Stratification Algorithm Research Articles

Combined effects of PNPLA3, TM6SF2 and HSD17B13 variants on severity of biopsy-proven non-alcoholic fatty liver disease

ObjectiveSeveral single-nucleotide polymorphisms have been identified to be disadvantageous or protective in regard to disease severity in patients with non-alcoholic fatty liver disease (NAFLD). However, it is unclear, whether including genetic risk factor(s) either alone or combined into risk stratification algorithms for NAFLD actually provides incremental benefit over clinical risk factors.DesignPatients with biopsy-proven NAFLD were genotyped for the PNPLA3-rs738409(minor allele:G), TM6SF2-rs58542926(minor allele:T) and HSD17B13- rs72613567 (minor allele:TA) variants. The NAFLD activity score (NAS) and fibrosis stage (F0–F4) were used to grade and stage all liver biopsy samples. Patients from seven centers throughout Central Europe were considered for the study.Results703 patients were included: NAS ≥ 5:173(24.6%); Fibrosis: F3–4:81(11.5%). PNPLA3 G/G genotype was associated with a NAS ≥ 5(aOR 2.23, p = 0.007) and advanced fibrosis (aOR-3.48, p < 0.001).TM6SF2 T/- was associated with advanced fibrosis (aOR 1.99, p = 0.023). HSD17B13 TA/- was associated with a lower probability of NAS ≥ 5(TA/T: aOR 0.65, p = 0.041, TA/TA: aOR 0.40, p = 0.033). Regarding the predictive capability for NAS ≥ 5, well-known risk factors (age, sex, BMI, diabetes, and ALT; baseline model) had an AUC of 0.758, Addition of PNPLA3(AUC 0.766), HSB17B13(AUC 0.766), and their combination(AUC 0.775), but not of TM6SF2(AUC 0.762), resulted in a higher diagnostic accuracy of the model. Addition of genetic markers for the prediction of advanced fibrosis (baseline model: age, sex, BMI, diabetes: AUC 0.777) resulted in a higher AUC if PNPLA3(AUC 0.789), and TM6SF2(AUC 0.786) but not if HSD17B13(0.777) were added.ConclusionIn biopsy-proven NAFLD, PNPLA3 G/-, TM6SF2 T/- and HSD17B13 TA/- carriage are associated with severity of NAFLD. Incorporating these genetic risk factors into risk stratification models might improve their predictive accuracy for severity of NAFLD and/or advanced fibrosis on liver biopsy.

Intercomparison of Thermal Regime Algorithms in 1‐D Lake Models

AbstractLakes are an important component of the global weather and climate system, but the modeling of their thermal regimes has shown large uncertainties due to the highly diverse lake properties and model configurations. Here, we evaluate the algorithms of four key lake thermal processes including turbulent heat fluxes, wind‐driven mixing, light extinction, and snow density, using a highly diverse lake data set provided by the Inter‐Sectoral Impact Model Intercomparison Project (ISIMIP) 2a lake sector. Algorithm codes are configured and run separately within the same parent model to rule out any interference from factors apart from the algorithms examined. Evaluations are based on both simulation accuracy and recalibration complexity for application to global lakes. For turbulent heat fluxes, the non‐Monin–Obukhov similarity (MOS) based, more simplified algorithms perform better in predicting lake epilimnion temperatures and achieve high convergence in the values of the calibrated parameters. For wind‐driven mixing, a two‐algorithm strategy considering lake shape and season is suggested with the regular mixing algorithm used for spring and earlier summer and the mixing‐enhanced algorithm for summer steady stratification and fall overturn periods. There are no evident differences in the simulated thermocline depths using different light extinction algorithms or the observation. Finally, for lake ice phenology, an optimal algorithm is decided for most northern lakes while the Arctic lakes require separate consideration. Our study provides highly practical guides for improving 1‐D lake models and feasible parameterization strategies to better simulate global lake thermal regimes.

