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Introduction Fractional flow reserve (FFR) measured after percutaneous coronary intervention (PCI) has been identified as a surrogate marker for vessel related adverse events. FFR can be derived from standard coronary computed tomography angiography (CTA). Moreover, the FFR derived from coronary CTA (FFRCT) Planner is a tool that simulates PCI providing modeled FFRCT values after stenosis opening. Aim To validate the accuracy of the FFRCT Planner in predicting FFR after PCI with invasive FFR as a reference standard. Methods Prospective, international and multicenter study of patients with chronic coronary syndromes undergoing PCI. Patients will undergo coronary CTA with FFRCT prior to PCI. Combined morphological and functional evaluations with motorized FFR hyperemic pullbacks, and optical coherence tomography (OCT) will be performed before and after PCI. The FFRCT Planner will be applied by an independent core laboratory blinded to invasive data, replicating the invasive procedure. The primary objective is to assess the agreement between the predicted FFRCT post‐PCI derived from the Planner and invasive FFR. A total of 127 patients will be included in the study. Results Patient enrollment started in February 2019. Until December 2020, 100 patients have been included. Mean age was 64.1 ± 9.03, 76% were males and 24% diabetics. The target vessels for PCI were LAD 83%, LCX 6%, and RCA 11%. The final results are expected in 2021. Conclusion This study will determine the accuracy and precision of the FFRCT Planner to predict post‐PCI FFR in patients with chronic coronary syndromes undergoing percutaneous revascularization.

ObjectiveBleeding after endoscopic submucosal dissection (ESD) for early gastric cancer (EGC) is a frequent adverse event after ESD. We aimed to develop and externally validate a clinically useful prediction model (BEST-J score: Bleeding after ESD Trend from Japan) for bleeding after ESD for EGC.DesignThis retrospective study enrolled patients who underwent ESD for EGC. Patients in the derivation cohort (n=8291) were recruited from 25 institutions, and patients in the external validation cohort (n=2029) were recruited from eight institutions in other areas. In the derivation cohort, weighted points were assigned to predictors of bleeding determined in the multivariate logistic regression analysis and a prediction model was established. External validation of the model was conducted to analyse discrimination and calibration.ResultsA prediction model comprised 10 variables (warfarin, direct oral anticoagulant, chronic kidney disease with haemodialysis, P2Y12 receptor antagonist, aspirin, cilostazol, tumour size >30 mm, lower-third in tumour location, presence of multiple tumours and interruption of each kind of antithrombotic agents). The rates of bleeding after ESD at low-risk (0 to 1 points), intermediate-risk (2 points), high-risk (3 to 4 points) and very high-risk (≥5 points) were 2.8%, 6.1%, 11.4% and 29.7%, respectively. In the external validation cohort, the model showed moderately good discrimination, with a c-statistic of 0.70 (95% CI, 0.64 to 0.76), and good calibration (calibration-in-the-large, 0.05; calibration slope, 1.01).ConclusionsIn this nationwide multicentre study, we derived and externally validated a prediction model for bleeding after ESD. This model may be a good clinical decision-making support tool for ESD in patients with EGC.

Objective To investigate the relationship between CONUT score and serum vitamin (25-OHD, folic acid, vitamin B12) levels and CHD in young and middle-aged adults, and to analyze the value of CONUT score combined with serum vitamin (25-OHD, folic acid, vitamin B12) levels in predicting the risk of CHD in young and middle-aged adults. Methods This study was a retrospective case–control study. A total of 135 young and middle-aged patients with CHD diagnosed by coronary angiography in Tangshan Workers’ Hospital from April 2023 to October 2024 were selected as the case group ( n  = 135), and 120 patients with negative coronary angiography or CTA results in our hospital during the same period were selected as the control group ( n  = 120). The nutritional status of the subjects was evaluated by CONUT score, and the serum vitamin level of the subjects was detected by chemiluminescence method. Univariate and multivariate Logistic regression analysis were used to analyze the relationship between different nutritional status levels, serum vitamin levels and CHD in young and middle-aged people. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of CONUT score combined with serum vitamin level for the risk of CHD in young and middle-aged adults. Results The detection rate of malnutrition in the CHD group was 48.90%, and the detection rate of malnutrition in the control group was 30.80%. The multivariate results show that according to the unadjusted model, there was a significant relationship between high CONUT score, low 25-OHD, low folic acid, and low serum vitamin B12 levels and CHD. In multifactor models 2, after adjusting for gender, family history of premature CHD, history of hypertension, history of diabetes, history of smoking, LDL-C, Hcy, CRP, blood glucose, blood uric acid, serum creatinine and other traditional risk factors of CHD, it was found that CONUT score ≥ 2 points, serum 25-OHD ≤ 17.20 ng/ml, folic acid ≤ 10.90 ng/ml, serum vitamin B12 ≤ 485.50 pg/ml, the risk of CHD was higher. ROC curve analysis showed that CONUT score combined with three serum vitamins, AUC was 0.836(95% CI :0.788–0.884), the sensitivity and specificity were 83.7% and 69.2%( P  < 0.05). Conclusion The detection rate of nutritional imbalance in young and middle-aged patients with CHD is high, and there is a significant relationship between nutritional status and serum vitamin level and the risk of CHD in young and middle-aged patients. CONUT score and serum vitamin level can be used as indicators to evaluate the risk of CHD in young and middle-aged people.

