Left ventricular segmental wall motion analysis is important for clinical decision making in cardiac diseases. Strain analysis with myocardial tissue tagging is the non-invasive gold standard for ...quantitative assessment, however, it is time-consuming. Cardiovascular magnetic resonance myocardial feature-tracking (CMR-FT) can rapidly perform strain analysis, because it can be employed with standard CMR cine-imaging. The aim is to validate segmental peak systolic circumferential strain (peak SCS) and time to peak systolic circumferential strain (T2P-SCS) analysed by CMR-FT against tissue tagging, and determine its intra and inter-observer variability.
Patients in whom both cine CMR and tissue tagging has been performed were selected. CMR-FT analysis was done using endocardial (CMR-FTendo) and mid-wall contours (CMR-FTmid). The Intra Class Correlation Coefficient (ICC) and Pearson correlation were calculated.
10 healthy volunteers, 10 left bundle branch block (LBBB) and 10 hypertrophic cardiomyopathy patients were selected. With CMR-FT all 480 segments were analyzable and with tissue tagging 464 segments.Significant differences in mean peak SCS values of the total study group were present between CMR-FTendo and tissue tagging (-23.8 ± 9.9% vs -13.4 ± 3.3%, p<0.001). Differences were smaller between CMR-FTmid and tissue tagging (-16.4 ± 6.1% vs -13.4 ± 3.3%, p=0.001). The ICC of the mean peak SCS of the total study group between CMR-FTendo and tissue tagging was low (0.19 (95%-CI-0.10-0.49), p=0.02). Comparable results were seen between CMR-FTmid and tissue tagging. In LBBB patients, mean T2P-SCS values measured with CMR-FTendo and CMR-FTmid were 418 ± 66 ms, 454 ± 60 ms, which were longer than with tissue tagging, 376 ± 55 ms, both p<0.05. ICC of the mean T2P-SCS between CMR-FTendo and tissue tagging was 0.64 (95%-CI-0.36-0.81), p<0.001, this was better in the healthy volunteers and LBBB group, whereas the ICC between CMR-FTmid and tissue tagging was lower.The intra and inter-observer agreement of segmental peak SCS with CMR-FTmid was lower compared with tissue tagging; similar results were seen for segmental T2P-SCS.
The intra and inter-observer agreement of segmental peak SCS and T2P-SCS is substantially lower with CMR-FTmid compared with tissue tagging. Therefore, current segmental CMR-FTmid techniques are not yet applicable for clinical and research purposes.
Knee osteoarthritis (OA) is a leading cause of activity limitations. The knee OA population is likely to consist of subgroups. The aim of the present study was to identify homogeneous subgroups with ...distinct trajectories of activity limitations in patients with early symptomatic knee OA and to describe characteristics of these subgroups.
Follow-up data over a period of 5 years of 697 participants with early symptomatic knee OA from the Cohort Hip and Cohort Knee (CHECK) were used. Activity limitations were measured yearly with the Western Ontario and McMaster Universities Osteoarthritis Index. Latent class growth analyses identified homogeneous subgroups with distinct trajectories of activity limitations. Multivariable regression analyses examined differences in characteristics between the subgroups.
Three subgroups were identified. Participants in Subgroup 1 ('good outcome'; n=330) developed or displayed slight activity limitations over time. Participants in Subgroup 2 ('moderate outcome'; n=257) developed or displayed moderate activity limitations over time. Participants in subgroup 3 ('poor outcome'; n=110) developed or displayed severe activity limitations over time. Compared with the 'good outcome' subgroup, the 'moderate outcome' and 'poor outcome' subgroups were characterised by: younger age, higher body mass index, greater pain, bony tenderness, reduced knee flexion, hip pain, osteophytosis, ≥3 comorbidities, lower vitality or avoidance of activities.
Based on the 5-year course of activity limitations, we identified homogeneous subgroups of knee OA patients with good, moderate or poor outcome. Characteristics of these subgroups were consistent with existing knowledge on prognostic factors regarding activity limitations, which supports the validity of this classification.
