Risk Stratification In Clinical Practice Research Articles

Circulating amino acid signature features urea cycle alterations associated with coronary artery disease

Coronary artery disease (CAD) remains a leading cause of death worldwide and imposes a substantial socioeconomic burden on healthcare. Improving risk stratification in clinical practice could help to combat this burden. As amino acids are biologically active metabolites whose involvement in CAD remains largely unknown, this study investigated associations between circulating amino acid levels and CAD phenotypes. A high-coverage quantitative liquid chromatography-mass spectrometry approach was applied to acquire the serum amino acids profile of age- and sex-coarsened-matched patients with CAD (n = 46, 66.9 years, 74.7% male) and healthy individuals (n = 120, 67.4 years, 74.7% male) from the COmPLETE study. Multiple linear regressions were performed to investigate associations between amino acid levels and (a) the health status (CAD vs. healthy), (b) the number of affected coronary arteries, or (c) the left ventricular ejection fraction. Regressions were adjusted for age, sex, daily physical activity, sampling, and fasting time. Urea cycle amino acids (ornithine, citrulline, homocitrulline, aspartate, and arginine) were significantly and negatively associated with CAD, the number of affected coronary arteries, and the left ventricular ejection fraction. Lysine, histidine, and the glutamine/glutamate ratio were also significantly and negatively associated with the CAD phenotypes. Overall, patients with CAD displayed lower levels of urea cycle amino acids, highlighting a potential role for urea cycle amino acid profiling in cardiovascular risk stratification.Trial registrationThe study was registered on https://www.clinicaltrials.gov (NCT03986892) on June 5, 2019.

The Abdominal Adiposity Index (A Body Shape Index) Predicts 10-Year All-Cause Mortality in Elderly Active Non-Obese Subjects

Background/Objectives: A Body Shape Index (ABSI), which accounts for waist circumference relative to mass and height, shows a robust association with mortality risk. The present study evaluates the effectiveness of ABSI as a predictor of 10-year all-cause mortality in physically active, non-obese elderly individuals. Methods: This prospective cohort study included 159 volunteers (94 women, aged 60–80 years), recruited in the frame of the “Physical Activity and Nutrition for Great Ageing” (PANGeA) Cross-border Cooperation Program Slovenia–Italy 2007–2013, and followed for 10 years. Baseline characteristics included anthropometric measurements, bioelectrical impedance analysis, and cardiovascular fitness tests (VO2max). Statistical analyses (Cox regression, Kaplan–Meier survival) were conducted to examine the relationship between ABSI and mortality. Results: During the 10-year follow-up, 10 deaths (6.7%) were recorded. ABSI (adjusted for age, smoking, comorbidities, and therapy) was an independent predictor of mortality (hazard ratio = 4.65, p < 0.001). Higher ABSI scores were linked to reduced VO2max (r = −0.190, p = 0.017) and increased systolic blood pressure (r = 0.262, p = 0.001). An ABSI-based predictive model showed strong discriminatory power (AUROC = 0.91). Conclusions: ABSI is a reliable predictor of 10-year mortality in active, non-obese elderly individuals and may improve risk stratification in clinical practice.

Proposal of reference value for day-to-day blood pressure variability based on two outcomes: the Ohasama study.

This study aimed to propose reference values for day-to-day home blood pressure (BP) variability that align with the established hypertension threshold of home BP for the risk of two different outcomes: cardiovascular mortality and cognitive decline. This prospective study was conducted in Ohasama town, Japan, with 1212 participants assessed for cardiovascular mortality risk (age: 64.7 years, 33.6% men). Additionally, 678 participants (age: 62.7 years, 31.1% men) were assessed for cognitive decline risk (Mini-Mental Scale Examination score <24). The within-individual coefficient of variation (CV) of home morning SBP (HSBP) was used as the index of day-to-day BP variability (%). Adjusted Cox regression models were used to estimate the HSBP-CV values, which provided the 10-year outcome risk at an HSBP of 135 mmHg. A total of 114 cardiovascular deaths and 85 events of cognitive decline (mean follow-up:13.9 and 9.6 years, respectively) were identified. HSBP and HSBP-CV were associated with increased risks for both outcomes, with adjusted hazard ratios per 1-standard deviation increase of at least 1.25 for cardiovascular mortality and at least 1.30 for cognitive decline, respectively. The adjusted 10-year risks for cardiovascular mortality and cognitive decline were 1.67 and 8.83%, respectively, for an HSBP of 135 mmHg. These risk values were observed when the HSBP-CV was 8.44% and 8.53%, respectively. The HSBP-CV values indicating the 10-year risk of cardiovascular mortality or cognitive decline at an HSBP of 135 mmHg were consistent, at approximately 8.5%. This reference value will be useful for risk stratification in clinical practice.