Ondine Walter,1,2 Julien Maquet,1,2 Helene Derumeaux,3 Guillaume Moulis,1,2 Margaux Lafaurie2,4 1Service de Médecine Interne, Centre Hospitalier Universitaire de Toulouse, Toulouse, France; 2Centre d’Investigation Clinique 1436, Centre Hospitalier Universitaire de Toulouse, Toulouse, France; 3Département d’Information Médicale, Centre Hospitalier Universitaire de Toulouse, Toulouse, France; 4Service de Pharmacologie Médicale et Clinique, Faculté de Médecine, Centre Hospitalier Universitaire de Toulouse, Toulouse, FranceCorrespondence: Ondine WalterService de Médecine Interne, pavillon URM, CHU Purpan, place du Dr Baylac, TSA 40031, 31059, Toulouse Cedex 9, FranceTel +33 561 779 677Fax +33 561 778 058Email walter.o@chu-toulouse.frKeywords: sickle cell anemia, vaso occlusive crisis, predictive value of test, epidemiology

Detailed grading of chills is more useful for diagnosing bacteremia than simply classifying the presence or absence of chills. However, its value added to other clinical information has not been evaluated. To evaluate the value of adding chills grading to other clinical information compared to simply noting the presence or absence of chills for predicting bacteremia in patients with suspected infection. Prospective observational study. Adult patients admitted to two acute-care hospitals with suspected infection from April 2018 to March 2019. Two types of categorization for chills were applied: \"presence\" or \"absence\" (dichotomized chills); and \"no chills\", \"mild/moderate chills\", and \"shaking chills\" (trichotomized chills). Three multivariable logistic regression models incorporating each of dichotomized chills, trichotomized chills, and C-reactive protein (CRP) with other clinical information were developed and compared. To assess the potential consequences of using each model to identify patients with high risk of bacteremia (i.e., requiring prompt intervention), we applied a cut-off point of an estimated probability of 60%. The number of patients with bacteremia correctly identified by each model was compared. Among the 2,013 patients, 327 (16.2%) were diagnosed with bacteremia. The three models showed comparable discrimination and calibration performance. At the 60% cut-off, the dichotomized chills model correctly identified 11 patients (3.4% [95% confidence interval (CI) 1.9-3.4] of patients with bacteremia). The trichotomized chills model and CRP model correctly identified an additional 15 patients (4.6% [95% CI 2.8-7.4]) and 2 patients (0.6% [95% CI 0.1-2.3]) with bacteremia, respectively. Differentiating shaking chills in comparison with dichotomized chills for predicting bacteremia allowed the correct identification of an additional 4.6% of patients with bacteremia. Detailed grading of chills can be assessed without additional time, cost, or burden on patients and can be recommended in the routine history taking.

Objective: To evaluate the prognostic utility of the Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score 3 (SAPS 3) in COVID-19 patients and assess whether incorporating C-reactive protein (CRP), procalcitonin, lactate, and lactate dehydrogenase (LDH) enhances their predictive accuracy. Methods: Single-center, observational, cohort study. We analyzed a database of adult ICU patients with severe or critical COVID-19 treated at a large academic center. We used binary logistic regression for all analyses. We assessed the predictive performance of SAPS 3 and SOFA scores within 24 h of admission, individually and in combination with serum lactate, LDH, CRP, and procalcitonin. We examined the independent association of these biomarkers with hospital mortality. We evaluated discrimination using the C-statistic and determined clinical utility with decision curve analysis. Results: We included 1395 patients, 66% of whom required mechanical ventilation, and 59.7% needed vasopressor support. Patients who died (39.7%) were significantly older (61.1 ± 15.9 years vs. 50.1 ± 14.5 years, p < 0.001) and had more comorbidities than survivors. Among the biomarkers, only procalcitonin was independently associated with higher mortality in the multivariable analysis, in a non-linear pattern. The AUROC for predicting hospital mortality was 0.771 (95% CI: 0.746–0.797) for SAPS 3 and 0.781 (95% CI: 0.756–0.805) for the SOFA score. A model incorporating the SOFA score, age, and procalcitonin demonstrated high AUROC of 0.837 (95% CI: 0.816–0.859). These associations with the SOFA score showed greater clinical utility. Conclusions: The SOFA score may aid clinical decision-making, and incorporating procalcitonin and age could further enhance its prognostic utility.