Improved Risk Stratification for Ventricular Arrhythmias and Sudden Death in Patients With Nonischemic Dilated Cardiomyopathy

BackgroundRisk stratification for ventricular arrhythmias (VA) and sudden death in nonischemic dilated cardiomyopathy (DCM) remains suboptimal. ObjectivesThe goal of this study was to provide an improved risk stratification algorithm for VA and sudden death in DCM. MethodsThis was a retrospective cohort study of consecutive patients with DCM who underwent cardiac magnetic resonance with late gadolinium enhancement (LGE) at 2 tertiary referral centers. The combined arrhythmic endpoint included appropriate implantable cardioverter-defibrillator therapies, sustained ventricular tachycardia, resuscitated cardiac arrest, and sudden death. ResultsIn 1,165 patients with a median follow-up of 36 months, LGE was an independent and strong predictor of the arrhythmic endpoint (hazard ratio: 9.7; p < 0.001). This association was consistent across all strata of left ventricular ejection fraction (LVEF). Epicardial LGE, transmural LGE, and combined septal and free-wall LGE were all associated with heightened risk. A simple algorithm combining LGE and 3 LVEF strata (i.e., ≤20%, 21% to 35%, >35%) was significantly superior to LVEF with the 35% cutoff (Harrell’s C statistic: 0.8 vs. 0.69; area under the curve: 0.82 vs. 0.7; p < 0.001) and reclassified the arrhythmic risk of 34% of patients with DCM. LGE-negative patients with LVEF 21% to 35% had low risk (annual event rate 0.7%), whereas those with high-risk LGE distributions and LVEF >35% had significantly higher risk (annual event rate 3%; p = 0.007). ConclusionsIn a large cohort of patients with DCM, LGE was found to be a significant, consistent, and strong predictor of VA or sudden death. Specific high-risk LGE distributions were identified. A new clinical algorithm integrating LGE and LVEF significantly improved the risk stratification for VA and sudden death, with relevant implications for implantable cardioverter-defibrillator allocation.

NSTEMI Guideline During the Covid-19 Pandemia, the Missing Piece What’s New in the 2020 ESC Practice Guidelines?

Abstract According to tradition, every year, at the Congress of the European Society of Cardiology new clinical guidelines, usefull for our daily pratice, are launched. This year a new guideline for the management of non-ST-segment elevation myocardial infarction (NSTEMI) was presented. Substantial resources had been invested to sustain the research efforts in order to improve the diagnosis and therapeutic tools for this disease. In this article we present the main differences between this guideline and the previous one, regarding the utility of the cardiac biomarkers, diagnosis and risk stratification algorithms, and last, but not least, medical and invasive treatment tools.

Venous thromboembolic risk stratification in pediatric trauma: A Pediatric Trauma Society Research Committee multicenter analysis.

Venous thromboembolism (VTE) in injured children is rare, but its consequences are significant. Several risk stratification algorithms for VTE in pediatric trauma exist with little consensus, and all are hindered in development by relying on registry data with known inaccuracies. We performed a multicenter review to evaluate trauma registry fidelity and confirm the effectiveness of one established algorithm across diverse centers. Local trauma registries at 10 institutions were queried for all patients younger than 18 years admitted between 2009 and 2018. Additional chart review was performed on all "VTE" cases and random non-VTE controls to assess registry errors. Corrected data were then applied to our prediction algorithm using 10 real-time variables (Glasgow Coma Scale, age, sex, intensive care unit admission, transfusion, central line placement, lower extremity/pelvic fracture, major surgery) to calculate VTE risk scores. Contingency table classifiers and the area under a receiver operator characteristic curve were calculated. Registries identified 52,524 pediatric trauma patients with 99 episodes of VTE; however, chart review found that 13 cases were misclassified for a corrected total of 86 cases (0.16%). After correction, the algorithm still displayed strong performance in discriminating VTE-fated encounters (sensitivity, 69%; area under the receiver operating characteristic curve, 0.96). Furthermore, despite wide institutional variability in VTE rates (0.04-1.7%), the algorithm maintained a specificity of >91% and a negative predictive value of >99.7% across centers. Chart review also revealed that 54% (n = 45) of VTEs were directly associated with a central line, usually femoral (n = 34, p < 0.001 compared with upper extremity), and that prophylaxis rates were underreported in the registries by about 50%; still, only 19% of the VTE cases had been on prophylaxis before diagnosis. The VTE prediction algorithm performed well when applied retrospectively across 10 diverse pediatric centers using corrected registry data. These findings can advance initiatives for VTE screening/prophylaxis guidance following pediatric trauma and warrant prospective study. Clinical decision rule evaluated in a single population, level III.