Red Blood Cell Distribution Width to Albumin Ratio for Predicting Type I Cardiorenal Syndrome in Patients with Acute Myocardial Infarction: A Retrospective Cohort Study.

Red blood cell distribution width to albumin ratio (RAR) is a novel inflammatory biomarker that independently predicts adverse cardiovascular events and acute kidney injury. This study aimed to assess the predictive value of RAR for cardio-renal syndrome type I (CRS-I) risk in acute myocardial infarction (AMI) patients. This study retrospectively enrolled 551 patients who were definitively diagnosed as AMI between October 2021 and October 2022 at the Affiliated Zhongda Hospital of Southeast University. Participants were divided into two and four groups based on the occurrence of CRS-I and the quartiles of RAR, respectively. Demographic data, laboratory findings, coronary angiography data, and drug utilization were compared among the groups. Logistic regression and receiver operating characteristic curve (ROC) analysis were performed to identify independent risk factors for CRS-I and evaluated the predictive value of RAR for CRS-I. Among the cohort of 551 patients, 103 (18.7%) developed CRS-I. Patients with CRS-I exhibited significantly elevated RAR levels compared to those without the condition, and the incidence of CRS-I correlated with escalating RAR. Univariate and multivariate logistic regression analyses identified RAR as an independent risk factor for CRS-I. ROC curves analysis demonstrated that RAR alone predicted CRS-I with an area under the curve (AUC) of 0.683 (95% CI=0.642-0.741), which was superior to the traditional inflammatory marker C-reactive protein (CRP). Adding the variable RAR to the model for predicting the risk of CRS-I further improved the predictive value of the model from 0.808 (95% CI=0.781-0.834) to 0.825 (95% CI=0.799-0.850). RAR is an independent risk factor for CRS-I, and high levels of RAR are associated with an increased incidence of CRS-I in patients with AMI. RAR emerges as a valuable and readily accessible inflammatory biomarker that may play a pivotal role in risk stratification in clinical practice.

CT texture analysis of vertebrobasilar artery calcification to identify culprit plaques.

The aim of this study was to extract radiomic features from vertebrobasilar artery calcification (VBAC) on head computed tomography (CT) images and investigate its diagnostic performance to identify culprit lesions responsible for acute cerebral infarctions. Patients with intracranial atherosclerotic disease who underwent vessel wall MRI (VW-MRI) and head CT examinations from a single center were retrospectively assessed for VBAC visual and textural analyses. Each calcified plaque was classified by the likelihood of having caused an acute cerebral infarction identified on VW-MRI as culprit or non-culprit. A predefined set of texture features extracted from VBAC segmentation was assessed using the minimum redundancy and maximum relevance method. Five key features were selected to integrate as a radiomic model using logistic regression by the Aikaike Information Criteria. The diagnostic value of the radiomic model was calculated for discriminating culprit lesions over VBAC visual assessments. A total of 1,218 radiomic features were extracted from 39 culprit and 50 non-culprit plaques, respectively. In the VBAC visual assessment, culprit plaques demonstrated more observed presence of multiple calcifications, spotty calcification, and intimal predominant calcification than non-culprit lesions (all p < 0.05). In the VBAC texture analysis, 55 (4.5%) of all extracted features were significantly different between culprit and non-culprit plaques (all p < 0.05). The radiomic model incorporating 5 selected features outperformed multiple calcifications [AUC = 0.81 with 95% confidence interval (CI) of 0.72, 0.90 vs. AUC = 0.61 with 95% CI of 0.49, 0.73; p = 0.001], intimal predominant calcification (AUC = 0.67 with 95% CI of 0.58, 0.76; p = 0.04) and spotty calcification (AUC = 0.62 with 95% CI of 0.52, 0.72; p = 0.005) in the identification of culprit lesions. Culprit plaques in the vertebrobasilar artery exhibit distinct calcification radiomic features compared to non-culprit plaques. CT texture analysis of VBAC has potential value in identifying lesions responsible for acute cerebral infarctions, which may be helpful for stroke risk stratification in clinical practice.

