Multiparametric Score Research Articles

Histopathological and Immune Prognostic Factors in Colo-Rectal Liver Metastases.

Simple SummaryClinical management of colo-rectal liver metastasis would benefit from a refined stratification of patients in prognostic groups, in order to identify the best therapeutic option. Efforts are ongoing in the definition of parameters associated with clinical behaviors, which could help classifying patients in clinically relevant groups. Here we aimed at discussing the recent advances in this field, and we introduced current and new promising candidates, such as morphological tumor features and immune components, which have been showing significant association with survival. Some of these parameters are slowly reaching the clinic and further efforts are ongoing in the attempt to combine them in multiparametric scores.Prognostic studies are increasingly providing new tools to stratify colo-rectal liver metastasis patients into clinical subgroups, with remarkable implications in terms of clinical management and therapeutic choice. Here, the strengths and hurdles of current prognostic tools in colo-rectal liver metastasis are discussed. Alongside more classic histopathological parameters, which capture features related to the tumor component, such as tumor invasion, tumor growth pattern and regression score, we will discuss immune mediators, which are starting to be considered important features. Their objective quantification has shown significant results in prognostication studies, with most of the work focused on adaptive immune cells, namely T cells. As for macrophages, they are only starting to be appreciated and we will present recent advances in evaluation of macrophage morphological features. Deeper knowledge acquired by multiparametric analyses is rapidly uncovering the variety of immune players that should be assessed. The future projection is to implement deep-learning histopathological tools and to integrate histopathological and immune metrics in multiparametric scores, with the ultimate objective to achieve a deeper resolution of the tumor features and their relevance for colo-rectal liver metastasis.

Precision Medicine in Hematology 2021: Definitions, Tools, Perspectives, and Open Questions.

During the past few years, our understanding of molecular mechanisms and cellular interactions relevant to malignant blood cell disorders has improved substantially. New insights include a detailed knowledge about disease-initiating exogenous factors, endogenous (genetic, somatic, epigenetic) elicitors or facilitators of disease evolution, and drug actions and interactions that underlie efficacy and adverse event profiles in defined cohorts of patients. As a result, precision medicine and personalized medicine are rapidly growing new disciplines that support the clinician in making the correct diagnosis, in predicting outcomes, and in optimally selecting patients for interventional therapies. In addition, precision medicine tools are greatly facilitating the development of new drugs, therapeutic approaches, and new multiparametric prognostic scoring models. However, although the emerging roles of precision medicine and personalized medicine in hematology and oncology are clearly visible, several questions remain. For example, it remains unknown how precision medicine tools can be implemented in healthcare systems and whether all possible approaches are also affordable. In addition, there is a need to define terminologies and to relate these to specific and context-related tools and strategies in basic and applied science. To discuss these issues, a working conference was organized in September 2019. The outcomes of this conference are summarized herein and include a proposal for definitions, terminologies, and applications of precision and personalized medicine concepts and tools in hematologic neoplasms. We also provide proposals aimed at reducing costs, thereby making these applications affordable in daily practice.

Standard ECG for differential diagnosis between Anderson-Fabry disease and hypertrophic cardiomyopathy

ObjectivesTo evaluate the role of the ECG in the differential diagnosis between Anderson-Fabry disease (AFD) and hypertrophic cardiomyopathy (HCM).MethodsIn this multicentre retrospective study, 111 AFD patients with left ventricular hypertrophy...

Predicting heart failure transition and progression: a weighted risk score from bio-humoral, cardiopulmonary and echocardiographic stress testing

