Disease progression rate is a strong predictor of ventricular arrhythmias in patients with cardiac laminopathies: a primary prevention cohort study.

AIMS: Cardiac disease progression prior to first ventricular arrhythmia (VA) in LMNA genotype-positive patients is not described. METHODS AND RESULTS: We performed a primary prevention cohort study, including consecutive LMNA genotype-positive patients from our centre. Patients underwent repeated clinical, electrocardiographic, and echocardiographic examinations. Electrocardiographic and echocardiographic disease progression as a predictor of first-time VA was evaluated by generalized estimation equation analyses. Threshold values at transition to an arrhythmic phenotype were assessed by threshold regression analyses. We included 94 LMNA genotype-positive patients without previous VA (age 38 ± 15 years, 32% probands, 53% females). Nineteen (20%) patients experienced VA during 4.6 (interquartile range 2.1-7.3) years follow up, at mean age 50 ± 11 years. We analysed 536 echocardiographic and 261 electrocardiogram examinations. Individual patient disease progression was associated with VA [left ventricular ejection fraction (LVEF) odds ratio (OR) 1.4, 95% confidence interval (CI) 1.2-1.6 per 5% reduction, left ventricular end-diastolic volume index (LVEDVi) OR 1.2 (95% CI 1.1-1.3) per 5 mL/m2 increase, PR interval OR 1.2 (95% CI 1.1-1.4) per 10 ms increase]. Threshold values for transition to an arrhythmic phenotype were LVEF 44%, LVEDVi 77 mL/m2, and PR interval 280 ms. CONCLUSIONS: Incidence of first-time VA was 20% during 4.6 years follow up in LMNA genotype-positive patients. Individual patient disease progression by ECG and echocardiography were strong predictors of VA, indicating that disease progression rate may have additional value to absolute measurements when considering primary preventive ICD. Threshold values of LVEF <44%, LVEDVi >77 mL/m2, and PR interval >280 ms indicated transition to a more arrhythmogenic phenotype.

Deep learning for automated left ventricular outflow tract diameter measurements in 2D echocardiography.

BACKGROUND: Measurement of the left ventricular outflow tract diameter (LVOTd) in echocardiography is a common source of error when used to calculate the stroke volume. The aim of this study is to assess whether a deep learning (DL) model, trained on a clinical echocardiographic dataset, can perform automatic LVOTd measurements on par with expert cardiologists. METHODS: Data consisted of 649 consecutive transthoracic echocardiographic examinations of patients with coronary artery disease admitted to a university hospital. 1304 LVOTd measurements in the parasternal long axis (PLAX) and zoomed parasternal long axis views (ZPLAX) were collected, with each patient having 1-6 measurements per examination. Data quality control was performed by an expert cardiologist, and spatial geometry data was preserved for each LVOTd measurement to convert DL predictions into metric units. A convolutional neural network based on the U-Net was used as the DL model. RESULTS: The mean absolute LVOTd error was 1.04 (95% confidence interval [CI] 0.90-1.19) mm for DL predictions on the test set. The mean relative LVOTd errors across all data subgroups ranged from 3.8 to 5.1% for the test set. Generally, the DL model had superior performance on the ZPLAX view compared to the PLAX view. DL model precision for patients with repeated LVOTd measurements had a mean coefficient of variation of 2.2 (95% CI 1.6-2.7) %, which was comparable to the clinicians for the test set. CONCLUSION: DL for automatic LVOTd measurements in PLAX and ZPLAX views is feasible when trained on a limited clinical dataset. While the DL predicted LVOTd measurements were within the expected range of clinical inter-observer variability, the robustness of the DL model requires validation on independent datasets. Future experiments using temporal information and anatomical constraints could improve valvular identification and reduce outliers, which are challenges that must be addressed before clinical utilization.

Neural classification of Norwegian radiology reports: using NLP to detect findings in CT-scans of children.

