Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) was a cause of concern in the healthcare system and increased the need for disease severity indicators. However, they still vary in use to evaluate in-hospital outcomes and severity. The National Early Warning Score (NEWS) is routinely used to evaluate patient health status at the hospital. Further research is needed to ensure if NEWS can be a good instrument for an overall health status assessment with or without additional information like laboratory tests, intensive care needs, and history of chronic diseases. OBJECTIVE: To evaluate if NEWS can be an indicator to measure COVID-19 patient status in-hospital. METHODS: We used the fully anonymized Electronic Health Records (EHR) characterizing patients admitted to the hospital with COVID-19. Data was obtained from Vilnius University Hospital Santaros Klinikos EHR system (SANTA-HIS) from 01-03-2020 to 31-12-2022. The study sample included 3875 patients. We created several statistical and machine learning models for discrimination between in-hospital death/discharge for evaluation NEWS as a disease severity measure for COVID-19 patients. In these models, two variable sets were considered: median NEWS and its combination with clinical parameters and medians of laboratory test results. Assessment of models' performance was based on the scoring metrics: accuracy, sensitivity, specificity, area under the ROC curve (AUC), and F1-score. RESULTS: Our analysis revealed that NEWS predictive ability for describing patient health status during the stay in the hospital can be increased by adding the patient's age at hospitalization, gender, clinical and laboratory variables (0.853 sensitivity, 0.992 specificity and F1-score - 0.859) in comparison with single NEWS (0.603, 0.995, 0.719, respectively). A comparison of different models showed that stepwise logistic regression was the best method for in-hospital mortality classification. Our findings suggest employing models like ours for advisory routine usage. CONCLUSION: Our model demonstrated incremental value for COVID-19 patient's status evaluation.

Exploring myocardial fibrosis in severe aortic stenosis: echo, CMR and histology data from FIB-AS study.

Myocardial fibrosis in aortic stenosis is associated with worse survival following aortic valve replacement. We assessed myocardial fibrosis in severe AS patients, integrating echocardiographic, cardiovascular magnetic resonance (CMR) and histological data. A total of 83 severe AS patients (age 66.4 ± 8.3, 42% male) who were scheduled for surgical AVR underwent CMR with late gadolinium enhancement and T1 mapping and global longitudinal strain analysis. Collagen volume fraction was measured in myocardial biopsies (71) that were sampled at the time of AVR. Results. CVF correlated with imaging and serum biomarkers of LV systolic dysfunction and left side chamber enlargement and was higher in the sub-endocardium compared with midmyocardium (p<0.001). CVF median values were higher in LGE-positive versus LGE-negative patients [28.7% (19-33) vs 20.7% (15-30), respectively, p=0.040]. GLS was associated with invasively (CVF; r=-0.303, p=0.013) and non-invasively (native T1; r=-0.321, p<0.05) measured myocardial fibrosis. GLS and native T1 correlated with parameters of adverse LV remodelling, systolic and diastolic dysfunction and serum biomarkers of heart failure and myocardial injury. Conclusion. Our data highlight the role of myocardial fibrosis in adverse cardiac remodelling in AS. GLS has potential as a surrogate marker of myocardial fibrosis, and high native T1 and low GLS values differentiated patients with more advanced cardiac remodelling.

Prognostic value of myocardial fibrosis in severe aortic stenosis: study protocol for a prospective observational multi-center study (FIB-AS).

BACKGROUND: Adverse cardiac remodeling with a myocardial fibrosis as a key pathophysiologic component may be associated to worse survival in aortic stenosis (AS) patients. Therefore, with the application of advanced cardiac imaging we aim to investigate left ventricular myocardial fibrosis in severe AS patients undergoing aortic valve replacement (AVR) and determine its impact with post-intervention clinical outcomes. METHODS: In a prospective, observational, cohort study patients with severe AS scheduled either for surgical or transcatheter AVR will be recruited from two tertiary heart centers in Denmark and Lithuania. All patients will receive standard of care in accordance with the current guidelines and will undergo additional imaging testing before and after AVR: echocardiography with deformation analysis and cardiovascular magnetic resonance (CMR) with T1 parametric mapping. Those undergoing surgical AVR will also have a myocardial biopsy sampled at the time of a surgery for histological validation. Patients will be recruited over a 2-year period and followed up to 2 years to ascertain clinical outcomes. Follow-up CMR will be performed 12 months following AVR, and echocardiography with deformation analysis will be performed 3, 12, and 24 months following AVR. The study primary outcome is a composite of all-cause mortality and major adverse cardiovascular events. DISCUSSION: Despite continuous effort of research community there is still a lack of early predictors of left ventricular decompensation in AS, which could improve patient risk stratification and guide the optimal timing for aortic valve intervention, before irreversible left ventricular damage occurs. Advanced cardiac imaging and CMR derived markers of diffuse myocardial fibrosis could be utilized for this purpose. FIB-AS study is intended to invasively and non-invasively assess diffuse myocardial fibrosis in AS patients and investigate its prognostic significance in post-interventional outcomes. The results of the study will expand the current knowledge of cardiac remodeling in AS and will bring additional data on myocardial fibrosis and its clinical implications following AVR. ETHICS/DISSEMINATION: The study has full ethical approval and is actively recruiting patients. The results will be disseminated through scientific journals and conference presentations. TRIAL REGISTRATION: ClinicalTrials.govNCT03585933. Registered on 02 July 2018.