Abstract Funding Acknowledgements Type of funding sources: None. Aims. We tested the prognostic role of a risk score including bio-humoral evaluation, cardiopulmonary-echocardiographic stress (CPET-ESE) and lung ultrasound, in patients with heart failure (HF) with reduced and preserved ejection fraction (HFrEF and HFpEF), and subjects at risk of developing HF (American College of Cardiology/American Heart Association Stages A and B). Methods and results. We evaluated 318 subjects: 94 in Stages A-B, 194 in Stage C (85 HFpEF and 109 HFrEF), and 30 age and sex-matched controls (Stage 0). During a median follow-up of 18.5 months, we reported 40 urgent HF visits, 31 HF hospitalisations and 10 cardiovascular deaths. Cox proportional-hazards regression for predicting adverse events identified five independent predictors and each was assigned a number of points proportional to its regression coefficient: Δstress-rest B-lines >10 (3 points), peak oxygen consumption <16 mL/kg/min (2 points), minute ventilation/carbon dioxide production slope ≥36 (2 points), peak systolic pulmonary artery pressure ≥50 mmHg (1 point) and resting N-terminal pro-brain natriuretic peptide (NT-proBNP) >900 pg/mL (1 point). We defined three risk categories: low-risk (<3 points), intermediate-risk (3-6 points), and high-risk (>6 points). The event-free survival probability for these three groups were 93%, 52% and 20%, respectively. Hazard Ratio was 4.55 for each risk category upgrade (95% confidence interval [CI], 3.44-5.93). The area-under-curve for the scoring system to predict events was 0.92 (95% CI 0.88-0.96). Conclusion. A multiparametric risk score including indices of exercise-induced pulmonary congestion, markers of cardiopulmonary dysfunction and NT-proBNP identifies patients at increased risk for HF events across the HF spectrum. Table 1 Variable EPYC score EPYC score <3 (low risk) n = 217 EPYC score 3-6 (intermediate risk) n = 70 EPYC score >6 (high risk) n = 31 p-value (between risk categories) Event-free (n = 244) 0 (0 - 2) 210 (97) 32 (46) 2 (6) <0.0001 With events (n = 74) 6 (4 - 9) 7 (3) 38 (54) 29 (94) <0.0001 p-value (event-free vs with events) <0.0001 <0.0001 <0.0001 <0.0001 Stage 0-Controls (n = 30) 0 (0 - 1) 30 0 0 <0.0001 Stages A-B (n = 94) 1 (0 - 2) 85 (45) 6 (9) 3 (10) <0.0001 Stage C-HFpEF (n = 85) 3 (1 - 6)*† 46 (25) 29 (41) 10 (32) <0.0001 Stage C-HFrEF (n = 109) 4 (2 - 7)*† 56 (30) 35 (50) 18 (58) <0.0001 p-value (between HF Stages) <0.0001 <0.0001 <0.0001 <0.0001 Values are mean ± standard deviation, n (%), or median [25th quartile, 75th quartile]. * p < 0.01 vs Stage 0-Controls; † p < 0.01 vs Stages A-B. Abstract Figure 1

A Multiparametric Assessment of Human Islets Predicts Transplant Outcomes in Diabetic Mice

Prior to transplantation into individuals with type 1 diabetes, in vitro assays are used to evaluate the quality, function and survival of isolated human islets. In addition to the assessments of these parameters in islet, they can be evaluated by multiparametric morphological scoring (0–10 points) and grading (A, B, C, D, and F) based on islet characteristics (shape, border, integrity, single cells, and diameter). However, correlation between the multiparametric assessment and transplantation outcome has not been fully elucidated. In this study, 55 human islet isolations were scored using this multiparametric assessment. The results were correlated with outcomes after transplantation into immunodeficient diabetic mice. In addition, the multiparametric assessment was compared with oxygen consumption rate of isolated islets as a potential prediction factor for successful transplantations. All islet batches were assessed and found to score: 9 points (n = 18, Grade A), 8 points (n = 19, Grade B), and 7 points (n = 18, Grade B). Islets that scored 9 (Grade A), scored 8 (Grade B) and scored 7 (Grade B) were transplanted into NOD/SCID mice and reversed diabetes in 81.2%, 59.4%, and 33.3% of animals, respectively (P < 0.0001). Islet scoring and grading correlated well with glycemic control post-transplantation (P < 0.0001) and reversal rate of diabetes (P < 0.05). Notably, islet scoring and grading showed stronger correlation with transplantation outcome compared to oxygen consumption rate. Taken together, a multiparametric assessment of isolated human islets was highly predictive of transplantation outcome in diabetic mice.

Selecting Patients with Favorable Risk, Grade Group 2 Prostate Cancer for Active Surveillance-Does Magnetic Resonance Imaging Have a Role?