Confounding is a common issue in epidemiological research. Commonly used confounder-adjustment methods include multivariable regression analysis and propensity score methods. Although it is common ...practice to assess the linearity assumption for the exposure-outcome effect, most researchers do not assess linearity of the relationship between the confounder and the exposure and between the confounder and the outcome before adjusting for the confounder in the analysis. Failing to take the true non-linear functional form of the confounder-exposure and confounder-outcome associations into account may result in an under- or overestimation of the true exposure effect. Therefore, this paper aims to demonstrate the importance of assessing the linearity assumption for confounder-exposure and confounder-outcome associations and the importance of correctly specifying these associations when the linearity assumption is violated.
A Monte Carlo simulation study was used to assess and compare the performance of confounder-adjustment methods when the functional form of the confounder-exposure and confounder-outcome associations were misspecified (i.e., linearity was wrongly assumed) and correctly specified (i.e., linearity was rightly assumed) under multiple sample sizes. An empirical data example was used to illustrate that the misspecification of confounder-exposure and confounder-outcome associations leads to bias.
The simulation study illustrated that the exposure effect estimate will be biased when for propensity score (PS) methods the confounder-exposure association is misspecified. For methods in which the outcome is regressed on the confounder or the PS, the exposure effect estimate will be biased if the confounder-outcome association is misspecified. In the empirical data example, correct specification of the confounder-exposure and confounder-outcome associations resulted in smaller exposure effect estimates.
When attempting to remove bias by adjusting for confounding, misspecification of the confounder-exposure and confounder-outcome associations might actually introduce bias. It is therefore important that researchers not only assess the linearity of the exposure-outcome effect, but also of the confounder-exposure or confounder-outcome associations depending on the confounder-adjustment method used.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Objectives The current study evaluates the incremental value of transluminal attenuation gradient (TAG), TAG with corrected contrast opacification (CCO), and TAG with exclusion of calcified coronary ...segments (ExC) over coronary computed tomography angiogram (CTA) alone using fractional flow reserve (FFR) as the gold standard. Background TAG is defined as the contrast opacification gradient along the length of a coronary artery on a coronary CTA. Preliminary data suggest that TAG provides additional functional information. Interpretation of TAG is hampered by multiple heartbeat acquisition algorithms and coronary calcifications. Two correction models have been proposed based on either dephasing of contrast delivery by relating coronary density to corresponding descending aortic opacification (TAG-CCO) or excluding calcified coronary segments (TAG-ExC). Methods Eighty-five patients with intermediate probability of coronary artery disease were prospectively included. All patients underwent step-and-shoot 256-slice coronary CTA. TAG, TAG-CCO, and TAG-ExC analyses were performed followed by invasive coronary angiography in conjunction with FFR measurements of all major coronary branches. Results Thirty-four patients (40%) were diagnosed with hemodynamically-significant coronary artery disease (i.e., FFR ≤0.80). On a per-vessel basis (n = 253), 59 lesions (23%) were graded as hemodynamically significant, and the diagnostic accuracy of coronary CTA (diameter stenosis ≥50%) was 95%, 75%, 98%, and 54% for sensitivity, specificity, negative predictive value, and positive predictive value, respectively. TAG and TAG-ExC did not discriminate between vessels with or without hemodynamically significant lesions (–13.5 ± 17.1 HU Hounsfield units × 10 mm–1 vs. –11.6 ± 13.3 HU × 10 mm–1 , p = 0.36; and 13.1 ± 15.9 HU × 10 mm–1 vs. –11.4 ± 11.7 HU × 10 mm–1 , p = 0.77, respectively). TAG-CCO was lower in vessels with a hemodynamically-significant lesion (–0.050 ± 0.051 10 mm–1 vs. –0.036 ± 0.034 10 mm–1 , p = 0.03) and TAG-ExC resulted in a slight improvement of the net reclassification index (0.021, p < 0.05). Conclusions TAG did not provide incremental diagnostic value over 256-slice coronary CTA alone in assessing the hemodynamic consequences of a coronary stenosis. Correction for temporal nonuniformity of contrast delivery or exclusion of calcified coronary segments slightly enhanced the results.
Abstract
Study Objectives
Children often experience sleep problems, with a negative impact on mood, behavior, cognitive function, and other aspects of mental and physical health. Accelerometers are ...widely used to assess sleep, but general reference values for healthy children do not yet exist. The aim of this meta-analysis was to determine mean values for wake after sleep onset (WASO), sleep efficiency (SE), total sleep time (TST) and sleep onset latency (SOL), and to determine the effect of child and accelerometer-characteristics.
