interviews were conducted with practice staff to understand the feasibility, acceptability, appropriateness and determinants of implementing the Tool. Results The Tool was implemented by 19 general practices in two Primary Health Networks and 1071 consenting patients were assessed. Overall, 80% of patients (n = 860) met the criterion for frailty: 33% of patients (n = 352) were frail, and 47% were pre-frail (n = 508). They were predominantly then referred for exercise prescription, medication reviews and geriatric assessment. The Tool was acceptable to staff and patients and compatible with practice workflows. Conclusions This study demonstrates that frailty is identified frequently in Australians aged ≥75 years who visit their general practice. It’s identification, linked with management support to reverse or reduce frailty risk, can be readily incorporated into the Medicare-funded annual 75+ Health Assessment.

Development and validation of a new drug-focused predictive risk score for postoperative delirium in orthopaedic and trauma surgery patients

BackgroundPostoperative delirium (POD) is the most common complication following surgery in elderly patients. During pharmacist-led medication reconciliation (PhMR), a predictive risk score considering delirium risk-increasing drugs and other available risk factors could help to identify risk patients.MethodsOrthopaedic and trauma surgery patients aged ≥ 18 years with PhMR were included in a retrospective observational single-centre study 03/2022-10/2022. The study cohort was randomly split into a development and a validation cohort (6:4 ratio). POD was assessed through the 4 A’s test (4AT), delirium diagnosis, and chart review. Potential risk factors available at PhMR were tested via univariable analysis. Significant variables were added to a multivariable logistic regression model. Based on the regression coefficients, a risk score for POD including delirium risk-increasing drugs (DRD score) was established.ResultsPOD occurred in 42/328 (12.8%) and 30/218 (13.8%) patients in the development and validation cohorts, respectively. Of the seven evaluated risk factors, four were ultimately tested in a multivariable logistic regression model. The final DRD score included age (66–75 years, 2 points; > 75 years, 3 points), renal impairment (eGFR < 60 ml/min/1.73m2, 1 point), anticholinergic burden (ACB-score ≥ 3, 1 point), and delirium risk-increasing drugs (n ≥ 2; 2 points). Patients with ≥ 4 points were classified as having a high risk for POD. The areas under the receiver operating characteristic curve of the risk score model were 0.89 and 0.81 for the development and the validation cohorts, respectively.ConclusionThe DRD score is a predictive risk score assessable during PhMR and can identify patients at risk for POD. Specific preventive measures concerning drug therapy safety and non-pharmacological actions should be implemented for identified risk patients.

Implications of Five Different Risk Models In Primary Prevention Guidelines.

A lack of consensus exists across guidelines as to which risk model should be used for the primary prevention of cardiovascular disease (CVD). Our objective was to determine potential improvements in the number needed to treat (NNT) and number of events prevented (NEP) using different risk models in patients eligible for risk stratification. A retrospective observational cohort was assembled from primary care patients in Ontario, Canada between January 1st, 2010, to December 31st, 2014 and followed for up to 5 years. Risk estimation was undertaken in patients 40-75 years of age, without CVD, diabetes, or chronic kidney disease using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCEs), a recalibrated FRS (R-FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and the low-risk region recalibrated SCORE2 (LR-SCORE2). The cohort consisted of 47,399 patients (59% women, mean age 54). The NNT with statins was lowest for SCORE2 at 40, followed by LR-SCORE2 at 41, R-FRS at 43, PCEs at 55, and FRS at 65. Models that selected for individuals with a lower NNT recommended statins to fewer, but higher risk patients. For instance, SCORE2 recommended statins to 7.9% of patients (5-year CVD incidence 5.92%). The FRS, however, recommended statins to 34.6% of patients (5-year CVD incidence 4.01%). Accordingly, the NEP was highest for the FRS at 406 and lowest for SCORE2 at 156. Newer models such as SCORE2 may improve statin allocation to higher risk groups with a lower NNT but prevent fewer events at the population level.

Lysosome-related genes predict acute myeloid leukemia prognosis and response to immunotherapy.