The National Comprehensive Cancer Network® recommends that selected men with grade group 2 prostate cancer be considered for active surveillance. However, selecting which patients with grade group 2 disease can be safely managed by active surveillance remains controversial. The aim of this study was to evaluate the association of multiparametric magnetic resonance imaging with adverse pathology in the radical prostatectomy specimen of men with favorable risk grade group 2 prostate cancer, which could help select patients for active surveillance. We retrospectively analyzed a cohort of patients with favorable grade group 2 disease who underwent radical prostatectomy between 2010 and 2019. Preoperative multiparametric magnetic resonance imaging was scored as negative (no identifiable lesion), positive (identifiable lesion) or equivocal. We defined a multivariable logistic regression model with multiparametric magnetic resonance imaging score as the predictor and adverse pathology (up staging to T3a/b disease, upgrading to ≥grade group 3 or lymph node invasion) as the outcome, adjusting for preoperative prostate specific antigen, biopsy Gleason grade, clinical stage, and number of negative and positive prostate biopsy cores. Secondary outcomes of biochemical recurrence, grade group upgrading alone and the added value of incorporating multiparametric magnetic resonance imaging data into the nomogram were also investigated. We identified 1,117 patients with favorable risk grade group 2 disease who underwent radical prostatectomy. Positive multiparametric magnetic resonance imaging was associated with higher rates of adverse pathology (OR 2.55, 95% CI 1.75-3.40, p <0.0001) and upgrading (OR 3.89, 95% CI 2.00-7.56, p <0.0001). However, as our study included only grade group 2 patients who underwent radical prostatectomy, our cohort may represent a higher risk group than grade group 2 patients as a whole. Adding multiparametric magnetic resonance imaging results to a standard prediction model led to higher net benefit on decision curve analysis. An identifiable lesion on multiparametric magnetic resonance imaging was associated with an increased risk of aggressive pathological features in the radical prostatectomy specimen of patients with favorable risk grade group 2 prostate cancer who were potential active surveillance candidates. This information could be used to inform biopsy strategy, counsel patients on treatment options and guide strategies for those on active surveillance. Combining multiple magnetic resonance imaging modalities (multiparametric magnetic resonance imaging) provides a more accurate prediction of the risk presented by prostate cancer than current prediction methods. In this study, positive magnetic resonance imaging results approximately doubled the chances that a patient with favorable risk prostate cancer would be found to have adverse pathology when their prostate was removed. Thus, multiparametric magnetic resonance imaging could help select patients with favorable risk cancer who may be good candidates for active surveillance, and help guide biopsy and surveillance strategies for such patients.

Usefulness of a single-parameter tool for the prediction of large vessel occlusion in acute stroke.

In acute stroke, large vessel occlusion (LVO) should be promptly identified to guide patient's transportation directly to comprehensive stroke centers (CSC) for mechanical thrombectomy (MT). In many cases, prehospital multi-parameter scores are used by trained emergency teams to identify patients with high probability of LVO. However, in several countries, the first aid organization without intervention of skilled staff precludes the on-site use of such scores. Here, we assessed the accuracy of LVO prediction using a single parameter (i.e. complete hemiplegia) obtained by bystander's telephone-based witnessing. This observational, single-center study included consecutive patients who underwent intravenous thrombolysis at the primary stroke center and/or were directly transferred to a CSC for MT, from January 1, 2015 to March 1, 2020. We defined two groups: patients with initial hemiplegia (no movement in one arm and leg and facial palsy) and patients without initial hemiplegia, on the basis of a bystander's witnessing. During the study time, 874 patients were included [mean age 73years (SD 13.8), 56.7% men], 320 with initial hemiplegia and 554 without. The specificity of the hemiplegia criterion to predict LVO was 0.88, but its sensitivity was only 0.53. Our results suggest that the presence of hemiplegia as witnessed by a bystander can predict LVO with high specificity. This single criterion could be used for decision-making about direct transfer to CSC for MT when the absence of emergency skilled staff precludes the patient's on-site assessment, especially in regions distant from a CSC.