Correction to: Prevalence and prognostic value of late gadolinium enhancement on CMR in aortic stenosis: meta-analysis.

The original version of this article, published on 12 August 2019, unfortunately contained a mistake. The funding note was incorrect; the correct funding note is given below.

Prevalence and prognostic value of late gadolinium enhancement on CMR in aortic stenosis: meta-analysis.

OBJECTIVES: The aim of this study was to investigate the prevalence and prognostic value of late gadolinium enhancement (LGE), as assessed by cardiovascular magnetic resonance (CMR) imaging, in patients with aortic stenosis. METHODS AND RESULTS: A systematic search of PubMed and EMBASE was performed, and observational cohort studies that analysed the prevalence of LGE and its relation to clinical outcomes in patients with aortic stenosis were included. Odds ratios were used to measure an effect of the presence of LGE on both all-cause and cardiovascular mortality. Nineteen studies were retrieved, accounting for 2032 patients (mean age 69.8 years, mean follow-up 2.8 years). We found that LGE is highly prevalent in aortic stenosis, affecting half of all patients (49.6%), with a non-infarct pattern being the most frequent type (63.6%). The estimated extent of focal fibrosis, expressed in % of LV mass, was equal to 3.83 (95% CI [2.14, 5.52], p < 0.0001). The meta-analysis showed that the presence of LGE was associated with increased all-cause (pooled OR [95% CI] = 3.26 [1.72, 6.18], p = 0.0003) and cardiovascular mortality (pooled OR [95% CI] = 2.89 [1.90, 4.38], p < 0.0001). CONCLUSIONS: LGE by CMR is highly prevalent in aortic stenosis patients and exhibits a substantial value in all-cause and cardiovascular mortality prediction. These results suggest a potential role of LGE in aortic stenosis patient risk stratification. KEY POINTS: • Up to the half of aortic stenosis patients are affected by myocardial focal fibrosis. • Sixty-four percent of focal fibrosis detected by LGE-CMR is non-infarct type. • The presence of focal fibrosis triples all-cause and cardiovascular mortality.

High-risk profile in a region with extremely elevated cardiovascular mortality.

INTRODUCTION: Although mortality rates from cardiovascular diseases have shown a remarkable decline in many western countries, cardiovascular mortality in Lithuania has remained high. It is widely accepted that half of the decline in cardiovascular mortality can be attributed to favourable changes in modifiable risk factors. METHODS: In 2006, the Lithuanian High Cardiovascular Risk Programme was started. A two-level approach--primary health care institutions and specialised cardiovascular prevention units--was applied. The cardiovascular risk profile was evaluated for a group of 17,031 middle-aged subjects enrolled into the programme at a primary level and 2908 at a specialised level. RESULTS: Among the persons examined, 61.8% (10,519) were female. Arterial hypertension was present in 60.2% of the subjects. Dyslipidaemia was present in 88.8%. Total cholesterol was 6.02 ± 1.23 mmol/L, LDL cholesterol 3.74 ± 1.09 mmol/L, HDL cholesterol 1.53 ± 0.52 mmol/L, and triglycerides 1.61 ± 1.27 mmol/L. Diabetes mellitus was found in 10.3%, abdominal obesity in 45.4%, and metabolic syndrome in 43.8% of cases. These values were even greater in high-risk subjects. CONCLUSIONS: In middle-aged subjects the prevalence of dyslipidaemia, arterial hypertension, diabetes, and metabolic syndrome was found to be high. We can roughly state that almost nine out of ten middle-aged subjects in Lithuania have established dyslipidaemia, every second one has established arterial hypertension, and four out of ten are obese. Hence, these are the main risk factors that should be considered first of all in daily clinical practice.

Quantitative approach using multiple single parameters versus visual assessment in dobutamine stress echocardiography.