BACKGROUND: With a motivation of quality assurance, machine learning techniques were trained to classify Norwegian radiology reports of paediatric CT examinations according to their description of abnormal findings. METHODS: 13.506 reports from CT-scans of children, 1000 reports from CT scan of adults and 1000 reports from X-ray examination of adults were classified as positive or negative by a radiologist, according to the presence of abnormal findings. Inter-rater reliability was evaluated by comparison with a clinician's classifications of 500 reports. Test-retest reliability of the radiologist was performed on the same 500 reports. A convolutional neural network model (CNN), a bidirectional recurrent neural network model (bi-LSTM) and a support vector machine model (SVM) were trained on a random selection of the children's data set. Models were evaluated on the remaining CT-children reports and the adult data sets. RESULTS: Test-retest reliability: Cohen's Kappa = 0.86 and F1 = 0.919. Inter-rater reliability: Kappa = 0.80 and F1 = 0.885. Model performances on the Children-CT data were as follows. CNN: (AUC = 0.981, F1 = 0.930), bi-LSTM: (AUC = 0.978, F1 = 0.927), SVM: (AUC = 0.975, F1 = 0.912). On the adult data sets, the models had AUC around 0.95 and F1 around 0.91. CONCLUSIONS: The models performed close to perfectly on its defined domain, and also performed convincingly on reports pertaining to a different patient group and a different modality. The models were deemed suitable for classifying radiology reports for future quality assurance purposes, where the fraction of the examinations with abnormal findings for different sub-groups of patients is a parameter of interest.

Lamin A/C cardiomyopathy: young onset, high penetrance, and frequent need for heart transplantation.

Aims: Lamin A/C (LMNA) mutations cause familial dilated cardiomyopathy (DCM) with frequent conduction blocks and arrhythmias. We explored the prevalence, cardiac penetrance, and expressivity of LMNA mutations among familial DCM in Norway. Furthermore, we explored the risk factors and the outcomes in LMNA patients. Methods and results: During 2003-15, genetic testing was performed in patients referred for familial DCM. LMNA genotype-positive subjects were examined by electrocardiography, Holter monitoring, cardiac magnetic resonance imaging, and echocardiography. A positive cardiac phenotype was defined as the presence of atrioventricular (AV) block, atrial fibrillation/flutter (AF), ventricular tachycardia (VT), and/or echocardiographic DCM. Heart transplantation was recorded and compared with non-ischaemic DCM of other origin. Of 561 unrelated familial DCM probands, 35 (6.2%) had an LMNA mutation. Family screening diagnosed an additional 93 LMNA genotype-positive family members. We clinically followed up 79 LMNA genotype-positive [age 42 ± 16 years, ejection fraction (EF) 45 ± 13%], including 44 (56%) with VT. Asymptomatic LMNA genotype-positive family members (age 31 ± 15 years) had a 9% annual incidence of a newly documented cardiac phenotype and 61% (19/31) of cardiac penetrance during 4.4 ± 2.9 years of follow-up. Ten (32%) had AV block, 7 (23%) AF, and 12 (39%) non-sustained VT. Heart transplantation was performed in 15 of 79 (19%) LMNA patients during 7.8 ± 6.3 years of follow-up. Conclusion: LMNA mutation prevalence was 6.2% of familial DCM in Norway. Cardiac penetrance was high in young asymptomatic LMNA genotype-positive family members with frequent AV block and VT, highlighting the importance of early family screening and cardiological follow-up. Nearly 20% of the LMNA patients required heart transplantation.

Artificial intelligence in clinical practice - an industry without raw materials. / Kunstig intelligens i klinikken ­ en industri uten råvarer.

Research on health data is unfortunately guided by the available data rather than the clinical problems we need to solve. Clinically-related data are locked away in silos. As a result, both patients and research are losing out.

Determinants of high sensitivity cardiac troponin T elevation in acute ischemic stroke.