A multiparametric ICD algorithm for heart failure risk stratification and management: an analysis in clinical practice

Abstract Funding Acknowledgements Type of funding sources: None. Introduction The HeartLogic algorithm combines multiple implantable cardioverter defibrillator (ICD) sensors to identify patients at risk of heart failure (HF) events. Purpose We sought to evaluate the risk stratification ability of this algorithm in clinical practice. We also analyzed the alert management strategies adopted in the study group and their association with the occurrence of HF events. Methods The HeartLogic feature was activated in 366 ICD and cardiac resynchronization therapy ICD patients at 22 centers. The HeartLogic algorithm automatically calculates a daily HF index and identifies periods IN or OUT of an alert state on the basis of a configurable threshold (in this analysis set to 16). Results The HeartLogic index crossed the threshold value 273 times (0.76 alerts/patient-year) in 150 patients over a median follow-up of 11 months [25-75 percentile: 6-16]. Overall, the time IN the alert state was 11% of the total observation period. Patients experienced 36 HF hospitalizations and 8 patients died of HF (rate: 0.12 events/patient-year) during the observation period. Thirty-five events were associated with the IN alert state (0.92 events/patient-year versus 0.03 events/patient-year in the OUT of alert state). The hazard ratio in the IN/OUT of alert state comparison was (HR: 24.53, 95% CI: 8.55-70.38, p &amp;lt; 0.001), after adjustment for baseline clinical confounders. Alerts followed by clinical actions were associated with a lower rate of HF events (HR: 0.37, 95% CI: 0.14-0.99, p = 0.047). No differences in event rates were observed between in-office and remote alert management. By contrast, verification of HF symptoms during post-alert examination was associated with a higher risk of HF events (HR: 5.23, 95% CI: 1.98-13.83, p &amp;lt; 0.001). Conclusions This multiparametric ICD algorithm identifies patients during periods of significantly increased risk of HF events. The rate of HF events seemed lower when clinical actions were undertaken in response to alerts. Extra in-office visits did not seem to be required in order to effectively manage HeartLogic alerts, while post-alert verification of symptoms seemed useful in order to better stratify patients at risk of HF events.

POS0157-HPR CONSTRUCT VALIDITY OF THE OCTOPUS STRATIFICATION ALGORITHM FOR ALLOCATING PATIENTS WITH KNEE OSTEOARTHRITIS INTO CLINICALLY RELEVANT SUBGROUPS

Background:We recently developed a model of stratified exercise therapy [1], consisting of (i) a stratification algorithm allocating patients with knee osteoarthritis (OA) into clinically relevant subgroups, and (ii) subgroup-specific exercise therapy. More specifically, in our model we distinguish the following subgroups with proposed underlying phenotypes: ‘high muscle strength subgroup’ representing a post-traumatic phenotype, ‘low muscle strength subgroup’ representing an age-induced phenotype and ‘obesity subgroup’ representing a metabolic phenotype.Objectives:In the present study, we aimed to validate the construct of this algorithm, focusing on 3 research questions: (i) are the proportions of patients in each subgroup similar across cohorts?; (ii) are the characteristics of each of the subgroups in line with their proposed underlying phenotypes?; (iii) are the effects of usual exercise therapy in the 3 subgroups in line with the proposed effect sizes?Methods:Data from five studies (four trials and one cross-sectional cohort) were used to validate the construct of our algorithm by 63 a priori formulated hypotheses regarding the research questions.Results:Baseline data from a total of 1,211 patients with knee OA were analyzed for the first and second research question, and follow-up data from 584 patients who were part of an exercise arm within a trial for the third research question. In total, the vast majority (73%) of the hypotheses were confirmed. Regarding our first research question, we found similar proportions in each of the three subgroups across cohorts, especially for three cohorts. Regarding our second research question, subgroup characteristics were almost completely in line with the proposed underlying phenotypes. Regarding our third research question, unexpectedly, usual exercise therapy resulted in similar, moderate to large effect sizes for knee pain and physical function for all three subgroups.Conclusion:This study suggests that our algorithm might be a valid instrument to allocate patients with knee OA into clinically relevant subgroups, as most of our a priori hypotheses could be confirmed. On the other hand, subgroups did not differ substantially in effects of usual exercise therapy, contrary to our expectation. An ongoing trial [1] will assess whether this algorithm accompanied by subgroup-specific exercise therapy improves clinical and economic outcomes.