P128 Predicting Persistent Inflammatory Arthritis in patients with Palindromic Rheumatism: Development of Scores for Risk Stratification

Abstract Background/Aims Palindromic rheumatism (PR) is a recognised precursor of rheumatoid arthritis (RA). Up to 50% of PR patients will progress to persistent inflammatory arthritis (PIA) but risk factors for progression remain unclear. Analysis of this large UK prospective PR cohort has been used to develop the first risk stratification tool to predict progression to PIA. Methods The Leeds PR cohort was recruited from regional primary and secondary care referrals. PR was defined as ‘a confirmed history/physical examination consistent with episodes of joint pain and swelling that returned to normal in the absence of an alternative diagnosis’. Clinical, serological and immunogenetic parameters were assessed at baseline and three monthly for the first year, then six monthly. Progression to PIA was defined as clinical synovitis persisting for &amp;gt;3 weeks as confirmed by a rheumatologist. Prediction models were developed by performing a Cox regression analysis, then applying LASSO to select the most important risk variables (using R). Results 161 PR patients were followed between July 2008 and January 2023. 33% (53/161) developed PIA and 91% of progressors met criteria for RA. 90% of patients were DMARD naive at baseline. Female gender, anti-cyclic citrullinated peptide (anti-CCP) positivity, rheumatoid factor (RF) positivity, age&amp;gt;40, smoking (ever) and a typical interval between attacks of &amp;lt; 1 month were all associated with progression (Table 1). Cox regression analysis showed female gender (HR 2.2CI1.1-4.7, p = 0.03) and anti-CCP&amp;gt;3x upper limit of normal (HR 5.9, CI 2.0-17.4, p = 0.002) were strongly associated with progression. 'Ever’ and 'Two-year’ prediction models were created to calculate risk of developing PIA (Table 1). Patients could be stratified into high, moderate and low risk groups, with progression rates of 53% (34/64), 25% (19/77) and 0% respectively in the ‘Ever’ model and 37% (27/ 73), 16% (11/69) and 0% respectively in the ‘Two-year’ model. Conclusion In patients with PR, female gender, positive anti-CCP, positive RF, age &amp;gt;40, smoking and a typical interval between attacks of &amp;lt; 1 month were predictive of progression to PIA. Combining these factors allows feasible risk stratification in clinical practice. High and moderate risk groups should be monitored in secondary care and considered for interventional trials. Disclosure R. Chowdhury: None. F. Shuweihdi: None. N. Sidhu: None. L. Duquenne: None. L. Garcia-Montoya: None. J. Nam: None. A. Di Matteo: None. K. Harnden: None. D. Sahin-Eroglu: None. P. Emery: Consultancies; BMS, AbbVie, MSD, Pfizer, Novartis, and Roche. Honoraria; Abbvie, Gilead, Lilly, Novartis. Grants/research support; AbbVie, BMS, Lilly, Samsung. K. Mankia: Honoraria; Abbvie, Lilly, UCB, Galapagos. Grants/research support; Gilead, Lilly.

Cystatin C Use for CKD Detection in the Veterans Health Administration System: A Qualitative Study of Barriers and Facilitators

Rationale & ObjectiveThe measurement of cystatin C has been recommended to enhance chronic kidney disease (CKD) detection and risk stratification in clinical practice. This study gathered insights into the perceptions and experiences of clinical staff regarding the use of cystatin C in CKD detection within the Veterans Health Administration (VHA) System. Study DesignA qualitative approach was employed to explore barriers and facilitators of clinical staff regarding the use of cystatin C in CKD detection within the VHA system. The Organizational Theory of Implementation Effectiveness informed the development of a semi-structured interview guide. Setting & ParticipantsHealthcare providers, nurses, and clinical pharmacists from the VHA systems in San Francisco, San Diego, and Houston were interviewed between October 2021 and May 2022. Analytical ApproachParticipant responses from individual interviews were analyzed by a multidisciplinary team using rapid qualitative analysis methods. ResultsFourteen in-depth interviews were conducted across the three VHA systems. Ten of eleven providers worked in primary care. Five key barriers to using cystatin C for CKD detection were identified. These included: lack of patient awareness of CKD testing, lack of provider awareness about cystatin C, knowledge barriers about cystatin C testing, unclear roles and ownership of CKD detection, and lack of clinic support to enhance CKD detection. Suggested interventions to overcome these barriers included educational and training programs, improved clinic workflows, and electronic health record aids to support CKD detection and use of cystatin C. LimitationsThe results may not be generalizable to other healthcare systems outside the VHA. ConclusionsFindings indicate a need for targeted interventions such as educational and training programs, improved clinical workflows, and electronic health record aids to address barriers limiting the use of cystatin C in clinical practice for enhanced CKD detection.

Integrative models of histopathological images and multi-omics data predict prognosis in endometrial carcinoma.

