Clinical Indoor Running Gait Analysis May Not Approximate Outdoor Running Gait Based on Novel Drone Technology

Background: Traditional running gait analysis is limited to artificial environments, but whether treadmill running approximates overground running is debated. This study aimed to compare treadmill gait analysis using fixed video with outdoor gait analysis using drone video capture. Hypothesis: Measured kinematics would be similar between natural outdoor running and traditional treadmill gait analysis. Study Design: Crossover study. Level of Evidence: Level 2. Methods: The study population included cross-country, track and field, and recreational athletes with current running mileage of at least 15 km per week. Participants completed segments in indoor and outdoor environments. Indoor running was completed on a treadmill with static video capture, and outdoor segments were obtained via drone on an outdoor track. Three reviewers independently performed clinical gait analysis on footage for 32 runners using kinematic measurements with published acceptable intra- and interrater reliability. Results: Of the 8 kinematic variables measured, 2 were found to have moderate agreement indoor versus outdoor, while 6 had fair to poor agreement. Foot strike at initial contact and rearfoot position at midstance had moderate agreement indoor versus outdoor, with a kappa of 0.54 and 0.49, respectively. The remaining variables: tibial inclination at initial contact, knee flexion angle initial contact, forward trunk lean full gait cycle, knee center position midstance, knee separation midstance, and lateral pelvic drop at midstance were found to have fair to poor agreement, ranging from 0.21 to 0.36. Conclusion: This study suggests that kinematics may differ between natural outdoor running and traditional treadmill gait analysis. Clinical Relevance: Providing recommendations for altering gait based on treadmill gait analysis may prove to be harmful if treadmill analysis does not approximate natural running environments. Drone technology could provide advancement in clinical running recommendations by capturing runners in natural environments.

Performance of Automated Telemetry in Diagnosing QT Prolongation in Critically Ill Patients

Background QT prolongation increases the risk of ventricular arrhythmia and is common among critically ill patients. The gold standard for QT measurement is electrocardiography. Automated measurement of corrected QT (QTc) by cardiac telemetry has been developed, but this method has not been compared with electrocardiography in critically ill patients. Objective To compare the diagnostic performance of QTc values obtained with cardiac telemetry versus electrocardiography. Methods This prospective observational study included patients admitted to intensive care who had an electrocardiogram ordered simultaneously with cardiac telemetry. Demographic data and QTc determined by electrocardiography and telemetry were recorded. Bland-Altman analysis was done, and correlation coefficient and receiver operating characteristic (ROC) coefficient were calculated. Results Fifty-one data points were obtained from 43 patients (65% men). Bland-Altman analysis revealed poor agreement between telemetry and electrocardiography and evidence of fixed and proportional bias. Area under the ROC curve for QTc determined by telemetry was 0.9 (P < .001) for a definition of prolonged QT as QTc ≥ 450 milliseconds in electrocardiography (sensitivity, 88.89%; specificity, 83.33%; cutoff of 464 milliseconds used). Correlation between the 2 methods was only moderate (r = 0.6, P < .001). Conclusions QTc determination by telemetry has poor agreement and moderate correlation with electrocardiography. However, telemetry has an acceptable area under the curve in ROC analysis with tolerable sensitivity and specificity depending on the cutoff used to define prolonged QT. Cardiac telemetry should be used with caution in critically ill patients.

Value of echocardiography using knowledge-based reconstruction in determining right ventricular volumes in pulmonary sarcoidosis: comparison with cardiac magnetic resonance imaging