Predictors of 5-year mortality in patients with congestive heart failure and implanted devices for cardiac resynchronization therapy

Abstract Cardiac resynchronization therapy (CRT) has a wide range of therapeutic benefits including reduction in hospitalizations and death in appropriately selected patients, while the appropriate selection remains the cornerstone of CRT. Apart from the current selection criteria, many additional factors may play an incremental role affecting cardiac prognosis and CRT efficacy. Aim To examine the ability of a multiparametric score to predict 5-year mortality in patients with congestive heart failure (HF) treated with CRT. Methods The study enrolled 218 HF patients (83% men, 17% women; mean age of 58.7±10.7 years) with left ventricular ejection fraction (LVEF) ≤35%, NYHA class II-IV. 130 patients (59.6%) had ischemic etiology of HF (84 with prior myocardial infarction), 88 patients (31.4%) – non-ischemic cardiomyopathy. 57.3% of patients had left bundle branch block (LBBB), mean QRS width was 150.5±38.4 ms. Results The mean follow-up period was 38.8±20.9 months. The 5-year survival was 69.3%. Points were calculated from 11 parameters identified as factors associated with all-cause mortality in multivariate analysis: gender (female – 0, male – 1); etiology of HF (non-ischemic – 0, ischemic – 1); history of myocardial infarction (no – 0, yes – 1); NYHA (II or III – 0, IV – 1); QRS (≥150 ms or ≤120 ms + 3 parameters of mechanical dyssynchrony – 0, 120–149 ms – 1); rhythm (sinus or radiofrequency ablation of atrial fibrillation (AF) – 0, AF – 1); LBBB (LBBB – 0, non-LBBB – 1); LVEF (&amp;gt;30% – 0, ≤30% – 1); frailty (not frail – 0, frail – 1); PR interval (&amp;lt;200 ms – 0; ≥200 ms – 1); NT-proBNP (median value) (&amp;lt;1788 pg/ml – 0, ≥1788 pg/ml – 1). To calculate the score, the sum of points was divided by the number of parameters. If less than 3 items were missing the denominator adjusted accordingly. The 5-year survival rate for patients with highest tertile score (&amp;gt;0.44; n=43) was 43.1%, for middle tertile (0.44≤ score ≥0.22; n=124) – 73.4% and 88.4% for lowest tertile (&amp;lt;0.22; n=51) (Log rank p&amp;lt;0.001). Conclusions Multiparametric score can be used to predict 5-year mortality in patients with CRT. Survival curves in groups by tertiles Funding Acknowledgement Type of funding source: None

Hydroxychloroquine and QTc: beyond COVID-19

Hydroxychloroquine is an antimalarial drug also known for its anti-inflammatory and antiviral effects, which have raised the interest of many researchers for its potential use in COVID-19 patients. It is known that this drug, being able to influence the cardiac repolarization phase with QTc interval prolongation, can be potentially harmful, chiefly in elderly subjects with frailty syndrome, several comorbidities and polypharmacotherapy. Therefore, although electrocardiogram monitoring of QTc prolongation is the focal point for reducing the arrhythmic risk of these patients, in order to identify the most exposed patients, the traditional Comprehensive Geriatric Assessment should be combined with a multiparametric risk score for QTc prolongation.

Multi-parametric evaluation of autologous cultivated Limbal epithelial cell transplantation outcomes of Limbal stem cell deficiency due to chemical burn

BackgroundThe sparsity of established tools for the grading of limbal stem cell deficiency hinder objective assessments of the clinical outcome of cultivated limbal epithelial cell transplantation. To advance towards the development of standards for the comparison of the outcomes of these bio-surgical protocols we have now applied a battery of recognized objective and patient-declared subjective outcome criteria to the autologous modality of cultivated limbal epithelial cell transplantation.MethodsThe prospective study involved ten patients (M/F = 9/1; mean age = 42.1 years) displaying overt unilateral limbal stem cell deficiency complying with the inclusion criteria described in Methods. Limbal biopsies were obtained from the contralateral eye and their outgrowths after 2-week cultures were transplanted on the affected eye after pannus resection. Outcomes were followed up for 12 months. The objective tests were scores for best-corrected visual acuity (BCVA); using the LogMAR scale, a multiparametric ocular surface score (OSS), and the Schirmer’s test. Subjective scores were based on patient answers to a) perception of visual improvement/pain; b) the 25-item National Eye Institute Visual Function Questionnaire (NEI-VFQ 25); and c) the 12-item Ocular Surface Disease Index Questionnaire (OSDI). All procedures were performed under good manufacture practices using solely xeno-free reagents. In all cases, a single biopsy was divided into two pieces and they were expanded in order to prevent outgrowth failure. In 5 patients, both biopsies generated healthy culture sheet. In those cases the lesser outgrowth were used for immune-histological characterization.ResultsThe experimental parallel outgrowth samples showed a similar percent of p63α+ cells. PreOp and 12-month PostOp BCVAs and OSSs were, respectively, 1.15 ± 0.70; 0.21 ± 0.13 and 7.40 ± 2.01; 2,30 ± 1.30, (p < 0.05). Patient’s responses to all three question sets except ocular pain were consistent with significant improvement (p < 0.05).ConclusionObjective clinical metrics demonstrate that in patients with limbal stem cell deficiency, cultivated limbal epithelial cell transplantation improves vision and ocular surface health and subjective visual perceptions.