This study aimed to predict the molecular features of endometrial carcinoma (EC) and the overall survival (OS) of EC patients using histopathological imaging. The patients from The Cancer Genome Atlas (TCGA) were separated into the training set (n = 215) and test set (n = 214) in proportion of 1:1. By analyzing quantitative histological image features and setting up random forest model verified by cross-validation, we constructed prognostic models for OS. The model performance is evaluated with the time-dependent receiver operating characteristics (AUC) over the test set. Prognostic models based on histopathological imaging features (HIF) predicted OS in the test set (5-year AUC = 0.803). The performance of combining histopathology and omics transcends that of genomics, transcriptomics, or proteomics alone. Additionally, multi-dimensional omics data, including HIF, genomics, transcriptomics, and proteomics, attained the largest AUCs of 0.866, 0.869, and 0.856 at years 1, 3, and 5, respectively, showcasing the highest discrepancy in survival (HR = 18.347, 95% CI [11.09-25.65], p < 0.001). The results of this experiment indicated that the complementary features of HIF could improve the prognostic performance of EC patients. Moreover, the integration of HIF and multi-dimensional omics data might ameliorate survival prediction and risk stratification in clinical practice.

Multiple sleep-wake disturbances after stroke predict an increased risk of cardio-cerebrovascular events or death: A prospective cohort study.

Contradictory evidence on the impact of single sleep-wake-disturbances (SWD), such as sleep-disorderd breating (SDB) or insomnia, in patients with stroke, on the risk of subsequent cardio- and cerebrovascular events (CCE) and death, exists. Very recent studies in the general population suggest that the presence of multiple SWD increases cardio-cerebrovascular risk. Hence, the aim of this study was to asssess whether a novel score capturing the burden of multiple SWD, a so called "sleep burden index", is predictive for subsequent CCE including death in a prospectively followed cohort of stroke patients. Patients with acute ischemic stroke or transient ischemic attack (TIA) were prospectively recruited. Four SWD were analyzed: (i) SDB with respirography; (ii) insomnia (defined using the insomnia severity index [ISI]); (iii) restless legs syndrome (RLS; defined using the International RLS Study Group rating scale); and (iv) self-estimated sleep duration at 1 and 3 months. A "sleep burden index", calculated using the mean of z-transformed values from assessments of these four SWD, was created. The occurrence of CCE was recorded over a mean ± standard deviation (SD) follow-up of 3.2 ± 0.3 years. We assessed 437 patients (87% ischemic stroke, 13% TIA, 64% males) with a mean ± SD age of 65.1 ± 13.0 years. SDB (respiratory event index ≥ 5/h) was present in 66.2% of these patients. Insomnia (ISI ≥ 10), RLS and extreme sleep duration affected 26.2%, 6.4% and 13.7% of the patients 3 months post-stroke. Seventy out of the 437 patients (16%) had at least one CCE during the follow-up. The sleep burden index was associated with a higher risk for subsequent CCE, including death (odds ratio 1.80 per index unit, 95% confidence interval 1.19-2.72; p=0.0056). The presence of multiple SWDs constitutes a risk for subsequent CCE (including death) within the first 3 years following stroke. Larger systematic studies should assess the utility of the sleep burden index for patients' risk stratification in clinical practice.

Frailty and affective disorders throughout adult life: A 5-year follow-up of the Lifelines Cohort Study.

Frailty is an important concept for risk stratification in clinical practice, but it is hardly acknowledged at all in mental healthcare settings. This paper aims to assess the impact of frailty on the course of depression and anxiety, and the impact of these affective disorders on the course of frailty. Lifelines, a prospective population-based cohort study, evaluated 167,729 people living in the northern Netherlands. Frailty was based on the deficit accumulation model, which resulted in a 60-item frailty index (FI) at baseline and a 35-item FI at baseline and 5-year follow-up. Current depressive and anxiety disorders were assessed with the Mini International Neuropsychiatric Interview according to DSM-IV criteria. Bidirectional associations between frailty and affective disorders were investigated using separate multivariable regression analyses in younger (<60 years) and older adults (≥60 years). The FI was associated with the onset of a depressive disorder (younger adults: odds ratio [OR]=1.12; 95% confidence interval [CI] 1.11-1.13; older adults: OR=1.13; 95% CI 1.09-1.16) as well as any anxiety disorder (younger adults: OR=1.10; 95% CI 1.09-1.10; older adults: OR=1.07; 95% CI 1.04-1.09). The other way around, depressive disorder and anxiety disorders were associated with an accelerated increase of frailty over time (depressive disorder: younger adults: beta [β]=0.03, p < 0.001; older adults: β=0.04, p < 0.001; and any anxiety disorder: younger adults: β=0.02, p < 0.001; older adults: β=0.01, p < 0.142), although the effect of anxiety disorders was less equivocal among older adults. Affective disorders are reciprocally related to frailty. Results with respect to the impact of anxiety disorders on frailty suggest most impact at lower levels of frailty. Our results might imply that interventions to slow biological aging should be broadened towards younger and middle-aged people as well as non-frail older patients. To develop targeted treatment, future clinical and epidemiologic studies on the underlying pathways of this bidirectional association are needed.

