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Background: Point‐of‐care (POC) biochemistry analyzers are widely used in small animal clinical practice but infrequently independently assessed for performance. Objective: To assess the performance of two current model point‐of‐care biochemistry analyzers (Heska Element DC and IDEXX Catalyst) compared with a commercial laboratory analyzer (Cobas 8000). Methods: One hundred twenty‐one cats from a feline hospital population were sampled with plasma results from a single lithium heparin tube assessed on all three analyzers. Plasma biochemistry results from each POC analyzer were compared with the commercial laboratory analyzer using Bland–Altman difference plots and by determining whether the limits of agreement (LOAs) (95% of differences) fell within various quality goals after correcting for inherent bias. Results: Only 7 of 14 analytes on the Heska analyzer and 2 analytes on the IDEXX analyzer attained the most stringent LOA quality goal, which was being within desirable total error based on biologic variation (TEdes). The number of analytes achieving quality goals increased with less stringent standards such as American Society of Veterinary Clinical Pathologists allowable total error (ASVCP TEA) guidelines or if <95% of clinical comparisons reaching these quality goals is considered acceptable. Widespread bias was found between both POC analyzers and the commercial laboratory analyzer. Conclusions: The performance of both POC biochemistry analyzers was variable compared with a commercial laboratory analyzer. Performance goals were only able to be attained after the bias for each analyzer was accounted for by offsetting the LOAs and quality goals set by the mean bias for each analyte on each analyzer. [ABSTRACT FROM AUTHOR]

This study aimed to develop the ‘Healthy Eating Index for Older People’ (the index), based on New Zealand dietary guidelines, and measures the validity and reproducibility of a food frequency questionnaire (FFQ) to derive the index scores in older adults. In Auckland, New Zealand, participants (community-dwelling adults aged 65–74 years, [n = 273, 36% male]) completed a 109-item FFQ administered one month apart (FFQ1, FFQ2), with a four-day food record (4-DFR) collected in between. Adherence to the guidelines was scored using the index, comprising a total score (maximum = 100) and two sub-scores: adequacy (maximum = 60) and moderation (maximum = 40). A comparison of FFQ1 and FFQ2 determined reproducibility, and FFQ1 and 4-DFR determined validity. Higher index scores (from FFQ1) were associated with higher intakes of protein, fibre, vitamins and minerals and lower intakes of alcohol and saturated fats (nutrients from 4-DFR) after adjusting for age and sex (all p < 0.001). Total index and sub-indices correlation coefficients ranged from 0.42 to 0.77 (all p < 0.001); weighted kappa values ranged from 0.35 to 0.67; and mean differences were all p < 0.05). The index applied to the FFQ demonstrated good construct validity and reproducibility. Relative and absolute validity were acceptable, though caution is required when using the absolute sub-index scores. The index is suitable for measuring total diet quality in older New Zealand adults.

Fortification of edible oil with vitamin A is a widely adopted intervention to minimize the effects of vitamin A deficiency in vulnerable groups and mitigate some of its deleterious consequences. Regulatory monitoring is an important prerequisite to ensure that the fortification program is implemented effectively. Standard laboratory analysis methods for vitamin A in oils to assess adequate addition levels remain expensive and time-consuming. Portable testing devices are relatively less expensive in terms of capital investment and cost per test. However, the reliability of results needs to be assured to ensure acceptability and confidence. This study compared a portable device to high-performance liquid chromatography (HPLC) in terms of quantification of vitamin A in both spiked and commercially fortified oils. Nine oils (soybean, palm, cottonseed, rapeseed, corn, peanut, coconut, sunflower, and rice bran oils) were selected and spiked with retinyl palmitate at six different concentrations, and 112 commercially fortified oils were quantified for their vitamin A content using both methods. A good indicator of intra-day and inter-day repeatability (< 10% CV) was obtained for the measurement of vitamin A in the spiked oils for both methods, which denotes a high agreement between them. Vitamin A recoveries were 97–132% for HPLC and 74–127% for the portable device. A strong positive correlation, r = 0.88, is observed between the two methods for the quantification of vitamin A in the commercially fortified oils. The portable device provides a relatively low-cost, quick, and user-friendly alternative to HPLC. [ABSTRACT FROM AUTHOR]

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson's correlation coefficient (r) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method. [ABSTRACT FROM AUTHOR]

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson’s correlation coefficient (r) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method.