BACKGROUND: A proportion of patients with acute ischemic stroke have elevated cardiac troponin levels and ECG changes suggestive of cardiac injury, but the etiology is unclear. The aims of this study were to assess the frequency of high sensitivity cardiac troponin T (hs-cTnT) elevation, to identify determinants and ECG changes associated with hs-cTnT elevation, to identify patients with myocardial ischemia and to assess the impact of hs-cTnT elevation on in-hospital mortality. METHODS: Patients discharged with a diagnosis of acute ischemic stroke during a 1-year period, were included. Patients diagnosed with acute myocardial infarction (MI) within the last 7 days before admission or during hospitalization were excluded. RESULTS: In all, 156 (54.4%) of 287 patients had elevated hs-cTnT. The factors independently associated with hs-cTnT elevation were age ≥ 76 years (OR 3.71 [95% CI 2.04-6.75]), previous coronary heart disease (CHD) (OR 2.61 [1.23-5.53]), congestive heart failure (OR 4.26 [1.15-15.82]), diabetes mellitus (OR 4.02 [1.50-10.76]) and lower eGFR (OR 0.97 [0.95-0.98]). Of the 182 patients who had two hs-cTnT measurements, 12 (6.6%) had both a rise or fall of hs-cTnT with at least one elevated value, and ECG manifestations of myocardial ischemia, e.g. meeting the criteria of acute MI. Both dynamic relative change (p = 0.026) and absolute change (p = 0.032) in hs-cTnT were significantly associated with higher in-hospital mortality. CONCLUSIONS: Established CHD and cardiovascular risk factors are associated with hs-cTnT elevation. Acute MI is likely underdiagnosed in acute ischemic stroke patients. Dynamic changes in troponin levels seem to be related to poor short-term prognosis.

Differentiation of Myocardial Properties in Physiological Athletic Cardiac Remodeling and Mild Hypertrophic Cardiomyopathy.

Clinical differentiation between athletes' hearts and those with hypertrophic cardiomyopathy (HCM) can be challenging. We aimed to explore the role of speckle tracking echocardiography (STE) and cardiac magnetic resonance imaging (CMR) in the differentiation between athletes' hearts and those with mild HCM. We compared 30 competitive endurance elite athletes (7% female, age 41 ± 9 years) and 20 mild phenotypic mutation-positive HCM carriers (15% female, age 51 ± 12 years) with left ventricular wall thickness 13 ± 1 mm. Mechanical dispersion (MD) was assessed by means of STE. Native T1-time and extracellular volume (ECV) were assessed by means of CMR. MD was higher in HCM mutation carriers than in athletes (54 ± 16 ms vs. 40 ± 11 ms, p = 0.001). Athletes had a lower native T1-time (1204 (IQR 1191, 1234) ms vs. 1265 (IQR 1255, 1312) ms, p < 0.001) and lower ECV (22.7 ± 3.2% vs. 25.6 ± 4.1%, p = 0.01). MD > 44 ms optimally discriminated between athletes and HCM mutation carriers (AUC 0.78, 95% CI 0.65-0.91). Among the CMR parameters, the native T1-time had the best discriminatory ability, identifying all HCM mutation carriers (100% sensitivity) with a specificity of 75% (AUC 0.83, 95% CI 0.71-0.96) using a native T1-time > 1230 ms as the cutoff. STE and CMR tissue characterization may be tools that can differentiate athletes' hearts from those with mild HCM.

NT-proBNP independently predicts long term mortality after acute exacerbation of COPD - a prospective cohort study.

BACKGROUND: Cardiovascular disease is prevalent and frequently unrecognized in patients with chronic obstructive pulmonary disease (COPD). NT-proBNP is an established risk factor in patients with heart failure. NT-proBNP may also be released from the right ventricle. Thus serum NT-proBNP may be elevated during acute exacerbations of COPD (AECOPD). The prognostic value of NT-proBNP in patients hospitalized with AECOPD is sparsely studied. Our objective was to test the hypothesis that NT-proBNP independently predicts long term mortality following AECOPD. METHODS: A prospective cohort study of 99 patients with 217 admissions with AECOPD. Clinical, electrocardiographic, radiological and biochemical data were collected at index and repeat admissions and analyzed in an extended survival analysis with time-dependent covariables. RESULTS: Median follow-up time was 1.9 years, and 57 patients died during follow-up. NT-proBNP tertile limits were 264.4 and 909 pg/mL, and NT-proBNP in tertiles 1 through 3 was associated with mortality rates of 8.6, 35 and 62 per 100 patient-years, respectively (age-adjusted log-rank p<0.0001). After adjustment for age, gender, peripheral edema, cephalization and cTnT in a multivariable survival model, the corresponding hazard ratios for dying were 2.4 (0.95-6.0) and 3.2 (1.3-8.1) (with 95% confidence intervals in parentheses, p-value for trend 0.013). CONCLUSIONS: NT-proBNP is a strong and independent determinant of mortality after AECOPD.