A nomogram predicting 30-day mortality in patients undergoing percutaneous coronary intervention.

Background and aimsEarly detection of mortality after percutaneous coronary intervention (PCI) is crucial, whereas most risk prediction models are based on outdated cohorts before the year 2000. This study aimed to establish a nomogram predicting 30-day mortality after PCI.Materials and methodsIn total, 10,444 patients undergoing PCI in National Center for Cardiovascular Diseases in China were enrolled to establish a nomogram to predict 30-day mortality after PCI. The nomogram was generated by incorporating parameters selected by logistic regression with the stepwise backward method.ResultsFive features were selected to build the nomogram, including age, male sex, cardiac dysfunction, STEMI, and TIMI 0–2 after PCI. The performance of the nomogram was evaluated, and the area under the curves (AUC) was 0.881 (95% CI: 0.8–0.961). Our nomogram exhibited better performance than a previous risk model (AUC = 0.7, 95% CI: 0.586–0.813) established by Brener et al. The survival curve successfully stratified the patients above and below the median score of 4.ConclusionA novel nomogram for predicting 30-day mortality was established in unselected patients undergoing PCI, which may help risk stratification in clinical practice.

Different Models to Predict the Risk of Recurrent Hepatocellular Carcinoma in the Setting of Liver Transplantation.

Simple SummaryLiver transplantation is considered the first-choice curative therapy for hepatocellular carcinoma in the early phase of the disease, when surgical resection is not possible. Even when implementing restrictive criteria to select patients for liver transplantation, there is a risk of recurrence in the transplanted liver, influencing the long-term outcome and prognosis. As it is challenging to predict the individual risk of recurrence, there is a need for validated and predictive scoring systems to use to stratify patients before and/or after liver transplantation. Most of the proposed scorings include biological markers for tumour behavior, in addition to the number and size of tumoral nodules. In this review, we discuss different published models to assess the risk of recurrent hepatocellular carcinoma after transplantation. Our aim is to refine clinical decisions about prioritization and listing for liver transplantation, to better inform patients and provide an appropriate surveillance strategy to influence their prognosis.Liver transplantation is the preferred therapeutic option for non-resectable hepatocellular carcinoma in early-stage disease. Taking into account the limited number of donor organs, liver transplantation is restricted to candidates with long-term outcomes comparable to benign indications on the waiting list. Introducing the morphometric Milan criteria as the gold standard for transplant eligibility reduced the recurrence rate. Even with strict patient selection, there is a risk of recurrence of between 8 and 20% in the transplanted liver, and this is of even greater importance when using more expanded criteria and downstaging protocols. Currently, it remains challenging to predict the risk of recurrence and the related prognosis for individual patients. In this review, the recurrence-risk-assessment scores proposed in the literature are discussed. Currently there is no consensus on the optimal model or the implications of risk stratification in clinical practice. The most recent scorings include additional biological markers for tumour behavior, such as alfa-foetoprotein, and the response to locoregional therapies, in addition to the number and diameter of tumoral nodules. The refinement of the prediction of recurrence is important to better inform patients, guide decisions about prioritization and listing and implement individualized surveillance strategies. In the future, this might also provide indications for tailored immunosuppressive therapy or inclusion in trials for adjuvant treatment.

Left atrial contractile strain predicts recurrence of atrial tachyarrhythmia after catheter ablation