Background Right ventricular (RV) dysfunction in sarcoidosis is associated with adverse outcomes. Assessment of RV function by conventional transthoracic echocardiography (TTE) is challenging due to the complex RV geometry. Knowledge-based reconstruction (KBR) combines TTE measurements with three-dimensional coordinates to determine RV volumes. Purpose The aim of this study was to investigate the accuracy of TTE-KBR compared to the gold standard cardiac magnetic resonance imaging (CMR) in determining RV dimensions in pulmonary sarcoidosis. Methods Pulmonary sarcoidosis patients prospectively received same-day TTE and TTE-KBR. If performed, CMR within three months after TTE-KBR was used as reference standard. Outcome parameters included RV end-diastolic volume (RVEDV), end-systolic volume (RVESV), stroke volume (RVSV) and ejection fraction (RVEF). Results 282 patients underwent same day TTE and TTE-KBR. In total, 122 patients received a CMR within 90 days of TTE and were included. TTE-KBR measured RVEDV and RVESV showed strong correlation with CMR measurements (R=0.73, R=0.76), while RVSV and RVEF correlated weakly (R=0.46, R=0.46). Bland-Altman analyses (mean bias ±95% limits of agreement), showed good agreement for RVEDV (ΔRVEDVKBR-CMR, 5.67±55.4mL), while RVESV, RVSV and RVEF showed poor agreement (ΔRVESVKBR-CMR, 21.6±34.1mL; ΔRVSVKBR-CMR, −16.1±42.9mL; ΔRVEFKBR-CMR, −12.9±16.4%). Image quality, time to CMR and learning curve showed no impact. Conclusions TTE-KBR is convenient and shows good agreement with CMR for RVEDV. However, there is poor agreement for RVESV, RVSV and RVEF. The use of TTE-KBR does not seem to provide additional value in the determination of RV dimensions in pulmonary sarcoidosis patients. FUNDunding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): ZonMW (The Netherlands Organisation for Health Research and Development) Figure 1. Correlation plots Figure 2. Bland-Altman plots

P035 Is the Grael oximetry averaging time interchangeable with a Masimo pulse oximeter algorithm in polysomnography?

Compumedics recording software (Grael V2) for polysomnography (PSG) calculates SpO2 values using a 3-heartbeat long averaging window. This is derived from the ECG and thus introduces variability in the averaging time that is dependent on the heart rate. Little is known about the effect this has on the common oximetry metrics used in PSG interpretation. This study explorer the interchangeability of the Grael V2 inbuilt 3-beat averaging algorithm with a short averaging window of 2 - 4 seconds using a Masimo Radical 7 pulse oximeter during a PSG. SpO2 data were collected from 2 oximeter probes (Grael and Radical 7) both attached to a patient’s fingers. After SpO2 artifacts were removed, the following SpO2 parameters from each oximeter were generated: mean sleep SpO2, oxygen desaturation index (ODI) using 2%, 3% and 4% drop in SpO2 in sleep, total sleep time (TST) with SpO2 < 90% and < 80% as well as time spent < SpO2 88% in minutes. 88 sleep studies were included in the data collection. For ODI2%, 3% and 4%, bias (95% limits of agreement) values were -0.75 events/hr (9.99 to -11.49 events/hr), -0.74 events/hr (10.00 - -11.49 events/hr) and -0.20 events/hr (8.45 - -8.86 events/hr) respectively. There was no significant difference between measurements except for the mean sleep SpO2 values, p < .001. Although no bias found between measurements, there was poor agreement between the algorithms as demonstrated by the wide 95% limits of agreement suggesting that the two oximeter devices are not interchangeable.

Development of a clinically useful tool for Prakriti assessment

Introduction: Prakriti assessment is of fundamental importance for research and standardization of clinical practice. The available tools for prakriti assessment are not intended to be used in a clinical setting, which demands a short and clinically flexible one. Methods: 3 selected tools were compared with a newly developed questionnaire. These were administered first in 100 healthy volunteers. Agreement analysis between these tools were done. The validation process was completed by running the new tool together with TNMC questionnaire in 150 more individuals who have some doshavriddhi. The results were discussed in an FGD involving clinicians and faculties. Results: The new tool has shown fair agreement with Ayusoft (kappa 0.434 and Spearman correlation 0.506) and TNMC (kappa 0.429 and Spearman correlation 0.454) questionnaires. And it showed week agreement with self-assessment tool (kappa 0.214 and Spearman correlation 0.407). Meanwhile self-assessment tool has poor agreement with both Ayusoft (kappa 0.172 and Spearman correlation 0.279) and TNMC (kappa 0.175 and Spearman correlation 0.244). Reliability was tested in a total of 250 individuals and a Cronbach’s alpha of 0.524 was obtained. Factor analysis was also done. In this total dataset, the new tool showed better agreement with TNMC questionnaire (kappa 0.581 and Spearman correlation 0.442). Conclusion: These results show that the new tool has potency to be run in large scale to study more variability among patients. This will add to the standardization of Ayurvedic diagnostic, prognostic and therapeutic fields.