Determinants of high-sensitivity cardiac troponin T during acute exacerbation of chronic obstructive pulmonary disease: a prospective cohort study.

BACKGROUND: A high-sensitivity cardiac troponin T (hs-cTnT) concentration above the 99th percentile (i.e. 14 ng/L) is common during Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) and associated with increased mortality. The objective of the study was to identify factors associated with hs-cTnT levels during AECOPD. METHODS: We included 99 patients with AECOPD on admission. As 41 patients had one or more repeat admissions, there were 202 observations in the final analysis. We recorded clinical and biochemical data, medication, spirometry, chest radiographs, and ECGs. The data were analysed for cross-sectional and longitudinal associations using ordinary least square as well as linear mixed models with the natural logarithm of hs-cTnT as the dependent variable. RESULTS: Mean age at inclusion was 71.5 years, mean FEV1/FVC was 45%, and median hs-cTnT was 27.0 ng/L. In a multivariable model there was a 24% increase in hs-cTnT per 10 years increase in age (p < 0.0001), a 6% increase per 10 µmol/L increase in creatinine (p = 0.037), and a 2% increase per month after enrollment (p = 0.046). Similarly, the ratios of hs-cTnT between patients with and without tachycardia (heart rate ≥100/min) and with and without history of arterial hypertension were 1.25 (p = 0.042) and 1.44 (p = 0.034), respectively. We found no significant association between arterial hypoxemia and elevated hs-cTnT. CONCLUSION: Age, arterial hypertension, tachycardia, and serum creatinine are independently associated with the level of hs-cTnT on admission for AECOPD.

Cardiac Structure and Function in Epilepsy Patients with Drug-Resistant Convulsive Seizures.

High frequency of convulsive seizures and long-lasting epilepsy are associated with an increased risk of sudden unexpected death in epilepsy (SUDEP). Structural changes in the myocardium have been described in SUDEP victims. It is speculated that these changes are secondary to frequent convulsive seizures and may predispose to SUDEP. The aim of this cross-sectional study was to investigate the impact of chronic drug-resistant epilepsy on cardiac function and structure in patients with a high frequency of convulsive seizures. We consecutively included 21 patients (17 women, 4 men) aged 18-40 years, with at least 10 years with epilepsy and a minimum of six convulsive seizures in the last year and without a history of status epilepticus or nonepileptic events. A complete clinical examination, resting 12-lead electrocardiogram, 72-h Holter monitoring, and echocardiography were recorded in all patients. Ten patients were assessed by 3-Tesla cardiac magnetic resonance imaging. Echocardiography and MRI data were compared with those from age- and sex-matched healthy control individuals. No significant changes in cardiac structure or function were found among patients with chronic drug-resistant epilepsy and high frequency of convulsive seizures. However, we cannot exclude that there are subgroups of patients who are more prone to epilepsy-associated cardiac alterations.

Synthetic data for annotation and extraction of family history information from clinical text.