BackgroundDespite improvement in treatment strategies of atrial fibrillation (AF), a considerable number of patients still experience recurrence of atrial tachyarrhythmia (ATA) following catheter ablation (CA). This study aimed to investigate the prognostic value of left atrial (LA) deformation analysis in a large group of patients undergoing CA for AF. MethodsThis study included 678 patients with AF. Echocardiography including two-dimensional speckle tracking echocardiography (2DSTE) was performed in all patients prior to CA. Logistic regression analysis was used to assess the association between ATA recurrence and LA strain during reservoir phase (LASr), LA strain during contraction phase (LASct), and LA strain during conduit phase (LAScd). ResultsDuring one-year follow-up, 274 (40%) experienced ATA recurrence. Median age of the included study population was 63.2 years (IQR: 55.5, 69.5) and 485 (72%) were male. Patients with recurrence had lower LASr (22.6% vs. 25.1%, p = 0.001) and LASct (10.7% vs. 12.4%, p < 0.001). No difference in LAScd was observed. After adjusting for potential clinical and echocardiographic confounders LASr (OR = 1.04, CI95% [1.01; 1.07], p = 0.015, per 1% decrease) and LASct (OR = 1.06, CI95% [1.02; 1.11], p = 0.007, per 1% decrease) remained independent predictors of recurrence. However, in patients with a normal-sized LA (LA volume index<34 mL/m2), only LASct remained an independent predictor of recurrence (OR = 1.07, CI95% [1.01; 1.12], p = 0.012, per 1% decrease). ConclusionIn patients undergoing CA for AF, LA deformation analysis by 2DSTE could be of use in risk stratification in clinical practice regarding ATA recurrence, even in patients with a normal-sized LA.

Frequency of Transition of patients with NYHA class III / IV to NYHA class I / II / III of stage C and D Heart Failure with Pharmacotherapy in a Tertiary Level Hospital

Background: Heart failure (HF) is one of the most important health problems in terms of prevalence, morbidity, mortality and health service use. It affects around 2 to 3 % of the population. NYHA class can be used for the prioritization, triage and tailoring the HF management which is the foundation for the selection of therapies. The patient with higher NYHA class may need Mechanical Circulatory Support therapy or palliative care or hospice care. The identification of the patients with lower NYHA class helps to tailor vigorous drug therapy and close follow up program, the prognosis of these low risk patients maybe further improved. It is a simple tool for risk stratification in clinical practice.&#x0D; Objective: The principal objective of this study was to determine frequency of transition of NYHA class III / IV to NYHA class I / II / III of stage C &amp; D HF with drugs in a tertiary level hospital.&#x0D; Methods: This was a crosssectional study. A total of 45 patients with stage C and D HF were enrolled in the study by consecutive sampling from October 2019 to September 2020. Detailed history including NYHA functional class of stage C and D HF, physical examination, relevant investigations and Echocardiography were done in all the subjects. The subjects were treated accordingly. The treatment response was assessed again with NYHA functional class on discharge.&#x0D; Result: Patients had mean age of 62 &amp;60 and 54 &amp; 54 years for NYHA class III &amp; IV of stage C and D HF. Majority of the patients were male. Primary cause of HF for both stage were IHD followed by DCM and valvular heart disease. The clinical presentation of stage C &amp; D HF was improved significantly on discharge. Haematological, biochemical, radiological and echocardiographic findings of NYHA class IV of stage C &amp; D HF was more worst.&#x0D; Conclusion: There is statistically significant transition of NYHA class III of stage C and D HF to lower NYHA class but there is no statistically significant transition of NYHA class IV of stage C and D HF with pharmacotherapy in a tertiary level hospital. Higher NYHA class is associated with poor outcome of stage C &amp; D HF patients.&#x0D; University Heart Journal 2022; 18(1): 14-21

Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes.

Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD), calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers, and investigates its performance according to the age and pharmacological treatment. This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) used three risk scores: a GRS, a validated clinical score, and their combined score. Hazard ratios (HR) were calculated with Cox regression, and model performances were compared with the Harrell C-index (C-index). A HR of 6.7 for CAD was observed between the highest and the lowest 5th percentile of the GRS (P = 1.8 × 10-6). The performance of GRS (C-index = 0.562) was similar to HbA1c (C-index = 0.563, P = 0.96 for difference), HDL (C-index = 0.571, P = 0.6), and total cholesterol (C-index = 0.594, P = 0.1). The GRS was not correlated with the clinical score (r = -0.013, P = 0.5). The combined score outperformed the clinical score (C-index = 0.813 vs. C-index = 0.820, P = 0.003). The GRS performed better in individuals below the median age (38.6 years) compared with those above (C-index = 0.637 vs. C-index = 0.546). A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD, with a predictive power comparable to that of HbA1c and HDL and total cholesterol, and when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD.