Bland-Altman plots can be useful in paired data settings such as measurement-method comparison studies. A Bland-Altman plot has differences, percentage differences, or ratios on the y axis and a mean of the data pairs on the x axis, with 95% limits of agreement indicating the central 95% range of differences, percentage differences, or ratios. This range can vary with the mean. We introduce the community-contributed blandaltman command, which uniquely in Stata can 1) create Bland-Altman plots featuring ratios in addition to differences and percentage differences, 2) allow the limits of agreement for ratios and percentage differences to vary as a function of the mean, and 3) add confidence intervals, prediction intervals, and tolerance intervals to the plots. [ABSTRACT FROM AUTHOR]

High magnitude loading from performing resistance-based exercise has been found to improve tendon strength and reduce symptoms of Achilles tendinopathy (AT) but is difficult to quantify without specialist equipment. Here, we assess the validity and reliability of a novel AT rehabilitation tool (the "PhysViz" system) compared to a "gold-standard" dynamometer for assessing plantarflexion maximal voluntary isometric contractions (MVIC). 41 participants aged 18–60 completed the study. A within-subject test–retest study design was used to examine and compare the validity and reliability of the two systems during plantarflexion MVICs. Test – retest reliability of the two methods were determined by calculating intra-class correlation coefficients (ICCs) and 95% confidence intervals. Method agreement was assessed with Bland – Altman Limits of Agreement (LoA) analysis. The PhysViz demonstrated excellent test–retest reliability; ICC, SEM and MDC were numerically comparable to the dynamometer (ICC 0.93 vs. 0.92; SEM 2.01 vs. 2.95 kg and MDC 5.58 vs. 8.18 kg, respectively), indicating that the novel system is valid and reliable for measuring plantarflexor MVICs. Future studies should address its utility in monitoring AT rehabilitative loading remotely over time. [ABSTRACT FROM AUTHOR]

Purpose: To compare axial length (AL) and corneal radius (CR) measured with the Oculus Myopia Master and the Zeiss IOLMaster 700, and cycloplegic refractive error measured with the Myopia Master and the Huvitz Auto Ref/Keratometer (HRK‐8000A). Methods: The study included both eyes of 74 participants (16 male), with a mean (SD) age of 22.8 (3.7) years. The parameters indicated were measured under cycloplegia with these instruments: Myopia Master (AL, CR and refractive error), IOLMaster 700 (AL and CR) and HRK‐8000A (refractive error and CR). Bland–Altman plots with mixed effects 95% limits of agreement (LoA) and corresponding 95% confidence intervals were used to assess the agreement in ocular biometry between the Myopia Master and the IOLMaster 700, and for refractive error between the Myopia Master and the HRK‐8000A. Results: The analysis included 139 eyes, of which 52 were myopic (spherical equivalent refractive error, SER ≤ −0.50 D), 32 emmetropic and 55 hyperopic (SER ≥ 0.50 D). The 95% LoA for AL between the Myopia Master and IOLMaster 700 was −0.097 to 0.089 mm. There was no mean difference in AL [mean (SD) = −0.004 (0.047) mm, p = 0.34]. There was a significant difference in mean CR, with that measured with the Myopia Master being flatter than that found with the IOLMaster 700 [0.035 (0.028) mm, p < 0.001]. The 95% LoA for CR was −0.02 to 0.09 mm. Compared with HRK‐8000A, the Myopia Master measured a significantly more negative SER [−0.19 (0.33) D, p < 0.001], with 95% LoA of −0.86 to 0.46 D. Conclusion: The LoA for measurements of SER, CR and AL when comparing the Myopia Master with the HRK‐8000A and the IOLMaster 700 were wider than deemed acceptable for making direct comparisons. This indicates that the instruments cannot be used interchangeably in clinical practice or research. [ABSTRACT FROM AUTHOR]