Early-stage predictors of the acute phase duration in uncomplicated COVID-19 pneumonia.

ObjectiveIn this study, we aimed to highlight the common early‐stage clinical and laboratory variables independently related to the acute phase duration in patients with uncomplicated coronavirus disease (COVID‐19) pneumonia.MethodsIn hospitalized patients, the acute phase disease duration was followed using the Brescia‐COVID respiratory severity scale. Noninvasive ventilation was administered based on clinical judgment. Patients requiring oropharyngeal intubation were excluded from the study. For parameters to be measured at the hospital entrance, age, clinical history, National Early Warning Score 2 (a multiparametric score system), partial pressure of oxygen in arterial blood/fraction of inspired oxygen (P/F ratio), C‐reactive protein, and blood cell count were selected.ResultsIn 64 patients, age (direct relationship), P/F, and platelet number (inverse relationship) independently accounted for 43% of the acute phase duration of the disease (P < .001).ConclusionsFor the first time, the present results revealed that the acute phase duration of noncomplicated pneumonia, resulting from severe acute respiratory syndrome coronavirus 2, is independently predicted from a patient's age, as well as based on the hospital entrance values of P/F ratio and peripheral blood platelet count.

Multi-parametric magnetic resonance imaging in acute necrotizing encephalopathy of children: validity and prognostic value

BackgroundAcute necrotizing encephalopathy of children (ANEC) is a rare fulminant type of acute encephalopathy that mainly occurs in children with a characteristic clinico-radiological pattern. It is commonly preceded by viral infections. The condition carries a poor prognosis with high morbidity and mortality rates. We highlight the relationship between diagnostic multi-parametric magnetic resonance imaging (MRI) findings and correlate them with the clinical outcome of children with ANEC by enrollment of MRI scoring.ResultsThe thalami were involved in all 30 patients, brain stem in 80%, basal ganglia (13.3%), cerebral white matter (WM) in 73%, and cerebellar WM in 33%. Hemorrhage was present in 86.7% patients, edema 80%, and necrosis in 13.3%. We found that the patients having the highest MRI scores were in the poor outcome category; whereas the patients with lower MR score (1 or 2) had better outcomes. Statistically positive correlation (r= 0.1198) was found between the multi-parametric MR score and the outcome category.ConclusionAn extended multi-parametric MRI should be performed in ANEC, allowing early detection and scoring of the disease for better prognosis. There is a positive correlation between the clinical outcome and the MR scoring.

Ventilator-associated pneumonia in neonates: the role of point of care lung ultrasound

No consensus exists regarding the definition of ventilator-associated pneumonia (VAP) in neonates and reliability of chest X-ray (CXR) is low. Lung ultrasound (LU) is a potential alternative diagnostic tool. The aim was to define characteristics of VAP in our patient population and propose a multiparameter score, incorporating LU, for VAP diagnosis. Between March 25, 2018, and May 25, 2019, infants with VAP were identified. Clinical, laboratory and microbiology data were collected. CXRs and LU scans were reviewed. A multiparameter VAP score, including LU, was calculated on Day 1 and Day 3 for infants with VAP and for a control group and compared with CXR. VAP incidence was 10.47 episodes/1000 ventilator days. LU and CXR were available for 31 episodes in 21 infants with VAP, and for six episodes in five patients without VAP. On Day 1, a VAP score of > 4, and on Day 3 a score of > 5 showed sensitivity of 0.94, and area under the curve of 0.91 and 0.97, respectively. AUC for clinical information only was 0.88 and for clinical and CXR 0.85.Conclusion: The multiparameter VAP score including LU could be useful in diagnosing VAP in neonates with underlying lung pathology.What is Known:• Ventilator associated pneumonia (VAP) is common in infants on the neonatal unit and is associated with increased use of antibiotics, prolonged ventilation and higher incidence of chronic lung disease.• Commonly used definitions of VAP are difficult to apply in neonates and interpretation of chest X-ray is challenging with poor inter-rater agreement in patients with underlying chronic lung disease.What is New:• The multiparameter VAP score combining clinical, microbiology and lung ultrasound (LU) data is predictive for VAP diagnosis in preterm infants with chronic lung disease.• LU findings of VAP in neonates showed high inter-rater agreement and included consolidated lung areas, dynamic bronchograms and pleural effusion.