Acute myeloid leukemia (AML) is a highly aggressive and pathogenic hematologic malignancy with consistently high mortality. Lysosomes are organelles involved in cell growth and metabolism that fuse to form specialized Auer rods in AML, and their role in AML has not been elucidated. This study aimed to identify AML subtypes centered on lysosome-related genes and to construct a prognostic model to guide individualized treatment of AML. Gene expression data and clinical data from AML patients were downloaded from two high-throughput sequencing platforms. The 191 lysosomal signature genes were obtained from the database MsigDB. Lysosomal clusters were identified by unsupervised consensus clustering. The differences in molecular expression, biological processes, and the immune microenvironment among lysosomal clusters were subsequently analyzed. Based on the molecular expression differences between lysosomal clusters, lysosomal-related genes affecting AML prognosis were screened by univariate cox regression and multivariate cox regression analyses. Algorithms for LASSO regression analyses were employed to construct prognostic models. The risk factor distribution, KM survival curve, was applied to evaluate the survival distribution of the model. Time-dependent ROC curves, nomograms and calibration curves were used to evaluate the predictive performance of the prognostic models. TIDE scores and drug sensitivity analyses were used to explore the implication of the model for AML treatment. Our study identified two lysosomal clusters, cluster1 has longer survival time and stronger immune infiltration compared to cluster2. The differences in biological processes between the two lysosomal clusters are mainly manifested in the lysosomes, vesicles, immune cell function, and apoptosis. The prognostic model consisting of six prognosis-related genes was constructed. The prognostic model showed good predictive performance in all three data sets. Patients in the low-risk group survived significantly longer than those in the high-risk group and had higher immune infiltration and stronger response to immunotherapy. Patients in the high-risk group showed greater sensitivity to cytarabine, imatinib, and bortezomib, but lower sensitivity to ATRA compared to low -risk patients. Our prognostic model based on lysosome-related genes can effectively predict the prognosis of AML patients and provide reference evidence for individualized immunotherapy and pharmacological chemotherapy for AML.

Noninvasive Atherosclerotic Phenotyping: The Next Frontier into Understanding the Pathobiology of Coronary Artery Disease.

Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease. Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation.

Nomogram built based on machine learning to predict recurrence in early-stage hepatocellular carcinoma patients treated with ablation.

To analyze the risk factors affecting recurrence in early-stage hepatocellular carcinoma (HCC) patients treated with ablation and then establish a nomogram to provide a clear and accessible representation of the patients' recurrence risk. Collect demographic and clinical data of 898 early-stage HCC patients who underwent ablation treatment at Beijing You'an Hospital, affiliated with Capital Medical University from January 2014 to December 2022. Patients admitted from 2014 to 2018 were included in the training cohort, while 2019 to 2022 were in the validation cohort. Lasso and Cox regression was used to screen independent risk factors for HCC patients recurrence, and a nomogram was then constructed based on the screened factors. Age, gender, Barcelona Clinic Liver Cancer (BCLC) stage, tumor size, globulin (Glob) and γ-glutamyl transpeptidase (γ-GT) were finally incorporated in the nomogram for predicting the recurrence-free survival (RFS) of patients. We further confirmed that the nomogram has optimal discrimination, consistency and clinical utility by the C-index, Receiver Operating Characteristic Curve (ROC), calibration curve and Decision Curve Analysis (DCA). Moreover, we divided the patients into different risk groups and found that the nomogram can effectively identify the high recurrence risk patients by the Kaplan-Meier curves. This study developed a nomogram using Lasso-Cox regression to predict RFS in early-stage HCC patients following ablation, aiding clinicians in identifying high-risk groups for personalized follow-up treatments.

Early outcome in patients with STEMI undergoing primary PCI and high Zwolle risk score discharged within 72 hours

Abstract Funding Acknowledgements None. Introduction Zwolle risk score has been used to guide decision for early discharge in patients with ST- elevation acute myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PCI). There is limited evidence on the outcome of patients with high score discharged within 72 hours from primary PCI. Our study aim is to evaluate the outcomes via 1 - month follow up in patients with STEMI undergoing primary PCI, with different Zwolle risk who were discharged within 72 hours from the hospital. Purpose To evaluate 1-month outcome of STEMI patients treated with primary PCI discharged within 72 hours according to Zwolle risk score. Methods We studied 187 consecutive STEMI patients from April 2022 to December 2022, presented in hospital within 12 hours of initial of chest pain, treated with primary PCI and discharged within 72 hours from hospital admission based on physician’s clinical judgement and patient’s preference. Patients were divided in two groups according to Zwolle risk score – low risk (≤3) and high risk (&amp;gt;3). The composite of major adverse events (MACE) consisting of: death, non-fatal re-infarction, stroke and repeat intervention at 1-month follow up was the primary endpoint. Follow up rate was 100%. Results There were 131 patients in the low risk and 56 in high risk groups. Males were 90% versus 80.3% in the low vs high risk group; in addition, mean age was 58.64 ± 10.6 vs 67.8± 6.24 years, respectively; mean ischemic time was 4.78± 3.03 vs 6.9 ± 3.6 hours, respectively; anterior localization was present in 32.8% vs 46.4% of the patients, respectively; 3-vessel coronary artery disease was present in 29.0% vs 46.4% of the patients, respectively; final TIMI 3 flow was present in all vs 96.4% of the patients, respectively. MACE occurred in 7 patients (3.8%) in the low risk group versus 3 patients (5.3%) in the high risk group (P = 0.63). Conclusions In our study population at higher Zwolle risk score was not associated with a worse early outcome among STEMI patients discharged within 72 hours.