ObjectiveThe majority of cardiovascular diagnoses in the Danish National Patient Registry (DNPR) remain to be validated despite extensive use in epidemiological research. We therefore examined the positive predictive value (PPV) of cardiovascular diagnoses in the DNPR.DesignPopulation-based validation study.Setting1 university hospital and 2 regional hospitals in the Central Denmark Region, 2010–2012.ParticipantsFor each cardiovascular diagnosis, up to 100 patients from participating hospitals were randomly sampled during the study period using the DNPR.Main outcome measureUsing medical record review as the reference standard, we examined the PPV for cardiovascular diagnoses in the DNPR, coded according to the International Classification of Diseases, 10th Revision.ResultsA total of 2153 medical records (97% of the total sample) were available for review. The PPVs ranged from 64% to 100%, with a mean PPV of 88%. The PPVs were ≥90% for first-time myocardial infarction, stent thrombosis, stable angina pectoris, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, takotsubo cardiomyopathy, arterial hypertension, atrial fibrillation or flutter, cardiac arrest, mitral valve regurgitation or stenosis, aortic valve regurgitation or stenosis, pericarditis, hypercholesterolaemia, aortic dissection, aortic aneurysm/dilation and arterial claudication. The PPVs were between 80% and 90% for recurrent myocardial infarction, first-time unstable angina pectoris, pulmonary hypertension, bradycardia, ventricular tachycardia/fibrillation, endocarditis, cardiac tumours, first-time venous thromboembolism and between 70% and 80% for first-time and recurrent admission due to heart failure, first-time dilated cardiomyopathy, restrictive cardiomyopathy and recurrent venous thromboembolism. The PPV for first-time myocarditis was 64%. The PPVs were consistent within age, sex, calendar year and hospital categories.ConclusionsThe validity of cardiovascular diagnoses in the DNPR is overall high and sufficient for use in research since 2010.

Background Extending the clinical indications for laparoscopic liver resection (LLR) should be carefully considered based on a surgeon’s experience and skill. However, objective indexes to help surgeons assess the estimated difficulty of LLR are scarce. The aim of our study was to develop the first objective numerical rating scale to predict the surgical difficulty of various LLR procedures. Methods We performed a retrospective review of the operative outcomes of 187 patients who underwent a pure LLR. First, the value of preoperative factors for predicting surgical time was evaluated by multivariate linear regression analyses, and a scoring system was constructed. Next, the integrity of our predictive linear model was evaluated against the documented operative outcomes for patients forming our study group. Results Four predictive factors were identified and scored based on the weighted contribution of each factor predicting surgical time: extent of resection (scored 0, 2, or 3); location of tumor (scored 0, 1, or 2); obesity (scored 0 or 1); and platelet count (scored 0 or 1). The scores were summed to classify surgical difficulty into three levels: low (total score ≤1); medium (total score 2–3); and high (total score ≥4). Operative outcomes, including surgical time, volume of blood loss, length of hospital stay, and rate of morbidity, were significantly different between the three surgical difficulty levels. Conclusion Our novel model will be useful for surgeons to predict the difficulty of an LLR procedure relative to their own experience and skill.

Imaging has traditionally played a minor role in the diagnosis and staging of prostate cancer. However, recent controversies generated by the use of prostate-specific antigen (PSA) screening followed by random biopsy have encouraged the development of new imaging methods for prostate cancer. Multiparametric magnetic resonance imaging (mpMRI) has emerged as the imaging method best able to detect clinically significant prostate cancers and to guide biopsies. Here, the authors explain what mpMRI is and how it is used clinically, especially with regard to high-risk populations, and we discuss the impact of mpMRI on treatment decisions for men with prostate cancer.

Objectives: Lung cancer remains as the most common cause of cancer-related death. The possible relationships between inflammatory markers and lung cancer prognosis have yet to be clarified. In this study, we aimed to assess and compare various inflammatory markers and prognostic tests for their role in predicting mortality in patients with lung cancer who were admitted to the intensive care unit. Methods: A total of 229 patients diagnosed with small cell or non-small cell lung cancer who attended follow-up after treatment were included. The predictive performance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), modified Glasgow prognostic score (mGPS), Prognostic nutritional index (PNI), APACHE II score, and MPM II-Admission (Mortality Probability Models II-0) were assessed in terms of mortality status. We also performed multivariable logistic regression to determine whether any of these parameters were independently associated with mortality. Results: We included 229 patients into our study; the mean age was 66.17 ± 11.89 years. Among these, 135 (58.95%) patients died and 94 (41.05%) patients were discharged. When we evaluated the performance of the prognostic scores in predicting mortality, we found mGPS, MPM II-Admission, and APACHE II scores had the highest sensitivity, and MPM II-Admission, PNI, and APACHE II scores had the highest specificity. Multivariable regression revealed that PNI was the only inflammation-related parameter that was independently associated with mortality. Conclusions: PNI, APACHE-II, and MPM II-Admission may be used as easily accessible tests for mortality estimation in lung cancer patients admitted to the ICU.