Accuracy of a multiparametric score based on pulse wave analysis for prediction of fluid responsiveness: ancillary analysis of an observational study.

PurposeThe pressure recording analytical method (PRAM) monitor is a non-invasive pulse contour cardiac output (CO) device that cannot be considered interchangeable with the gold standard for CO estimation. It, however, generates additional hemodynamic indices that need to be evaluated. Our objective was to investigate the performance of a multiparametric predictive score based on a combination of several parameters generated by the PRAM monitor to predict fluid responsiveness.MethodsSecondary analysis of a prospective observational study from April 2016 to December 2017 in two French teaching hospitals. We included critically ill patients who were monitored by esophageal Doppler monitoring and an invasive arterial line, and received a 250–500 mL crystalloid fluid challenge. The main outcome measure was the predictive score discrimination evaluated by the area under the receiver operating characteristics curve.ResultsThe three baseline PRAM-derived parameters associated with fluid responsiveness in univariate analysis were pulse pressure variation, cardiac cycle efficiency, and arterial elastance (P < 0.01, P = 0.03, and P < 0.01, respectively). The median [interquartile range] predictive score, calculated after discretization of these parameters according to their optimal threshold value was 3 [2–3] in fluid responders and 1 [1–2] in fluid non-responders, respectively (P < 0.001). The area under the curve of the predictive score was 0.807 (95% confidence interval, 0.662 to 0.909; P < 0.001).ConclusionA multiparametric score combining three parameters generated by the PRAM monitor can predict fluid responsiveness with good positive and negative predictive values in intensive care unit patients.Electronic supplementary materialThe online version of this article (10.1007/s12630-020-01736-y) contains supplementary material, which is available to authorized users.

P1110Role of an extensive diagnostic work-up in the detection of concealed cardiomyopathies in athletes with complex ventricular arrhythmias and implications for sports" eligibility assessment

Abstract Background ventricular Arrhythmias (VAs) are a common clinical problem and a critical issue with regards to sports" eligibility in athletes. Although VAs can be considered a benign feature of the athlete’s heart adaptive phenotype, they may also be the only clinical manifestation of a concealed cardiomyopathy, potentially heralding sudden cardiac death (SCD) during sports activity. Purpose to evaluate the diagnostic contribution and the implications for sports eligibility assessment of a thorough non-invasive and invasive work-up including electrophysiology study (EPS), electroanatomical mapping (EAM) and endomyocardial biopsy (EMB) in athletes with complex VAs and to derive a multiparametric risk score in order to easily predict structural heart diseases’ diagnosis. Methods we conducted a prospective, single-arm, open-label single center, observational study. All consecutive athletes presenting for evaluation at our institution after being disqualified from participating in sports due to complex VAs were enrolled. The athletes underwent a baseline non-invasive diagnostic protocol with transthoracic echocardiogram and gadolinium enhanced cardiac magnetic resonance imaging (cMRI). Subsequently EPS, EAM and EAM-guided EMB were performed if deemed necessary. Sports eligibility status was re-assessed at 6 months’ follow-up. A multivariable logistic regression model was built, considering cMRI as the gold standard exam. Results after diagnostic evaluation, 55 subjects (26.4%) had a diagnosis of heart disease, most commonly myocarditis (n = 27) and arrhythmogenic right ventricular cardiomyopathy (ARVC, n = 16). After 6 months, 100 athletes (48.1%) were judged eligible to participate in competitive sports and 46 subjects (22.1%) were deemed eligible to participate in non-competitive sports. On multivariable logistic-regression analysis, abnormalities on ECG (OR 5.3) or on echocardiogram (OR 3.7), sustained VA inducibility on EPS (OR 17.7) and low-voltage areas on EAM (OR 7.7) proved all predictive of concealed structural heart diseases’ diagnosis. We derived two simple risk scores: a 40-points risk score and an 8-points risk score (obtained by weighing each variable according to the regression model’s ORs). Both these risk scores’ performance proved very good (AUC = 0.856 for the 40-points score and AUC = 0.852 for the 8-points score, figure 1). Conclusions approximately 1/4 of athletes presenting with complex VAs have a concealed heart disease, most commonly myocarditis or ARVC. ECG, echocardiogram and EAM abnormalities and sustained VAs inducibility on EPS are predictive of structural heart diseases’ detection. Therefore, these diagnostic tests should be routinely included in the evaluation of athletes with complex VAs. A risk score including the results of these tests can greatly help in the prediction of concealed structural heart diseases’ diagnosis. More than 2/3 of subjects were judged eligible to participate in sports at 6 months’ follow-up. Abstract Figure 1. ROC curves for diagnosis