Inflammation and Cardiovascular Disease: The Future.

Despite considerable advances in reducing the global burden of atherosclerotic cardiovascular disease by targeting conventional risk factors, significant residual risk remains, with low-grade inflammation being one of the strongest risk modifiers. Inflammatory processes within the arterial wall or systemic circulation, which are driven in a large part by modified lipoproteins but subsequently trigger a hypercoagulable state, are a hallmark of atherosclerotic cardiovascular disease and, in particular, its clinical complications. Extending conventional guideline-based clinical risk stratification algorithms by adding biomarkers of inflammation may refine phenotypic screening, improve risk stratification and guide treatment eligibility in cardiovascular disease prevention. The integration of interventions aimed at lowering the inflammatory burden, alone or in combination with aggressive lipid-modifying or even antithrombotic agents, for those at high cardiovascular risk may hold the potential to reduce the still substantial burden of cardiometabolic disease. This review provides perspectives on future clinical research in atherosclerosis addressing the tight interplay between inflammation, lipid metabolism and thrombosis, and its translation into clinical practice.

Network-based identification of key master regulators associated with an immune-silent cancer phenotype.

A cancer immune phenotype characterized by an active T-helper 1 (Th1)/cytotoxic response is associated with responsiveness to immunotherapy and favorable prognosis across different tumors. However, in some cancers, such an intratumoral immune activation does not confer protection from progression or relapse. Defining mechanisms associated with immune evasion is imperative to refine stratification algorithms, to guide treatment decisions and to identify candidates for immune-targeted therapy. Molecular alterations governing mechanisms for immune exclusion are still largely unknown. The availability of large genomic datasets offers an opportunity to ascertain key determinants of differential intratumoral immune response. We follow a network-based protocol to identify transcription regulators (TRs) associated with poor immunologic antitumor activity. We use a consensus of four different pipelines consisting of two state-of-the-art gene regulatory network inference techniques, regularized gradient boosting machines and ARACNE to determine TR regulons, and three separate enrichment techniques, including fast gene set enrichment analysis, gene set variation analysis and virtual inference of protein activity by enriched regulon analysis to identify the most important TRs affecting immunologic antitumor activity. These TRs, referred to as master regulators (MRs), are unique to immune-silent and immune-active tumors, respectively. We validated the MRs coherently associated with the immune-silent phenotype across cancers in The Cancer Genome Atlas and a series of additional datasets in the Prediction of Clinical Outcomes from Genomic Profiles repository. A downstream analysis of MRs specific to the immune-silent phenotype resulted in the identification of several enriched candidate pathways, including NOTCH1, TGF-n}{}beta , Interleukin-1 and TNF-n}{}alpha signaling pathways. TGFB1I1 emerged as one of the main negative immune modulators preventing the favorable effects of a Th1/cytotoxic response.

A quality improvement initiative to reduce venous thromboembolism on a gynecologic oncology service