A prediction model for hospital mortality in patients with severe community-acquired pneumonia and chronic obstructive pulmonary disease

BackgroundNo personalized prediction model or standardized algorithm exists to identify those at high risk of death among severe community-acquired pneumonia (SCAP) patients with chronic obstructive pulmonary disease (COPD). The aim of this study was to investigate the risk factors and to develop a useful nomogram for prediction of mortality in those patients.MethodsWe performed a retrospective, observational, cohort study in the intensive care unit (ICU) of West China Hospital, Sichuan University with all consecutive SCAP patients with COPD between December 2011 and December 2018. The clinical data within 24 h of admission to ICU were collected. The primary outcome was hospital mortality. We divided the patients into training and testing cohorts (70% versus 30%) randomly. In the training cohort, univariate and multivariate logistic regression analysis were used to identify independent risk factors applied to develop a nomogram. The prediction model was assessed in both training and testing cohorts.ResultsFinally, 873 SCAP patients with COPD were included, among which the hospital mortality was 41.4%. In training cohort, the independent risk factors for hospital mortality were increased age, diabetes, chronic renal diseases, decreased systolic blood pressure (SBP), and elevated fibrinogen, interleukin 6 (IL-6) and blood urea nitrogen (BUN). The C index was 0.840 (95% CI 0.809–0.872) in training cohort and 0.830 (95% CI 0.781–0.878) in testing cohort. Furthermore, the time-dependent AUC, calibration plots, DCA and clinical impact curves indicated the model had good predictive performance. Significant association of risk stratification based on nomogram with mortality was also found (P for trend < 0.001). The restricted cubic splines suggested that estimated associations between these predictors and hospital mortality were all linear relationships.ConclusionWe developed a prediction model including seven risk factors for hospital mortality in patients with SCAP and COPD. It can be used for early risk stratification in clinical practice after more external validation.

Abstract 12869: Left Atrial Contractile Strain Predicts Recurrence of Atrial Tachyarrhythmia After Catheter Ablation

Background: Despite improvement in treatment strategies of atrial fibrillation (AF), a considerable number of patients still experience recurrence of atrial tachyarrhythmia (ATA) following catheter ablation (CA). We hypothesized that baseline myocardial impairment of the left atrium (LA) is useful in identifying patients at high risk of ATA recurrence. Methods: This retrospective study included 921 patients with AF who underwent CA. Echocardiography including two-dimensional speckle tracking echocardiography (2DSTE) was performed in all patients prior to CA. Logistic regression analysis was used to assess the association between ATA recurrence and peak atrial longitudinal strain (PALS), peak atrial contraction strain (PACS), and left atrial conduit strain (LACS). Results: During one-year follow-up, 375 (41%) experienced ATA recurrence. The median age of the included study population was 63.5 years (IQR: 55.6, 69.6) and 665 (72%) were male. Patients with recurrence had lower PALS (19.6% vs. 22.0%, p=0.004) and PACS (10.7% vs. 12.4%, p &lt; 0.001). No difference in LACS was observed. After adjusting for potential clinical and echocardiographic confounders PALS (OR = 1.04, CI95% [1.01; 1.06], p = 0.011, per 1% decrease) and PACS (OR = 1.06, CI95% [1.02; 1.11], p = 0.007, per 1% decrease) remained independent predictors of recurrence. However, in patients with a normal-sized LA (LA volume index &lt; 34 mL/m 2 ), only PACS remained an independent predictor of recurrence (OR = 1.06, CI95% [1.01; 1.12], p = 0.013, per 1% decrease). Figure 1 displays the increasing risk of recurrence with decreasing PALS, PACS, and LACS. Conclusion: In patients undergoing CA for AF, LA deformation analysis by 2DSTE could be of use in risk stratification in clinical practice regarding ATA recurrence, even in patients with a normal-sized LA.

ACCELERATED TRACER WASHOUT IN REGIONS OF SYMPATHETIC DENERVATION IN HEART FAILURE PATIENTS WITH ISCHEMIC CARDIOMYOPATHY USING FLUBROBENGUANE POSITRON EMISSION TOMOGRAPHY IMAGING