Recently, a new statistical methodology to assess the bias and precision of a new measurement method, which circumvents the deficiencies of the Bland and Altman (1986, Lancet 327: 307–310) limits of agreement method, was developed by Taffé (2018, Statistical Methods in Medical Research 27: 1650–1660). Later, the methodology was extended to assess the agreement. In addition, to allow for inferences, simultaneous confidence bands around the bias, precision, and agreement lines were developed (Taffé, 2020, Statistical Methods in Medical Research 29: 778–796). The goal of this article is to introduce the extended biasplot command, which implements these latest developments, and to illustrate its use by applying it to simulated data included with the command. Note that the Taffé method assumes that there are several measurements by one of the two measurement methods and possibly as few as one measurement by the other for each individual. The repeated measurements need not come from the reference standard but from any of the two measurement methods. This is a great advantage because it may sometimes be more feasible to gather repeated measurements either with the reference standard or the new measurement method. [ABSTRACT FROM AUTHOR]

Background Automatic noninvasive oscillometric blood pressure (NIBP) devices measure mean arterial pressure (MAP); systolic and diastolic blood pressure (SBP, DBP) are algorithmically derived from MAP. The most invalid NIBP measure is SBP, yet stroke practitioners use it to manage blood pressure (BP) in accordance with thrombolysis guidelines. We determined agreement between SBP, DBP, and MAP measured manually and by NIBP in patients treated with alteplase. Methods A multisite prospective observational study of NIBP and manual BP agreement was conducted in patients treated with alteplase immediately after bolus and infusion initiation using methods established in guidelines for the assessment of device agreement. Dual auscultatory stethoscopes were used by 2 investigators to ensure agreement with each manual BP variable and MAP was calculated using the standard formula for manual BP measures. Data were analyzed using Bland–Altman analyses and Lin concordance correlation coefficient. Results A total of 7 hospitals participated, collecting 5 sets of manual/NIBP BPs in 95 patients treated with alteplase (475 paired measures). Range in limits of agreement were SBP: −28.91 to 21.41 mmHg with Lin's concordance correlation coefficient 0.8; DBP: −21.0 to 19.0 mmHg with Lin's concordance correlation coefficient 0.69; and MAP: −27.5 to 16.5 mmHg with Lin's concordance correlation coefficient 0.7. There was no difference in device agreement by BP device manufacturer brand. Differences in SBP, DBP, and MAP between NIBP and manual sphygmomanometry failed to reach guideline recommendations requiring 80% of measures to fall within a 5 mmHg difference and 95% of measures to fall within a 10 mmHg difference. Conclusion NIBP devices produce significantly different BP measures then manual sphygmomanometry auscultated BP. Because NIBP devices rely on the MAP and do not directly measure SBP and DBP, definition of what constitutes safe MAP boundaries in patients treated with alteplase should be determined when automatic BP measurement is used in clinical practice.

PurposeMeibomian gland contrast may be a potential indicator of gland health, especially among isotretinoin users. We aimed to develop a repeatable and reliable method for measuring Meibomian gland contrast from meibography images.MethodsLower lid (LL) and upper lid (UL) meibography were captured with the OCULUS Keratograph 5M (OCULUS, Inc) at 2 visits under the following 4 conditions: face centered with room lights on (C), left-turned face (L), right-turned face (R), and face centered with room lights off (CLO). Contrast was measured with Fiji (v2.0.0-rc-59). Coefficient of repeatability and limits of agreement (LOA) were determined using Bland-Altman plots.ResultsA total of 512 meibography images from 16 subjects (age ± SD = 24.8 ± 5.2 years; 13 female patients) were collected. Coefficient of repeatability between visits was 10.5 for UL and 14.9 for LL. Lower and upper LOA, respectively, for UL, compared with condition C, were -10.9 [95% confidence interval (CI), -13.5 to -8.3] and 6.2 (95% CI, 3.6-8.8) for L; -11.0 (95% CI, -13.8 to -8.1) and 7.0 (95% CI, 4.2-9.8) for R; and -9.0 (95% CI, -11.6 to -6.5) and 7.2 (95% CI, 4.7-9.8) for CLO. Lower and upper LOA, respectively, for LL, compared with condition C, were -18.1 (95% CI, -22.6 to -13.5) and 11.0 (95% CI, 6.5-15.5) for L; -15.3 (95% CI, -19.2 to -11.3) and 9.9 (95% CI, 6.0-13.9) for R; and -12.0 (95% CI, -15.1 to -8.8) and 8.2 (95% CI, 5.0-11.3) for CLO.ConclusionsMeibomian gland contrast is a repeatable and reliable measure for changes in Meibomian gland contrast greater than 11 in the UL and 18 in the LL.