BACKGROUND: The limited availability of clinical texts for Natural Language Processing purposes is hindering the progress of the field. This article investigates the use of synthetic data for the annotation and automated extraction of family history information from Norwegian clinical text. We make use of incrementally developed synthetic clinical text describing patients' family history relating to cases of cardiac disease and present a general methodology which integrates the synthetically produced clinical statements and annotation guideline development. The resulting synthetic corpus contains 477 sentences and 6030 tokens. In this work we experimentally assess the validity and applicability of the annotated synthetic corpus using machine learning techniques and furthermore evaluate the system trained on synthetic text on a corpus of real clinical text, consisting of de-identified records for patients with genetic heart disease. RESULTS: For entity recognition, an SVM trained on synthetic data had class weighted precision, recall and F1-scores of 0.83, 0.81 and 0.82, respectively. For relation extraction precision, recall and F1-scores were 0.74, 0.75 and 0.74. CONCLUSIONS: A system for extraction of family history information developed on synthetic data generalizes well to real, clinical notes with a small loss of accuracy. The methodology outlined in this paper may be useful in other situations where limited availability of clinical text hinders NLP tasks. Both the annotation guidelines and the annotated synthetic corpus are made freely available and as such constitutes the first publicly available resource of Norwegian clinical text.

Two methods for modifed Doo-Sabin modeling of nonsmooth surfaces-applied to right ventricle modeling.

Purpose: In recent years, there has been increased clinical interest in the right ventricle (RV) of the heart. RV dysfunction is an important prognostic marker for several cardiac diseases. Accurate modeling of the RV shape is important for estimating the performance. We have created computationally effective models that allow for accurate estimation of the RV shape. Approach: Previous approaches to cardiac shape modeling, including modeling the RV geometry, has used Doo-Sabin surfaces. Doo-Sabin surfaces allow effective computation and adapt to smooth, organic surfaces. However, they struggle with modeling sharp corners or ridges without many control nodes. We modified the Doo-Sabin surface to allow for sharpness using weighting of vertices and edges instead. This was done in two different ways. For validation, we compared the standard Doo-Sabin versus the sharp Doo-Sabin models in modeling the RV shape of 16 cardiac ultrasound images, against a ground truth manually drawn by a cardiologist. A Kalman filter fitted the models to the ultrasound images, and the difference between the volume of the model and the ground truth was measured. Results: The two modified Doo-Sabin models both outperformed the standard Doo-Sabin model in modeling the RV. On average, the regular Doo-Sabin had an 8-ml error in volume, whereas the sharp models had 7- and 6-ml error, respectively. Conclusions: Compared with the standard Doo-Sabin, the modified Doo-Sabin models can adapt to a larger variety of surfaces while still being compact models. They were more accurate on modeling the RV shape and could have uses elsewhere.

Impact of transcatheter aortic valve implantation on mechanical dispersion.

Objectives: The physiological determinants of left ventricular (LV) mechanical dispersion (MD) are not fully explored. We aimed to investigate the impact of afterload reduction and changes in ventricular conduction on LV MD after transcatheter aortic valve implantation (TAVI). Methods: Patients with severe aortic stenosis (AS) were examined in a prospective, repeated measures observational cohort study before and after an uncomplicated transfemoral TAVI in a single tertiary centre. LV MD was assessed by speckle tracking echocardiography. Valvulo-arterial impedance (ZVA) was used as a measure of global afterload. Results: We included 140 consecutive patients (83±8 years old, 49% women, logistic EuroSCORE 16±10) with severe AS (valve area 0.7±0.2 cm2, mean transvalvular gradient 54±18 mm Hg) and a relatively preserved LV ejection fraction (52%±11%). After TAVI, we observed favourable changes in transvalvular gradients and ZVA in all patients. Compared with baseline, postprocedural MD was significantly lower in 108 patients with unchanged ventricular conduction (55±17 ms vs 51±17 ms, p=0.02) and higher in 28 patients with TAVI-induced left bundle branch block (51±13 ms vs 62±19 ms, p≤0.001). During 22±9 months observation, 22 patients died. Postprocedural MD was associated with mortality in a univariate Cox regression model (HR=1.24 (1.01-1.52), p<0.04, per 10 ms increase). Conclusions: Isolated afterload reduction was associated with reduction of MD, while concomitant impairment of ventricular conduction resulted in a more pronounced MD after TAVI, indicating that loading conditions and conduction should be considered when evaluating MD. A pronounced postprocedural LV MD was associated with mortality.