ObjectiveTo describe and evaluate the effects of implementation of a venous thromboembolism (VTE) prophylaxis quality improvement (QI) initiative on a gynecologic oncology service at a single institution. MethodsPrior to 2018, no consensus gynecologic oncology VTE prophylaxis protocol existed at the authors' academic institution. Published, evidence-based guidelines were reviewed to create a standardized VTE risk stratification algorithm. Interventions to improve perioperative heparin administration and sequential compression device (SCD) compliance as well as provider/patient education efforts were introduced in January 2018. Initial efforts included nursing and patient SCD education, internal dissemination of VTE prophylaxis guidelines, and creation of a VTE ‘dashboard’ to track performance. During a second phase, VTE prophylaxis guidelines were reviewed and further refined, non-compliant operative cases reviewed weekly, and guidelines incorporated into the electronic medical record. Performance was measured using Tableau data software (www.tableau.com) and by separately evaluating adherence to the developed guidelines in three retrospective cancer-enriched surgical cohorts (2016–2017, 2018, 2019). ResultsCompared to the baseline period, we observed a reduction in VTE rate during the 2018–2019 VTE QI implementation period from 2.1% (19/905) to 1.0% (20/2015, p = 0.02) among gynecologic oncology inpatients. In the retrospective cancer-enriched cohorts, adherence to evidence based guidelines improved: 31.0% in 2016–2017, 69.1% in 2018, and 82.4% in 2019 (p < 0.001). There were no significant differences in rates of peri-operative blood transfusion, surgical site infections, hematomas, or vaginal cuff dehiscences. ConclusionsImplementation of a robust VTE prophylaxis QI initiative has resulted in improved VTE prophylaxis guideline adherence and higher rates of pre-operative heparin administration.

АЛГОРИТМ СТРАТИФИКАЦИИ СЕРДЕЧНО-СОСУДИСТОГО РИСКА У МУЖЧИН В ВОЗРАСТЕ 18-29 ЛЕТ С СИНДРОМОМ АРТЕРИАЛЬНОЙ ГИПЕРТЕНЗИИ

Background: Arterial hypertension (AH) is a leading factor of cardiovascular risk (CVR), and stratification of CVR in young patients with AH is an important area of clinical research. Aim: to develop an algorithm for CVR stratification in men aged 18-29 years with AH syndrome (AHS). Materials and methods: 165 men underwent a complete physical examination, which included standard clinical, laboratory and instrumental methods, ergomtry test, analysis of heart rate variability, pulse wave velocity determination. Results: The clinical characteristics and features of the cardiovascular system functioning at rest and during ergometry test have been determined, depending on the nosological form of AHS and the established CVR. The algorithm has been developed based on the assessment of the type of hemodynamic response and determination of the probability of cardiovascular outcomes within 10 years. Conclusion: the proposed algorithm enables to optimize therapeutic, diagnostic and preventive measures in men aged 18-29 years with AHS.

Visual lung damage CT score at hospital admission of COVID-19 patients and 30-day mortality.

ObjectivesChest CT has been widely used to screen and to evaluate the severity of COVID-19 disease in the early stages of infection without severe acute respiratory syndrome, but no prospective data are available to study the relationship between extent of lung damage and short-term mortality. The objective was to evaluate association between standardized simple visual lung damage CT score (vldCTs) at admission, which does not require any software, and 30-day mortality.MethodsIn a single-center prospective cohort of COVID-19 patients included during 4 weeks, the presence and extent of ground glass opacities(GGO), consolidation opacities, or both of them were visually assessed in each of the 5 lung lobes (score from 0 to 4 per lobe depending on the percentage and out of 20 per patient = vldCTs) after the first chest CT performed to detect COVID-19 pneumonia.ResultsAmong 210 confirmed COVID-19 patients, the number of survivors and non-survivors was 162 (77%) and 48 (23%), respectively at 30 days. vldCTs was significantly higher in non-survivors, and the AUC of vldCTs to distinguish survivors and non-survivors was 0.72 (95%CI 0.628–0.807, p < 0.001); the best cut-off vldCTs value was 7. During follow-up, significant differences in discharges and 30-day mortality were observed between patients with vldCTs ≥ 7 versus vldCTs < 7: (98 [85.2%] vs 49 [51.6%]; p < 0.001 and 36 [37.9%] vs 12 [12.4%]; p < 0.001, respectively. The 30-day mortality increased if vldCTs ≥ 7 (HR, 3.16 (1.50–6.43); p = 0.001), independent of age, respiratory rate and oxygen saturation levels, and comorbidities at admission.ConclusionsBy using chest CT in COVID-19 patients, extensive lung damage can be visually assessed with a score related to 30-day mortality independent of conventional risk factors of the disease.Key Points • In non-selected COVID-19 patients included prospectively during 4 weeks, the extent of ground glass opacities(GGO) and consolidation opacities evaluated by a simple visual score was related to 30-day mortality independent of age, respiratory rate, oxygen saturation levels, comorbidities, and hs-troponin I level at admission. • This severity score should be incorporated into risk stratification algorithms and in structured chest CT reports requiring a standardized reading by radiologists in case of COVID-19. Supplementary InformationThe online version contains supplementary material available at 10.1007/s00330-021-07938-2.