Evaluation and Comparison of Self-Made and Commercial Calibration Markers for Radiographic Magnification Correction in Veterinary Digital Radiography

Introduction Magnification error is always present in radiography and calibration is necessary, if high accuracy is required in pre-surgical planning. The goal of this study was to verify the use of self-made markers and calibration techniques and to establish guidelines for magnification correction. Methods We evaluated and compared spherical and linear markers of different sizes with focus on practicability, accuracy and precision. Markers were placed on foam pads or attached to flexible arms. Results Vertical marker deviation of 1 cm from the anatomical reference point corresponded to ∼1% of magnification error in our setting. Marker placement along the horizontal plane showed no significant magnification in the periphery of the radiograph. All markers showed good accuracy and the commercial spherical marker with a flexible segment arm had the best results regarding practicability. Discussion Our study suggests that marker type is not solely responsible for usability and accuracy but also the type of fixation. In the absence of a calibration marker, calculation of the magnification factor using a measurement tape during radiography is equally reliable. Use of a fixed averaged calculated calibration factor showed poor agreement compared with the marker calibration, probably due to variability in size of the animals. In conclusion, if precision matters, use of a calibration marker, which could be purchased or self-made, is advised.

Significance and agreement between obesity anthropometric measurements and indices in adults: a population-based study from the United Arab Emirates

Background The rates of overweight and obese adults in the United Arab Emirates (UAE) have increased dramatically in recent decades. Several anthropometric measurements are used to assess body weight status. Some anthropometric measurements might not be convenient to use in certain communities and settings. The objective of this study was to assess the agreement of four anthropometric measurements and indices of weight status and to investigate their associations with cardiometabolic risks. Methods The study design was a cross-section population-based study. Adults living in the Northern Emirates were surveyed. Fasting blood samples, blood pressure readings and anthropometric measurements were also collected. Results A total of 3531 subjects were included in this study. The prevalence of obesity/overweight was 66.4% based on body mass index (BMI), 61.7% based on waist circumference (WC), 64.6% based on waist–hip ratio (WHR) and 71% based on neck circumference (NC). There were moderate agreements between BMI and WC and between WC and WHR, with kappa (k) ranging from 0.41 to 0.60. NC showed poor agreement with BMI, WC and WHR, with k ranging from 0 to 0.2. Overweight and obesity based on BMI, WC and WHR were significantly associated with cardiometabolic risks. Conclusion Overall, there was a moderate to a poor agreement between BMI, WC, WHR and NC. Particularly, NC showed poor agreement with BMI, WC and WHR. BMI and WC showed better performance for identifying cardiometabolic risks than WHR and NC.

Association and Agreement between Reactive Strength Index and Reactive Strength Index-Modified Scores