Methods
A search included studies with healthy children, 0–18 years, reporting WASO, SE, TST, and/or SOL, calculated with the Sadeh algorithm. Meta-analyses with random effects produced pooled estimate means per outcome. Meta-regression analyses determined the effect of age, sex, placement site and accelerometer type.
Results
Eighty-three studies (9,068 participants) were included. Pooled means were 63 min (95% CI 57 to 69) for WASO, 88% (95% CI 87 to 89) for SE, 477 min (95% CI 464 to 491) for TST and 19 min (95% CI 17 to 22) for SOL. Heterogeneity was high (95%–99%). TST decreased with age and there was an age-effect on SOL. SE differed between wrist and ankle (used in age 0–24 months) placement, and between piezoelectric and MEMS-type accelerometers. No differences were found between boys and girls, although this number of studies was small.
Conclusions
We found differences in almost all investigated outcomes and heterogeneity was high. Therefore, we advise to use a study-specific control sample until more robust reference values are available. Future research should narrow the methodological heterogeneity and produce larger datasets, needed to establish these reference values.
Background
Lower protein intake in older adults is associated with loss of muscle mass and strength. The present study aimed to provide a pooled estimate of the overall prevalence of protein intake ...below recommended (according to different cut‐off values) among community‐dwelling older adults, both within the general older population and within specific subgroups.
Methods
As part of the PRevention Of Malnutrition In Senior Subjects in the EU (PROMISS) project, a meta‐analysis was performed using data from four cohorts (from the Netherlands, UK, Canada, and USA) and four national surveys from the Netherlands, Finland (two), and Italy. Within those studies, data on protein and energy intake of community‐dwelling men and women aged ≥55 years were obtained by either a food frequency questionnaire, 24 h recalls administered on 2 or 3 days, or food diaries administered on 3 days. Protein intake below recommended was based on the recommended dietary allowance of 0.8 g/kg body weight (BW)/d, by using adjusted BW (aBW) instead of actual BW. Cut‐off values of 1.0 and 1.2 were applied in additional analyses. Prevalences were also examined for subgroups according to sex, age, body mass index (BMI), education level, appetite, living status, and recent weight loss.
Results
The study sample comprised 8107 older persons. Mean ± standard deviation protein intake ranged from 64.3 ± 22.3 (UK) to 80.6 ± 23.7 g/d the Netherlands (cohort) or from 0.94 ± 0.38 (USA) to 1.17z ± 0.30 g/kg aBW/d (Italy) when related to BW. The overall pooled prevalence of protein intake below recommended was 21.5% (95% confidence interval: 14.0–30.1), 46.7% (38.3–55.3), and 70.8% (65.1–76.3) using the 0.8, 1.0, and 1.2 cut‐off value, respectively. A higher prevalence was observed among women, individuals with higher BMI, and individuals with poor appetite. The prevalence differed only marginally by age, education level, living status, and recent weight loss.
Conclusions
In community‐dwelling older adults, the prevalence of protein intake below the current recommendation of 0.8 g/kg aBW/d is substantial (14–30%) and increases to 65–76% according to a cut‐off value of 1.2 g/kg aBW/d. To what extent the protein intakes are below the requirements of these older people warrants further investigation.
Early identification of older people at risk of falling is the cornerstone of fall prevention. Many fall prediction tools exist but their external validity is lacking. External validation is a ...prerequisite before application in clinical practice. Models developed with electronic health record (EHR) data are especially challenging because of the uncontrolled nature of routinely collected data. We aimed to externally validate our previously developed and published prediction model for falls, using a large cohort of community-dwelling older people derived from primary care EHR data.
Retrospective analysis of a prospective cohort drawn from EHR data.
Pseudonymized EHR data were collected from individuals aged ≥65 years, who were enlisted in any of the participating 59 general practices between 2015 and 2020 in the Netherlands.
Ten predictors were defined and obtained using the same methods as in the development study. The outcome was 1-year fall and was obtained from free text. Both reproducibility and transportability were evaluated. Model performance was assessed in terms of discrimination using the area under the receiver operating characteristic curve (ROC-AUC), and in terms of calibration, using calibration-in-the-large, calibration slope and calibration plots.