Large scale analyses of genotype-phenotype relationships of glycine decarboxylase mutations and neurological disease severity.

Monogenetic diseases provide unique opportunity for studying complex, clinical states that underlie neurological severity. Loss of glycine decarboxylase (GLDC) can severely impact neurological development as seen in non-ketotic hyperglycinemia (NKH). NKH is a neuro-metabolic disorder lacking quantitative predictors of disease states. It is characterized by elevation of glycine, seizures and failure to thrive, but glycine reduction often fails to confer neurological benefit, suggesting need for alternate tools to distinguish severe from attenuated disease. A major challenge has been that there are 255 unique disease-causing missense mutations in GLDC, of which 206 remain entirely uncharacterized. Here we report a Multiparametric Mutation Score (MMS) developed by combining in silico predictions of stability, evolutionary conservation and protein interaction models and suitable to assess 251 of 255 mutations. In addition, we created a quantitative scale of clinical disease severity comprising of four major disease domains (seizure, cognitive failure, muscular and motor control and brain-malformation) to comprehensively score patient symptoms identified in 131 clinical reports published over the last 15 years. The resulting patient Clinical Outcomes Scores (COS) were used to optimize the MMS for biological and clinical relevance and yield a patient Weighted Multiparametric Mutation Score (WMMS) that separates severe from attenuated neurological disease (p = 1.2 e-5). Our study provides understanding for developing quantitative tools to predict clinical severity of neurological disease and a clinical scale that advances monitoring disease progression needed to evaluate new treatments for NKH.

Prediction of prostate cancer Gleason score upgrading from biopsy to radical prostatectomy using pre-biopsy multiparametric MRI PIRADS scoring system

An increase or ‘upgrade’ in Gleason Score (GS) in prostate cancer following Transrectal Ultrasound (TRUS) guided biopsies remains a significant challenge to overcome. to evaluate whether MRI has the potential to narrow the discrepancy of histopathological grades between biopsy and radical prostatectomy, three hundred and thirty men treated consecutively by laparoscopic radical prostatectomy (LRP) between July 2014 and January 2019 with localized prostate cancer were included in this study. Independent radiologists and pathologists assessed the MRI and histopathology of the biopsies and prostatectomy specimens respectively. A multivariate model was constructed using logistic regression analysis to assess the ability of MRI to predict upgrading in biopsy GS in a nomogram. A decision-analysis curve was constructed assessing impact of nomogram using different thresholds for probabilities of upgrading. PIRADS scores were obtained from MRI scans in all the included cases. In a multivariate analysis, the PIRADS v2.0 score significantly improved prediction ability of MRI scans for upgrading of biopsy GS (p = 0.001, 95% CI [0.06–0.034]), which improved the C-index of predictive nomogram significantly (0.90 vs. 0.64, p < 0.05). PIRADS v2.0 score was an independent predictor of postoperative GS upgrading and this should be taken into consideration while offering treatment options to men with localized prostate cancer.