Risk factors and early prediction of cardiorenal syndrome type 3 among acute kidney injury patients: a cohort study

Background Type 3 cardiorenal syndrome (CRS type 3) triggers acute cardiac injury from acute kidney injury (AKI), raising mortality in AKI patients. We aimed to identify risk factors for CRS type 3 and develop a predictive nomogram. Methods In this retrospective study, 805 AKI patients admitted at the Department of Nephrology, Second Hospital of Shanxi Medical University from 1 January 2017, to 31 December 2021, were categorized into a study cohort (406 patients from 2017.1.1-2021.6.30, with 63 CRS type 3 cases) and a validation cohort (126 patients from 1 July 2021 to 31 Dec 2021, with 22 CRS type 3 cases). Risk factors for CRS type 3, identified by logistic regression, informed the construction of a predictive nomogram. Its performance and accuracy were evaluated by the area under the curve (AUC), calibration curve and decision curve analysis, with further validation through a validation cohort. Results The nomogram included 6 risk factors: age (OR = 1.03; 95%CI = 1.009–1.052; p = 0.006), cardiovascular disease (CVD) history (OR = 2.802; 95%CI = 1.193–6.582; p = 0.018), mean artery pressure (MAP) (OR = 1.033; 95%CI = 1.012–1.054; p = 0.002), hemoglobin (OR = 0.973; 95%CI = 0.96-–0.987; p < 0.001), homocysteine (OR = 1.05; 95%CI = 1.03–1.069; p < 0.001), AKI stage [(stage 1: reference), (stage 2: OR = 5.427; 95%CI = 1.781–16.534; p = 0.003), (stage 3: OR = 5.554; 95%CI = 2.234–13.805; p < 0.001)]. The nomogram exhibited excellent predictive performance with an AUC of 0.907 in the study cohort and 0.892 in the validation cohort. Calibration and decision curve analyses upheld its accuracy and clinical utility. Conclusions We developed a nomogram predicting CRS type 3 in AKI patients, incorporating 6 risk factors: age, CVD history, MAP, hemoglobin, homocysteine, and AKI stage, enhancing early risk identification and patient management.

The Brain Injury Guidelines (BIG) and emergency department observation and admission rates: A retrospective cohort study

BackgroundEmergency Department (ED) Observation Units (OU) can provide safe, effective care for low risk patients with intracranial hemorrhages. We compared current ED OU use for patients with subdural hematomas (SDH) to the validated Brain Injury Guidelines (BIG) to evaluate the potential impact of implementing this risk stratification tool. MethodsRetrospective cohort of patients ≥18 years old with SDH of any cause from 2014 to 2020 to evaluate for potential missed OU cases. Missed OU cases were defined as patients with an initial Glasgow Coma Score (GCS) of 15 with hospital length of stays (LOS) <2 days, who did not meet the composite outcome and were not cared for in the OU or discharged from the ED. Composite outcome included in-hospital death or transition to hospice care, neurosurgical intervention, GCS decline, and worsening SDH size. Secondary outcomes were whether application of BIG would increase ED OU use or reduce CT use. Results264 patients met inclusion criteria over 5.3 year study timeframe. Mean age was 61 years (range 19–93) and 61.4% were male. SDH were traumatic in 76.9% and 60.2% of the cohort had additional injuries. The admission rate was 81.4% (n = 215). Fourteen (6.5%) missed OU cases were identified (2.6/year). Retrospective application of BIG resulted in 82.6% (n = 217) at BIG 3, 10.2% (n = 27) at BIG 2 and 7.6% (n = 20) at BIG 1. Application of BIG would not have decreased admission rates (82.6% BIG 3) and BIG 1 and 2 admissions were often for medical co-morbidities. The composite outcome was met in 50% of BIG 3, 22% of BIG 2, and no BIG 1 patients. ConclusionIn a level 1 trauma center with an established observation unit, current clinical care processes missed very few patients who could be discharged or placed in ED OU for SDH. Hospital admissions in BIG 1/2 were driven by co-morbidities and/or injuries, limiting applicability of BIG to this population.