Since the reactive strength index (RSI) and reactive strength index-modified (RSI-mod) share similar nomenclature, they are commonly referred as interchangeable measures of agility in the sports research literature. The RSI and RSI-mod are most commonly derived from the performance of depth jumping (DJ) and countermovement jumping (CMJ), respectively. Given that DJ and CMJ are plyometric movements that differ materially from biomechanical and neuromotor perspectives, it is likely that the RSI and RSI-mod measure distinct aspects of neuromuscular function. The purpose of this investigation was to evaluate the association and agreement between RSI and RSI-mod scores. A mixed-sex sample of NCAA division I basketball athletes (n = 21) and active young adults (n = 26) performed three trials of DJ from drop heights of 0.51, 0.66, and 0.81 m and three trials of countermovement jumping. Using 2-dimensional videography and force platform dynamometry, RSI and RSI-mod scores were estimated from DJ and CMJ trials, respectively. Linear regression revealed moderate associations between RSI and RSI-mod scores (F = 11.0–38.1; R2 = 0.20–0.47; p < 0.001–0.001). Bland–Altman plots revealed significant measurement bias (0.50–0.57) between RSI and RSI-mod scores. Bland–Altman limit of agreement intervals (1.27–1.51) were greater than the mean values for RSI (0.97–1.05) and RSI-mod (0.42) scores, suggesting poor agreement. Moreover, there were significant performance-dependent effects on measurement bias, wherein the difference between and the mean of RSI and RSI-mod scores were positively associated (F = 77.2–108.4; R2 = 0.63–0.71; p < 0.001). The results are evidence that the RSI and RSI-mod cannot be regarded as interchangeable measures of reactive strength.

A data multiverse analysis investigating non-model based SCR quantification approaches

Data inevitably need to be processed, typically involving multiple decision nodes with decisions often being equally justifiable. Electrodermal signals are the most common outcome measure in fear conditioning research, but response quantification approaches vary strongly. It remains an open question whether different approaches result in convergent results. Using fear conditioning research as a case example, we identified that baseline-correction (BLC) and trough-to-peak (TTP) quantification are used most frequently in the literature. Furthermore, heterogeneity of specifications in BLC formulas was observed, i.e., within the pre-CS baseline window and the post-CS peak detection or mean detection window. Here we systematically scrutinize the robustness of results when applying different processing methods to one pre-existing dataset (N= 118). The study was pre-registered. We report high agreement between different BLC approaches for US and CS+ trials, but moderate to poor agreement for CS- trials. Furthermore, a specification curve of the main effect of CS discrimination during fear acquisition training from all potential and reasonable combinations of specifications (N=150) and a prototypical TTP approach indicates that resulting effect sizes are largely comparable. Crucially, however, we show that BLC approaches often misclassify the peak SCR - particularly for CS- trials, which leads to a stimulus-specific bias and challenges for post-processing and replicability. Lastly, we investigate how physiologically implausible (negative) skin conductance values in BLC appearing most frequently for CS- (CS- &gt; CS+ &gt; US), correspond to in TTP quantification. We discuss the results in terms of robustness and replicability and provide insights into challenges, opportunities, and implications.

To what extent do medication experts agree on diagnoses derived from psychotropic medication prescribed for children and adolescents in a state Medicare database?

This study evaluated the extent to which psychotropic medication experts agreed on psychiatric/behavior diagnoses derived from 30 individuals’ psychotropic medication regimens. Three medication experts reviewed the medication regimens and inferred one or more diagnoses based on the medication listed. Thereafter, we used kappa statistical analyses and category-by-category analyses to evaluate agreement of diagnoses (a) across all three reviewers for two time points (separated by 8 to 14 months) covered by each data set, (b) across each pairing of reviewers at the two time points, and (c) within each reviewer across both time points. Between-reviewer kappa statistical analyses of first- and last-regimen data yielded only five instances with excellent agreement and 13 instances of poor agreement. All remaining instances indicated various levels of disagreement. Similarly, within-expert kappa statistical analyses showed two instances with excellent agreement, four instances with poor agreement, and the remaining instances with various levels of disagreement. Overall, the highest kappa values were attached to low-count regimens, while most scores, regardless of medication count, were low and indicated potential disagreement. The category-by-category analyses yielded similar results. A secondary, conditional analysis revealed higher agreements between and within reviewers when medication regimens contained psychotropic medications typically prescribed to individuals diagnosed with Attention Deficit Hyperactivity Disorder.