BACKGROUND: A number of myocardial Doppler-derived velocity, strain myocardial imaging parameters (DMI) and speckle tracking imaging (STI) have been proposed for the quantification of myocardial ischemia during stress echocardiography. The purpose of the study was to identify the best single ultrasound quantitative parameter for prediction of significant coronary stenosis and compare it with visual assessment during dobutamine stress echocardiography (DSE). METHODS: Prospective analysis included data of 151 patients (age 61.8 ± 9.2) who underwent dobutamine stress echocardiography for known (n = 35) or suspected coronary artery disease (CAD) (n = 36) or symptomatic chest pain (n = 80), excluding patients with previous myocardial infarction. Systolic, post-systolic and diastolic velocities, strain and strain rate parameters were obtained at rest and at peak dobutamine challenge. Derivative markers as E'/A' ratio, post-systolic index and changes from rest to stress were calculated (98 parameters overall, predominantly longitudinal). Coronary angiography was chosen as reference method considering at least one stenosis ≥70% per patient as significant CAD. The predictive value of quantitative parameters and wall motion score index (WMSI) was obtained using logistic regression and ROC analysis. RESULTS: The value of single parameters discriminated as independent predictors of CAD appeared to be modest (area under the curve [AUC] ranged from 0.63 to 0.72 for 16 PW-DMI, 12 CC-DMI and 12 STI markers), comparing to AUC of WMSI 0.88. Sensitivity, specificity and accuracy of visual DSE evaluation was 82.4% (95%CI 77.4%; 85.2%), 92.6% (95%CI 83.4%; 97.5%) and 86.0% (95%CI 79.5%; 89.6%), respectively, Youden index 0.75. Sensitivity, specificity and accuracy of single predictors ranged from 40.0% to 93.3% (95% CI 22.7%; 99.2%), from 34.2% to 88.7% (95% CI 25.6%; 94.1%) and from 45.8% to 80.0% (95% CI 37.5%; 87.2%) respectively, Youden index ranged from 0.20 to 0.52. CONCLUSIONS: Multiple single quantitative parameters showed limited predictive ability to identify significant coronary artery stenosis. Visual assessment of DSE appears to be more accurate than single velocity and strain/strain rate markers in the diagnosis of CAD.

Value of scar imaging and inotropic reserve combination for the prediction of segmental and global left ventricular functional recovery after revascularisation.

BACKGROUND: This study sought to prospectively and directly compare three cardiovascular magnetic resonance (CMR) viability parameters: inotropic reserve (IR) during low-dose dobutamine (LDD) administration, late gadolinium enhancement transmurality (LGE) and thickness of the non-contrast-enhanced myocardial rim surrounding the scar (RIM). These parameters were examined to evaluate their value as predictors of segmental left ventricular (LV) functional recovery in patients with LV systolic dysfunction undergoing surgical or percutaneous revascularisation. The second goal of the study was to determine the optimal LDD-CMR- and LGE-CMR-based predictor of significant (≥ 5%) LVEF improvement 6 months after revascularisation. METHODS: In 46 patients with chronic coronary artery disease (CAD) (63 ± 10 years of age, LVEF 35 ± 8%), wall motion and the above mentioned CMR parameters were evaluated before revascularisation. Wall motion and LGE were repeatedly assessed 6 months after revascularisation. Logistic regression analysis models were created using 333 dysfunctional segments at rest. RESULTS: An LGE threshold value of 50% (LGE50) and a RIM threshold value of 4 mm (RIM4) produced the best sensitivities and specificities for predicting segmental recovery. IR was superior to LGE50 for predicting segmental recovery. When the areas under the ROC curves is compared, the combined viability prediction model (LGE50 + IR) was significantly superior to IR alone in all analysed sets of segments, except the segments with an LGE from 26% to 75% (p = 0.08). The RIM4 model was not superior to the LGE50 model. A myocardial segment was considered viable if it had no LGE or had any LGE and produced IR during LDD stimulation. ROC analysis demonstrated that ≥ 50% of viable segments from all dysfunctional and revascularised segments in a patient predict significant improvement in LVEF with a 69% sensitivity and 70% specificity (AUC 0.7, p = 0.05). The cut-off of ≥ 3 viable segments was a less useful predictor of significant global LV recovery. CONCLUSIONS: LDD-CMR is superior to LGE-CMR as a predictor of segmental recovery. The advantage is greatest in the segments with an LGE from 26% to 75%. The RIM cut-off value of 4 mm had no superiority over the LGE cut-off value of 50% in predicting the segmental recovery. Patients with ≥ 50% of viable segments from all dysfunctional and revascularised had a tendency to improve LVEF by ≥ 5% after revascularisation.