This study aimed to investigate the reproducibility of pupil size measurements over time and between reading methods when comparing human-assisted reading to automated reading. Pupillary data were analyzed on a subset of myopic children enrolled in a multicenter randomized clinical trial on myopia control with low-dose atropine. Pupil size measurements were obtained prior to randomization at two time points (screening and baseline visits) using a dedicated pupillometer under mesopic and photopic conditions. A customized algorithm was built to perform automated readings, allowing comparisons between human-assisted and automated readings. Reproducibility analyses followed the principles of Bland and Altman and included the calculation of the mean difference between measurements and limits of agreement (LOA). We included 43 children. Mean (standard deviation) age was 9.8 (1.7) years and 25 (58%) children were girls. Using human-assisted readings, reproducibility over time showed mesopic mean difference of 0.02 mm with LOA from −0.87 mm to 0.91 mm, whereas photopic mean difference was −0.01 mm with LOA from −0.25 mm to 0.23 mm. Reproducibility between human-assisted and automated readings was also higher under photopic conditions, with mean difference of 0.03 mm and LOA from −0.03 mm to 0.10 mm at screening and mean difference of 0.03 mm and LOA from −0.06 mm to 0.12 mm at baseline. Using a dedicated pupillometer, we found that examinations performed under photopic conditions demonstrated higher reproducibility over time and between reading methods. We speculate whether mesopic measurements are sufficiently reproducible to be monitored over time. Furthermore, photopic measurements may be of greater relevance when evaluating the side effects of atropine treatment, such as photophobia. [ABSTRACT FROM AUTHOR]

In this study, we have further extended the methodology proposed, first, by Lin et al. (2002) and, later, extended by Stevens et al. (2017, 2018), on the coverage probability/probability of agreement, by relaxing the strong parametric assumptions regarding the distribution of the latent trait and developing inference methods allowing to compute both pointwise and simultaneous confidence bands. The methodology requires repeated measurements by at least one of the two measurement methods and accommodates heteroscedastic measurement errors. It performs often very well even when one has only one measurement by one of the two measurement methods and at least five repeated measurements from the other. It circumvents some of the deficiencies of the Bland & Altman limits of agreement method and provides a more direct assessment of the agreement level. [ABSTRACT FROM AUTHOR]

A variety of noninvasive instruments have been introduced in the literature to assess thoracic curvature, although the psychometric properties of many of these instruments have not been satisfactory. Photogrammetry is a safe, accessible, and reliable technique. However, its validity in adolescents with hyperkyphosis has not yet been investigated. To investigate the validity and test–retest reliability of photogrammetry in the measurement of thoracic kyphosis among adolescents with hyperkyphosis. Fifty adolescents with hyperkyphosis participated in this study. The kyphosis angle was measured using radiography and photogrammetry. A two-way random model of the intraclass correlation coefficient (ICC2,3) was used to estimate relative reliability. Absolute reliability was assessed by calculating the standard error of the measurements (SEM) and the minimal detectable change (MDC). Pearson's correlation coefficient was calculated to evaluate the validity of the photogrammetry technique. Bland–Altman plots were plotted to determine the agreement between the angles measured by radiography and photogrammetry. There was a strong correlation between the values obtained from the photogrammetry technique and those from the radiography method (r = 0.94). The 95% limits of agreement indicated that the photogrammetric measurements of thoracic kyphosis angle might range from 2.4 degrees greater to 10.2 degrees lower than the Cobb radiographic angle. Photogrammetric measurements of thoracic kyphosis showed excellent test–retest reliability (ICC = 0.97; SEM = 1.67; MDC = 4.62). High reliability of photogrammetry technique and its strong correlation with radiographic Cobb angle support the application of this technique for the measurement of thoracic kyphosis in clinical practice. [ABSTRACT FROM AUTHOR]