An Utstein-based model score to predict survival to hospital admission: The UB-ROSC score

AimsTo develop and validate a multi-parametric practical score to predict the probability of survival to hospital admission of an out-of-hospital cardiac arrest (OHCA) victim by using Utstein Style-based variables. MethodsAll consecutive OHCA cases occurring from 2015 to 2017 in two regions, Pavia Province (Italy) and Canton Ticino (Switzerland) were included. We used random effect logistic regression to model survival to hospital admission after an OHCA. We computed the model area under the ROC curve (AUC ROC) for discrimination and we performed both internal and external validation by considering all OHCAs occurring in the aforementioned regions in 2018. The Utstein-Based ROSC (UB-ROSC) score was derived by using the coefficients estimated in the regression model. The score value was obtained adding the pertinent score components calculated for each variable. The score was then plotted against the probability of survival to hospital admission. Results1962 OHCAs were included (62% male, mean age 73 ± 16 years). Age, aetiology, location, witnessed OHCA, bystander CPR, EMS arrival time and shockable rhythm were independently associated with survival to hospital admission. The model showed excellent discrimination (AUC 0.83, 95%CI 0.81–0.85) for predicting survival to hospital admission, also at internal cross-validation (AUC 0.82, 95%CI 0.80–0.84). The model maintained good discrimination after external validation by using the 2018 OHCA cohort (AUC 0.77, 95%CI 0.74–0.80). ConclusionsUB-ROSC score is a novel score that predicts the probability of survival to hospital admission of an OHCA victim. UB-ROSC shall help in setting realistic expectations about sustained ROSC achievement during resuscitation manoeuvres.

Multiparametric Echocardiography Scores for the Diagnosis of Cardiac Amyloidosis

ObjectivesThis study aimed to investigate the accuracy of a broad range of echocardiographic variables to develop multiparametric scores to diagnose CA in patients with proven light chain (AL) amyloidosis or those with increased heart wall thickness who had amyloid was suspected. We also aimed to further characterize the structural and functional changes associated with amyloid infiltration. BackgroundCardiac amyloidosis (CA) is a serious but increasingly treatable cause of heart failure. Diagnosis is challenging and frequently unclear at echocardiography, which remains the most often used imaging tool. MethodsWe studied 1,187 consecutive patients evaluated at 3 referral centers for CA and analyzed morphological, functional, and strain-derived echocardiogram parameters with the aim of developing a score-based diagnostic algorithm. Cardiac amyloid burden was quantified by using extracellular volume measurements at cardiac magnetic resonance. ResultsA total of 332 patients were diagnosed with AL amyloidosis and 339 patients with transthyretin CA. Concentric remodeling and strain-derived parameters displayed the best diagnostic performance. A multivariable logistic regression model incorporating relative wall thickness, E wave/e′ wave ratio, longitudinal strain, and tricuspid annular plane systolic excursion had the greatest diagnostic performance in AL amyloidosis (area under the curve: 0.90; 95% confidence interval: 0.87 to 0.92), whereas the addition of septal apical–to–base ratio yielded the best diagnostic accuracy in the increased heart wall thickness group (area under the curve: 0.80; 95% confidence interval: 0.85 to 0.90). ConclusionsSpecific functional and structural parameters characterize different burdens of CA deposition with different diagnostic performances and enable the definition of 2 scores that are sensitive and specific tools with which diagnose or exclude CA.

Integrative modeling of protein-protein interactions with pyDock for the new docking challenges.

The seventh CAPRI edition imposed new challenges to the modeling of protein-protein complexes, such as multimeric oligomerization, protein-peptide, and protein-oligosaccharide interactions. Many of the proposed targets needed the efficient integration of rigid-body docking, template-based modeling, flexible optimization, multiparametric scoring, and experimental restraints. This was especially relevant for the multimolecular assemblies proposed in the CASP12-CAPRI37 and CASP13-CAPRI46 joint rounds, which were described and evaluated elsewhere. Focusing on the purely CAPRI targets of this edition (rounds 38-45), we have participated in all 17 assessed targets (considering heteromeric and homomeric interfaces in T125 as two separate targets) both as predictors and as scorers, by using integrative modeling based on our docking and scoring approaches: pyDock, IRaPPA, and LightDock. In the protein-protein and protein-peptide targets, we have also participated with our webserver (pyDockWeb). On these 17 CAPRI targets, we submitted acceptable models (or better) within our top 10 models for 10 targets as predictors, 13 targets as scorers, and 4 targets as servers. In summary, our participation in this CAPRI edition confirmed the capabilities of pyDock for the scoring of docking models, increasingly used within the context of integrative modeling of protein interactions and multimeric assemblies.