Engaging Family Medicine Residents in a Structured Patient Panel Reassignment Process.

The patient panels of graduating residents must be reassigned by the end of residency. This process affects over 1 million patients annually within the specialty of family medicine. The purpose of this project was to implement a structured, year-end reassignment system in a family medicine residency program. Our structured reassignment process took place from December 2017 through June 2020. Panel lists of current, active patients were generated and residents were responsible for reassigning their own panels during a panel reassignment night. We created a tip sheet that addressed patient complexity and continuity, a risk stratification algorithm based on patients' medical and social complexity, and a tool that tracked the number of patients assigned to each future provider. Outcome measures included a resident satisfaction survey administered in 2018-2020 and patient-provider continuity measured with a run chart from December 2016 through August 2020. The resident survey response rate was 75%. Seventy-three percent felt the panel reassignment night was very helpful; 87% thought the reassignment timeline was extremely reasonable, and 87% indicated that they had the necessary information to reassign their patients. Residents also felt confident that their patients were reassigned appropriately (33% extremely confident, 67% somewhat confident). Patient continuity improved with a 13-point run above the median, indicating nonrandom variation. Patient continuity remained above the median until the impact of COVID-19 in April 2020. Our structured reassignment process was received positively by residents and resulted in improved patient continuity.

Beyond the Nuts and Bolts: Tele-Critical Care Patients, Workflows, and Activity Patterns

Background:Tele-critical care (TCC) adoption has been slow since its emergence in the early 2000s. The COVID-19 pandemic has renewed interest in telemedicine and may spur expansion or development of new TCC programs. This narrative addresses the Cleveland Clinic TCC service, (eHospital) to promote exchange of ideas to continually optimize the practice for current and future users.Methods:A descriptive narrative methodology is used in this report.Results:Cleveland Clinic's eHospital was established in 2014 to support nighttime critical care across system hospitals. It encompasses a tiered system of two-way audiovisual communication, telemetry, software platform that integrates the electronic health record, and a proprietary risk stratification algorithm for targeted electronic surveillance. The TCC team includes intensivists, advanced care providers, and registered nurses. Three coverage models evolved depending on onsite clinician availability. More than 133,000 patients have been served by eHospital to date, and span the typical spectrum of critical illness. Along with universal monitoring, ∼18% of patients received active interventions, the most common of which are categorized. Patterns of activity, typical workflows, and adaptations of bedside best practices are also described. Bookending the work shift are sign outs focused on pending critical issues, unstable patients, and those who can be triaged out of the intensive care unit. In between, TCC teams round periodically and interact with bedside teams.Conclusions:TCC adoption has proceeded slowly. Some acceleration is anticipated in a post-COVID-19 pandemic world. Our experience highlights operational practices that can facilitate successful TCC practice.

Validity of the octopus stratification algorithm for allocating patients with knee osteoarthritis into clinically relevant subgroups

Purpose: Knee osteoarthritis (OA) is a heterogeneous disease, therefore it is likely that treatments can be optimized by phenotyping. For this purpose, we developed a model of stratified exercise therapy, consisting of (i) a stratification algorithm aiming to allocate patients with knee OA into clinically relevant subgroups (phenotypes), and (ii) subgroup-specific, stratified exercise therapy interventions. More specifically, in our model we distinguish three subgroups with the following proposed underling phenotypes: the ‘high muscle strength subgroup’ representing a post-traumatic phenotype (e.g., relatively young, history of knee surgery, physically active, mostly males), the ‘low muscle strength subgroup’ representing an age-induced phenotype (e.g., relatively old, physically inactive) and the ‘obesity subgroup’ representing an metabolic phenotype (e.g., obesity and other comorbidities, physically inactive, more severe symptoms).