Determinants of cardiac troponin T elevation in COPD exacerbation - a cross-sectional study.

BACKGROUND: Cardiac Troponin T (cTnT) elevation during exacerbations of chronic obstructive pulmonary disease (COPD) is associated with increased mortality the first year after hospital discharge. The factors associated with cTnT elevation in COPD are not known. METHODS: From our hospital's database, all patients admitted with COPD exacerbation in 2000-03 were identified. 441 had measurement of cTnT performed. Levels of cTnT > or = 0.04 microg/l were considered elevated. Clinical and historical data were retrieved from patient records, hospital and laboratory databases. Odds ratios for cTnT elevation were calculated using logistic regression. RESULTS: 120 patients (27%) had elevated cTnT levels. The covariates independently associated with elevated cTnT were increasing neutrophil count, creatinine concentration, heart rate and Cardiac Infarction Injury Score (CIIS), and decreasing hemoglobin concentration. The adjusted odds ratios (95% confidence intervals in parentheses) for cTnT elevation were 1.52 (1.20-1.94) for a 5 x 106/ml increase in neutrophils, 1.21 (1.12-1.32) for a 10 micromol/l increase in creatinine, 0.80 (0.69-0.92) for a 1 mg/dl increase in hemoglobin, 1.24 (1.09-1.42) for a 10 beats/minute increase in heart rate and 1.44 (1.15-1.82) for a 10 point increase in CIIS. CONCLUSION: Multiple factors are associated with cTnT elevation, probably reflecting the wide panorama of comorbid conditions typically seen in COPD. The positive association between neutrophils and cTnT elevation is compatible with the concept that an exaggerated inflammatory response in COPD exacerbation may predispose for myocardial injury.

Classical mechanical dyssynchrony is rare in transcatheter aortic valve implantation-induced left bundle branch block.

AIMS: Left bundle branch block (LBBB) is a frequent conduction abnormality after transcatheter aortic valve implantation (TAVI). We aimed to investigate how TAVI procedure related conduction abnormalities influence ventricular mechanics and prognosis, with particular focus on new-onset persistent LBBB. METHODS AND RESULTS: A total of 140 consecutive patients with severe aortic stenosis (83 ± 8 years old, 49% women) undergoing TAVI in a single tertiary centre were included in a repeated measures study. Changes in myocardial function and contraction patterns were investigated in relation to changes in electrical conduction and afterload by speckle tracking echocardiography. Whether patients with new-onset LBBB acquired classical dyssynchronous contractions was assessed by longitudinal strain in apical four-chamber view. Global longitudinal strain improvement was seen in all patients (-15.1 ± 4.3 vs. -16.1 ± 3.9%, P < 0.01, n = 140), and all subgroups, regardless of pre-existing or procedure-acquired conduction abnormalities immediately after TAVI. New-onset LBBB fulfilling strict electrocardiogram (ECG) criteria was observed in 28 patients (20%). The vast majority of new-onset LBBB patients (n = 26, 93%) had homogenous contractions. Classical dyssynchronous LBBB contractions were only observed in 2 patients (7%) with new-onset LBBB. Patients with new-onset LBBB and patients without acquired conduction disorders had similar mortality rates during 19 ± 9 months of follow-up [11.1, 95% confidence interval (CI) 4.6-26.8 vs. 8.1, 95% CI 4.8-13.7 per 100 patients years, P = 0.53]. CONCLUSION: Classical dyssynchronous LBBB contractions were absent in most patients with new-onset post-TAVI LBBB, even when applying strict ECG criteria. Patients with and without new-onset LBBB experienced similar prognosis with regards to mortality.

Detection of Regional Mechanical Activation of the Left Ventricular Myocardium Using High Frame Rate Ultrasound Imaging.