<h3>BACKGROUND</h3> Sympathetic denervation has been shown to predict the risk of sudden cardiac death in ischemic cardiomyopathy (ICM) heart failure patients with implanted cardiac defibrillators. The previous PAREPET trial (JACC 2014;63(2):141) used the PET tracer hydroxyephedrine (HED) which is a false neurotransmitter analog of norepinephrine. This established tracer is labeled with the short-lived isotope C-11, which limits its widespread utility for risk stratification in clinical practice. The purpose of this study was to evaluate the ability of a new F-18-labeled PET tracer LMI-1195 (flubrobenguane) to measure regional denervation (tracer uptake) as well as sympathetic tone (washout rate) in ICM patients with heart failure. <h3>METHODS AND RESULTS</h3> A subset of patients (N=7) in the LMI-1195 vs HED validation trial underwent early (30 min) and late (4 hours) PET-CT imaging following injection of 3 MBq/kg of flubrobenguane. Five subjects were ICM patients and 2 were healthy normal controls. Regional tracer distribution was quantified on the early and late uptake images using the clinical 4DM-PET analysis program (Ann Arbor, MI). Percent washout rate was measured as (early-late) / early uptake (x100%) using a 9-segment model of left ventricle. In normal controls, there was minimal washout over the 4-hour interval between early and late images (4 +/- 4%). Tracer washout was significantly accelerated (P < 0.0001) in both ischemic regions and in remote (perfused) regions in the ICM patients (21 +/- 10% and 17% +/- 9% respectively), suggesting increased sympathetic tone in the whole-LV of these heart failure patients, with regionally higher tone in the ischemic zone. <h3>CONCLUSION</h3> Initial pilot studies evaluating the novel PET tracer [18F]flubrobenguane as a marker of presynaptic neuronal function in humans with and without HF was performed, showing accelerated washout in regions of sympathetic denervation in patients with ischemic cardiomyopathy. If confirmed in larger studies, this would represent a novel and non-invasive method to quantify cardiac sympathetic activity in-vivo. This new imaging method may be helpful in the future to identify cardiac regions associated with elevated arrhythmogenic risk.

Time point-dependent concordance and prognostic significance of flow cytometry and real time quantitative PCR for measurable/minimal residual disease detection in acute myeloid leukemia with t(8;21)(q22;q22.1).

Flow cytometry (FCM) and PCR are reliable methods for assessing minimal residual disease (MRD) in acute myeloid leukemia with t(8;21)(q22;q22.1). The aim of this study was to analyze the concordant rate of these two methods and their prognostic significance. PCR and FCM were simultaneously used for MRD analysis at four different time points on 450 BM samples from 124 patients with AML with t(8;21)(q22;q22.1). The four monitoring time points included post-induction (first), after the first consolidation (second) and the second consolidation (third), and at the end of chemotherapy or before Allo/Auto stem cell transplantation (fourth). The concordant rates of the two methods were 33.06%, 25.81%, 49.59%, and 75.31%, respectively, and the main discordant cases were FCM-/PCR+ cases. At all monitoring time points, the MRD level ≥ 10-4 by FCM indicated a poor 3-year Relapse-Free Survival (RFS) (p < 0.001). More than 2-log MRD reduction by PCR after induction and more than 3-log reduction by PCR after the first consolidation remained the significant predictors of better RFS (p < 0.001). After the second consolidation, the negative MRD by PCR (<10-5) was also associated with improved RFS (p=0.002). A > 1-log increase in PCR can effectively predict recurrence after molecular remission (p < 0.001). In the multivariate analysis, MRD≥0.01% by. FCM and less than 2-log MRD reduction by PCR after induction remained the significant predictors of poor RFS (p < 0.05). FCM+ always indicates a poor prognosis. Sequential monitoring by PCR is of significance for evaluating prognosis. Our findings suggest a complementary role of two analyses in optimizing risk stratification in clinical practice.

Encephalopathy at admission predicts adverse outcomes in patients with SARS-CoV-2 infection.

AimsTo determine if neurologic symptoms at admission can predict adverse outcomes in patients with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2).MethodsElectronic medical records of 1053 consecutively hospitalized patients with laboratory‐confirmed infection of SARS‐CoV‐2 from one large medical center in the USA were retrospectively analyzed. Univariable and multivariable Cox regression analyses were performed with the calculation of areas under the curve (AUC) and concordance index (C‐index). Patients were stratified into subgroups based on the presence of encephalopathy and its severity using survival statistics. In sensitivity analyses, patients with mild/moderate and severe encephalopathy (defined as coma) were separately considered.ResultsOf 1053 patients (mean age 52.4 years, 48.0% men [n = 505]), 35.1% (n = 370) had neurologic manifestations at admission, including 10.3% (n = 108) with encephalopathy. Encephalopathy was an independent predictor for death (hazard ratio [HR] 2.617, 95% confidence interval [CI] 1.481–4.625) in multivariable Cox regression. The addition of encephalopathy to multivariable models comprising other predictors for adverse outcomes increased AUCs (mortality: 0.84–0.86, ventilation/ intensive care unit [ICU]: 0.76–0.78) and C‐index (mortality: 0.78 to 0.81, ventilation/ICU: 0.85–0.86). In sensitivity analyses, risk stratification survival curves for mortality and ventilation/ICU based on severe encephalopathy (n = 15) versus mild/moderate encephalopathy (n = 93) versus no encephalopathy (n = 945) at admission were discriminative (p < 0.001).ConclusionsEncephalopathy at admission predicts later progression to death in SARS‐CoV‐2 infection, which may have important implications for risk stratification in clinical practice.