Barriers and facilitators of a new model of stratified exercise therapy in knee osteoarthritis: results from a qualitative study alongside the octopus-study

Purpose: We recently developed and pilot-tested a model of stratified exercise therapy for patients with knee osteoarthritis (OA), based on previously identified phenotypes. In this model, patients are allocated to three distinct subgroups using a stratification algorithm: ‘high muscle strength subgroup’, ‘low muscle strength subgroup’ or ‘obesity subgroup’. For each subgroup, a tailored, subgroup-specific exercise therapy intervention is provided by a physiotherapist, with an additional dietary intervention from a dietician for the ‘obesity subgroup’.

Serum Levels of Soluble Urokinase Plasminogen Activator Receptor Predict Tumor Response and Outcome to Immune Checkpoint Inhibitor Therapy.

BackgroundImmune checkpoint inhibitors (ICIs) have led to a paradigm shift in cancer therapy, improving outcomes in the treatment of various malignancies. However, not all patients benefit to the same extend from ICI. Reliable tools to predict treatment response and outcome are missing. Soluble urokinase plasminogen activator receptor (suPAR) is a marker of immune activation, whose levels are prognostic in various cancers. We evaluated circulating suPAR levels as a novel predictive and prognostic biomarker in patients receiving ICI therapy for solid tumors.MethodsA total of n = 87 patients receiving ICI therapy for different solid malignancies as well as 32 healthy controls were included into this study. Serum levels of suPAR were measured by ELISA prior to and sequentially at two time points during ICI therapy.ResultsBaseline suPAR serum levels were significantly higher in solid tumor patients compared to healthy controls. Importantly, patients with low suPAR levels both before or during ICI treatment were more likely to have a favorable response to treatment at three and six months, respectively. This finding was confirmed by multivariate binary logistic regression analysis including several clinicopathological parameters. Moreover, circulating suPAR levels before and during therapy were an independent prognostic factor for overall survival (OS). As such, patients with initial suPAR levels above our ideal prognostic cut-off value (4.86 ng/ml) had a median OS of only 160 days compared to 705 days for patients with suPAR levels below this cut-off value. Finally, low baseline suPAR levels identified a subgroup of patients who experienced ICI-related side effects which in turn were associated with favorable treatment response and outcome.ConclusionOur data suggest that measurements of suPAR serum levels are a previously unknown, easily accessible tool to predict individual treatment response and outcome to ICI therapy. Circulating suPAR might therefore be implemented into stratification algorithms to identify the ideal candidates for ICI treatment.

Prognostic role of left ventricular apical aneurysm in hypertrophic cardiomyopathy: A systematic review and meta-analysis

ObjectivesThe aim of this study was to systematically review and quantitatively synthesize existing evidence about the prognostic value of LV apical aneurysm in patients with HCM. BackgroundHypertrophic cardiomyopathy (HCM) represents a common inherited heart disease associated with enormous diversity in morphologic expression and clinical course. With the increasing penetration of advanced high resolution cardiovascular imaging into routine HCM practice, a subset of HCM patients with left ventricular (LV) apical aneurysm have become more widely recognized. MethodsMedline was searched for studies describing the prognostic implication of LV apical aneurysm in patients with HCM. In the main analysis the combined endpoint of major HCM-related outcomes was assessed. Separate analyses for sudden cardiac death (SCD) events and thromboembolic events were also performed. ResultsSix studies comprising of 2382 patients met the inclusion criteria. In the pooled analysis, the presence of LV apical aneurysm was significantly associated with major adverse outcomes (pooled OR: 5.13, 95 CI: 2.85 to 9.23, I2:31%), increased risk of SCD arrhythmic events (pooled OR: 4.67, 95% CI: 2.30 to 9.48, I2: 38%) and thromboembolic events (pooled OR: 6.30, 95% CI: 1.52 to 26.19, I2: 66%). ConclusionsThese data demonstrate that LV apical aneurysm in HCM patients is associated with an increased risk for SCD events and thromboembolism. This finding might encourage the inclusion of LV apical aneurysm into the HCM SCD risk stratification algorithm as a novel risk marker that supports consideration for primary prevention implantable cardioverter defibrillator and anticoagulation for stroke prophylaxis.

Appropriateness of CT pulmonary angiograms according to current diagnostic guidelines based on risk stratification: A retrospective single-center study.