STEMI antiplatelet pretreatment strategy - national multicenter registry experience

Abstract Funding Acknowledgements None. Background/Introduction Antiplatelet therapy is the cornerstone treatment for ST-segment elevation myocardial infarction (STEMI). Dual antiplatelet therapy (DAPT) including aspirin and a potent P2Y12 inhibitor (P2Y12i) is recommended as the default strategy. However, the timing of DAPT remains controversial: European Cardiology Society (ESC) guidelines ceased recommending pretreatment with P2Y12i in STEMI, based on ATLANTIC trial results. Purpose This study aims to evaluate the effect of DAPT with potent P2Y12i pretreatment DAPT in STEMI patients, comparing with DAPT with clopidogrel and aspirin only pretreatment. Methods We have analyzed the antiplatelet pretreatment strategy results of a retrospective cohort of 2283 STEMI patients, from a multicenter national registry, from 2011 till 2019. We compared 3 groups: DAPT with potent P2Y12i, DAPT with clopidogrel and aspirin only. Primary endpoints were death, major adverse cardiovascular events (MACE), including reinfarction, heart failure, sustained ventricular arrhythmia, cardiogenic shock, mechanical complication and stroke, and successful PCI. Safety endpoint was major hemorrhagic events between different strategies. Results A total of 2283 STEMI patients where included, with a mean age of 66±13 years and 27% (n=627) were female. The population was divided in 3 groups, according with pretreatment strategy: DAPT with potent P2Y12i, DAPT with clopidogrel and aspirin only. 334 patients undergone DAPT with potent P2Y12i, and 86% (n=296) had a successful PCI, 21% (n=69) had a MACE and 9% (n=31) died in hospital. The group of patients submitted to DAPT with clopidogrel were 1815, and 80% (n=1448) had a successful PCI, 29% (n=527) had a MACE and 11,5% (n=209). The group pretreated only with aspirin were 124 patients, of which, only 14% (n=17) had a successful PCI, 38% (n=47) had a MACE and 39% (n=49) died. Regarding safety outcomes, 1,5% (n=5) patients with DAPT with potent P2Y12i had a significant hemorrhage, comparing with 3% (n=53) of patients with DAPT with clopidogrel and 3% (n=4) of aspirin only group of patients. There was a statistically significant higher rate of successful PCI with DAPT with potent P2Y12i (p&amp;lt;0,05 OR 2), a statistically significant lower number of MACE (p&amp;lt;0,05 OR 0,6) and in hospital deaths (p=0,04 OR 0,67), comparing with DAPT with clopidogrel and aspirin only groups. There was no statistically significant difference between groups in terms of hemorrhagic events (p=0,7). According to our retrospective multicenter national registry, pretreatment with potent P2Y12i is associated with better results, namely higher rate of successful PCI, less MACE and in hospital death, contrary to recent trials. Our study has some bias: the pretreatment with DAPT was standard of care during the registry, and the choice for aspirin only strategy might be due to higher risk patients, as the choice was not randomized.Antiplatelet treatment comparison

Colorectal cancer health and care quality indicators in a federated setting using the Personal Health Train

ObjectiveHospitals and healthcare providers should assess and compare the quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, which in return provide annual quality indicators. However, this process is time-consuming, resource intensive and risks patient privacy and confidentiality. In this paper, we presented a multicentric ‘Proof of Principle’ study for federated calculation of quality indicators in patients with colorectal cancer. The findings suggest that the proposed approach is highly time-efficient and consume significantly lesser resources.Materials and methodsTwo quality indicators are calculated in an efficient and privacy presevering federated manner, by i) applying the Findable Accessible Interoperable and Reusable (FAIR) data principles and ii) using the Personal Health Train (PHT) infrastructure. Instead of sharing data to a centralized registry, PHT enables analysis by sending algorithms and sharing only insights from the data.ResultsETL process extracted data from the Electronic Health Record systems of the hospitals, converted them to FAIR data and hosted in RDF endpoints within each hospital. Finally, quality indicators from each center are calculated using PHT and the mean result along with the individual results plotted.Discussion and conclusionPHT and FAIR data principles can efficiently calculate quality indicators in a privacy-preserving federated approach and the work can be scaled up both nationally and internationally. Despite this, application of the methodology was largely hampered by ELSI issues. However, the lessons learned from this study can provide other hospitals and researchers to adapt to the process easily and take effective measures in building quality of care infrastructures.