Among 39,342 older people, 5124 (13.4%) fell in the 1-year follow-up. The characteristics of the validation and the development cohorts were similar. ROC-AUCs of the validation and development cohort were 0.690 and 0.705, respectively. Calibration-in-the-large and calibration slope were 0.012 and 0.878, respectively. Calibration plots revealed overprediction for high-risk groups in a small number of individuals.
Our previously developed prediction model for falls demonstrated good external validity by reproducing its predictive performance in the validation cohort. The implementation of this model in the primary care setting could be considered after impact assessment.
Purpose To critically appraise and compare the measurement properties of the original versions of neckspecific questionnaires. Methods Bibliographic databases were searched for articles concerning ...the development or evaluation of the measurement properties of an original version of a selfreported questionnaire, evaluating pain and/or disability, which was specifically developed or adapted for patients with neck pain. The methodological quality of the selected studies and the results of the measurement properties were critically appraised and rated using a checklist, specifically designed for evaluating studies on measurement properties. Results The search strategy resulted in a total of 3,641 unique hits, of which 25 articles, evaluating 8 different questionnaires, were included in our study. The Neck Disability Index is the most frequently evaluated questionnaire and shows positive results for internal consistency, content validity, structural validity, hypothesis testing, and responsiveness, but a negative result for reliability. The other questionnaires show positive results, but the evidence for each measurement property is mostly limited, and at least 50% of the information on measurement properties per questionnaire is lacking. Conclusions Our findings imply that studies of high methodological quality are needed to properly assess the measurement properties of the currently available questionnaires. Until high quality studies are available, we recommend using these questionnaires with caution. There is no need for the development of new neck-specific questionnaires until the current questionnaires have been adequately assessed.
Methodological shortcomings in prognostic modeling for patients with spinal disorders are highly common. This general commentary discusses methodological challenges related to the specific nature of ...this field. Five specific methodological challenges in prognostic modeling for patients with spinal disorders are presented with their potential solutions, as related to the choice of study participants, purpose of studies, limitations in measurements of outcomes and predictors, complexity of recovery predictions, and confusion of prognosis and treatment response. Large studies specifically designed for prognostic model research are needed, using standard baseline measurement sets, clearly describing participants’ recruitment and accounting and correcting for measurement limitations.
Metabolic tumor volume (MTV) is a promising biomarker of pretreatment risk in diffuse large B-cell lymphoma (DLBCL). Different segmentation methods can be used that predict prognosis equally well but ...give different optimal cutoffs for risk stratification. Segmentation can be cumbersome; a fast, easy, and robust method is needed. Our aims were to evaluate the best automated MTV workflow in DLBCL; determine whether uptake time, compliance or noncompliance with standardized recommendations for
F-FDG scanning, and subsequent disease progression influence the success of segmentation; and assess differences in MTVs and discriminatory power of segmentation methods.
One hundred forty baseline
F-FDG PET/CT scans were selected from U.K. and Dutch studies on DLBCL to provide a balance between scans at 60 and 90 min of uptake, parameters compliant and noncompliant with standardized recommendations for scanning, and patients with and without progression. An automated tool was applied for segmentation using an SUV of 2.5 (SUV2.5), an SUV of 4.0 (SUV4.0), adaptive thresholding (A50P), 41% of SUV
(41%), a majority vote including voxels detected by at least 2 methods (MV2), and a majority vote including voxels detected by at least 3 methods (MV3). Two independent observers rated the success of the tool to delineate MTV. Scans that required minimal interaction were rated as a success; scans that missed more than 50% of the tumor or required more than 2 editing steps were rated as a failure.
One hundred thirty-eight scans were evaluable, with significant differences in success and failure ratings among methods. The best performing was SUV4.0, with higher success and lower failure rates than any other method except MV2, which also performed well. SUV4.0 gave a good approximation of MTV in 105 (76%) scans, with simple editing for a satisfactory result in additionally 20% of cases. MTV was significantly different for all methods between patients with and without progression. The 41% segmentation method performed slightly worse, with longer uptake times; otherwise, scanning conditions and patient outcome did not influence the tool's performance. The discriminative power was similar among methods, but MTVs were significantly greater using SUV4.0 and MV2 than using other thresholds, except for SUV2.5.
SUV4.0 and MV2 are recommended for further evaluation. Automated estimation of MTV is feasible.
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