Assessment of appropriateness of CT pulmonary angiograms (CTPA) in patients with suspected pulmonary embolism (PE) is based on risk stratification algorithms such as simplified the Geneva Score (sGS) in combination with D-dimer blood tests. The aim of this study was to validate the diagnostic yield and appropriateness of CTPA examinations in accordance with 2014 European Society of Cardiology (ESC) guidelines. Data from 155 outpatients who underwent CTPA for clinical suspicion of PE were gathered from the radiology information system (RIS) and the clinical information system (CIS). We assessed the presence of sGS items and D-dimer blood test results in RIS from CTPA request forms and from clinical documentation in CIS. Based on the RIS, there were 2.6% patients with high (sGS≥3) and 97.4% patients with low pre-test PE probability (sGS<3), and CTPA indication was formally comprehendible in 75.5% using sGS and D-dimer blood tests. Based on RIS and CIS data in combination, there were 41.3% patients with high and 58.7% patients with low pre-test PE probability, and CTPA indication was formally comprehendible in 88.4%. Using RIS and CIS in combination, PE probability was upgraded from low to high probability in 39.7% compared with RIS alone. In 12.9%, there was a lack of data in RIS for CTPA justification. There is a high diagnostic yield when applying current diagnostic guidelines to our data. There was however a notable discrepancy between the data transferred to the CTPA request forms from the full clinical documentation, therefore not readily available for clinical decision making.

Very High Coronary Artery Calcium (≥1000) and Association With Cardiovascular Disease Events, Non-Cardiovascular Disease Outcomes, and Mortality: Results From MESA.

There are limited data on the unique cardiovascular disease (CVD), non-CVD, and mortality risks of primary prevention individuals with very high coronary artery calcium (CAC; ≥1000), especially compared with rates observed in secondary prevention populations. Our study population consisted of 6814 ethnically diverse individuals 45 to 84 years of age who were free of known CVD from MESA (Multi-Ethnic Study of Atherosclerosis), a prospective, observational, community-based cohort. Mean follow-up time was 13.6±4.4 years. Hazard ratios of CAC ≥1000 were compared with both CAC 0 and CAC 400 to 999 for CVD, non-CVD, and mortality outcomes with the use of Cox proportional hazards regression adjusted for age, sex, and traditional risk factors. Using a sex-adjusted logarithmic model, we calculated event rates in MESA as a function of CAC and compared them with those observed in the placebo group of stable secondary prevention patients in the FOURIER clinical trial (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk). Compared with CAC 400 to 999, those with CAC ≥1000 (n=257) had a greater mean number of coronary vessels with CAC (3.4±0.5), greater total area of CAC (586.5±275.2 mm2), similar CAC density, and more extensive extracoronary calcification. After full adjustment, CAC ≥1000 demonstrated a 4.71- (3.63-6.11), 7.57- (5.50-10.42), 4.86-(3.32-7.11), and 1.94-fold (1.57-2.41) increased risk for all CVD events, all coronary heart disease events, hard coronary heart disease events, and all-cause mortality, respectively, compared with CAC 0 and a 1.65- (1.25-2.16), 1.66- (1.22-2.25), 1.51- (1.03-2.23), and 1.34-fold (1.05-1.71) increased risk compared with CAC 400 to 999. With increasing CAC, hazard ratios increased for all event types, with no apparent upper CAC threshold. CAC ≥1000 was associated with a 1.95- (1.57-2.41) and 1.43-fold (1.12-1.83) increased risk for a first non-CVD event compared with CAC 0 and CAC 400 to 999, respectively. CAC 1000 corresponded to an annualized 3-point major adverse cardiovascular event rate of 3.4 per 100 person-years, similar to that of the total FOURIER population (3.3) and higher than those of the lower-risk FOURIER subgroups. Individuals with very high CAC (≥1000) are a unique population at substantially higher risk for CVD events, non-CVD outcomes, and mortality than those with lower CAC, with 3-point major adverse cardiovascular event rates similar to those of a stable treated secondary prevention population. Future guidelines should consider a less distinct stratification algorithm between primary and secondary prevention patients in guiding aggressive preventive pharmacotherapy.