We have investigated the feasibility of noninvasive mapping of mechanical activation patterns in the left ventricular (LV) myocardium using high frame rate ultrasound imaging for the purpose of detecting conduction abnormalities. Five anesthetized, open-chest dogs with implanted combined sonomicrometry and electromyography (EMG) crystals were studied. The animals were paced from the specified locations of the heart, while crystal and ultrasound data were acquired. Isochrone maps of the mechanical activation patterns were generated from the ultrasound data using a novel signal processing method called clutter filter wave imaging (CFWI). The isochrone maps showed the same mechanical activation pattern as the sonomicrometry crystals in 90% of the cases. For electrical activation, the activation sequences from ultrasound were the same in 92% of the cases. The coefficient of determination between the activation delay measured with EMG and ultrasound was R 2 = 0.79 , indicating a strong correlation. These results indicate that high frame rate ultrasound imaging processed with CFWI has the potential to be a valuable tool for mechanical activation detection.

Underdiagnosis of myocardial infarction in COPD - Cardiac Infarction Injury Score (CIIS) in patients hospitalised for COPD exacerbation.

BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) are usually former or current smokers, and are at increased risk of ischemic heart disease. We used Cardiac Infarction Injury Score (CIIS) to assess the prevalence of prior myocardical infarction (MI) in COPD patients and compared this to clinicians' previous diagnosis of MI. METHODS: From the hospital database, 897 patients (mean age 70.9 years, 50.8% female) discharged after treatment for COPD exacerbation in the years 2000-2003 were identified. Disease history was established from medical records and the hospital patient database. Electrocardiograms from the day of admission were available in 827 patients, and were coded according to the CIIS algorithm by an investigator blinded to clinical and outcome data. The CIIS score was validated using follow-up data for the first year after discharge. RESULTS: Two hundred and twenty-nine patients had CIIS > or = 20, out of whom only 30% (95% confidence interval: 24-36%, n=68) had a recognised history of MI. Female patients had a lower probability of diagnosis despite ECG evidence. Validation of CIIS using multivariate Cox regression analysis showed that a score > or = 20 had independent prognostic value for the first year after discharge, with an adjusted HR of 1.52 (1.14-2.03). CONCLUSION: Unrecognised MI is common in patients hospitalised with COPD exacerbation. Less than one-third of patients with ECG evidence of previous MI by the CIIS system actually have the diagnosis in their medical records.

Prognostic Value of Left Ventricular Deformation Parameters in Patients with Severe Aortic Stenosis: A Pilot Study of the Usefulness of Strain Echocardiography.

BACKGROUND: In patients with aortic stenosis, subtle alterations in myocardial mechanics can be detected by speckle-tracking echocardiography before reduction of left ventricular ejection fraction (LVEF). METHODS: In this prospective study, 162 patients with aortic stenosis with an average aortic valve area of 0.7 ± 0.2 cm2 and a mean LVEF of 60 ± 11% were included. Global longitudinal strain (GLS) and mechanical dispersion (SD of time from Q/R on the electrocardiogram to peak strain in 16 left ventricular segments) were assessed using echocardiography, and all-cause mortality (n = 37) was recorded during 37 ± 13 months of follow-up. RESULTS: Overall, nonsurvivors had more pronounced mechanical dispersion and worse GLS compared with survivors (74 ± 24 vs 61 ± 18 msec [P < .01] and -14.5 ± 4.4% vs -16.7 ± 3.6% [P < .01], respectively). In the 42 conservatively treated patients without surgical aortic valve replacement, a similar pattern was observed in nonsurvivors versus survivors (mechanical dispersion, 80 ± 24 vs 57 ± 14 msec [P < .01]; GLS, -14.0 ± 4.9% vs -17.1 ± 3.8% [P = .04], respectively). Mechanical dispersion was significantly associated with mortality (hazard ratio per 10-msec increase, 1.23; 95% CI, 1.07-1.42; P < .01) in a Cox model adjusted for LVEF and with aortic valve replacement treatment as a time-dependent covariate. Continuous net reclassification improvement showed that mechanical dispersion was incremental to LVEF, GLS, and valvulo-arterial impedance when adjusting for aortic valve replacement treatment in the total population. CONCLUSION: Increased mechanical dispersion may be a risk marker providing novel prognostic information in patients with aortic stenosis.