Abstract Background The Bland-Altman plot with the limits of agreement has been widely used as an absolute index for assessing test-retest reliability or reproducibility between two measurements. We have observed that in the settings where the relative index such as concordance correlation coefficient (CCC) or intraclass correlation coefficient is employed, the limits of agreement approach may be inconsistent with the scaled index. Particularly, the broad width of the limits of agreement may indicate a lack of agreement when the two measurements are highly concordant but an acceptable difference is not known and the common variance of the data is large. This research aims to create a novel, CCC-based guidance for graphical evaluation of reproducibility or reliability. Methods The concordance correlation coefficient is used to create a 100(1-α)% reference band from two measurements. Simulation studies and real examples, including the peak expiratory flow rate data in Bland and Altman’s paper and the test-retest reproducibility data of the Radiomics study, are implemented to assess the use of the reference band. Results In the absence of an acceptable difference between measurements, we found that the limits of agreement may not be consistent with the concordance correlation coefficient. Our simulation study results and real data application show that the proposed method can provide practitioners with a novel graphical evaluation that is consistent with results from the concordance correlation coefficient. Conclusions Our proposed novel scaled index-based guidance can be used for the graphical evaluation of reproducibility or reliability and may have advantages over the limits of agreement in settings where the concordance correlation coefficient is employed.

When evaluating the clinical performance of a medical imaging device, a multi-reader multi-case (MRMC) analysis is usually applied to account for both case and reader variability. For a clinical task that equates to a quantitative measurement, an agreement analysis such as a limits of agreement (LOA) method can be used to compare different measurement methods. In this work, we introduce four types of comparisons; these types differ depending on whether the measurements are within or between readers and within or between modalities. A three-way mixed effect ANOVA model is applied to estimate the variances of individual differences, which is an essential step for estimating LOA. To verify the estimates of LOA, we propose a hierarchical model to simulate quantitative MRMC data. Two simulation studies were conducted to validate both the simulation and the LOA variance estimates. From the simulation results, we can conclude that our estimate of variance is unbiased, and the uncertainty of the estimation drops as the number of readers and cases increases and rises as the value of true variance increases. [ABSTRACT FROM AUTHOR]

Background and Objectives: The Hamilton Depression Rating Scale (HDRS) and Montgomery-Åsberg Depression Rating Scale (MADRS) are both frequently employed to gauge the symptoms of major depressive disorder (MDD). Limited studies have attempted to compare these two scales. The purpose of our study was to compare the HDRS and MADRS scores of the study population as well as to calculate their bias and precision., Methods: An open-label, randomized, three-arm trial was executed on 96 MDD patients. For 16 weeks, participants were put into three groups (in a 1:1:1 ratio) and administered vortioxetine (5-20 mg/day), escitalopram (10-20 mg/day), or vilazodone (20-40 mg/day). Vortioxetine and vilazodone were experimental drugs, while escitalopram acted as a control. Follow-up visits were scheduled at four-week intervals following the first visit. The per-protocol (PP) population had their HDRS and MADRS scores recorded at each visit. We contrasted the MADRS and HDRS scores through the Bland-Altman analysis and Taffé method. The former method generated the limit of agreement (LoA) plot. Moreover, the latter provided the bias, precision, and comparison plots. We prospectively registered our trial in the Clinical Trial Registry of India (CTRI) (2022/07/043808)., Results: We screened 134 individuals, and 109 (81.34%) were qualified. Ninety-six (88.07%) accomplished the 16-week study. The average age was 46.3 ± 6.2 years. The study population had baseline and final HDRS scores of 30.05 ± 1.52 and 14.29 ± 1.51, respectively. The mean MADRS scores at the first and last visits were 35.73 ± 1.47 and 18.08 ± 1.92, respectively. According to the LoA plot, the mean difference between HDRS and MADRS scores was 4.78 (95% CI: 2.61-6.95). As the bias plot indicates, MADRS scores had an estimated differential bias of 3.478 (95% CI: -2.119 to 9.074) and a proportional bias of 0.816 (95% CI: 0.649 to 0.982). The precision plot demonstrated that HDRS scores had lower standard deviation values and a narrower confidence interval than MADRS scores. This meant that the HDRS was more precise. The comparison plot showed that the regression line of the recalibrated MADRS coincided with that of HDRS. The MADRS was effectively recalibrated to remove bias., Conclusion: After 16 weeks of therapy, we noticed substantial drops in HDRS and MADRS scores. The HDRS was proved to be more precise than the analogous MADRS. The MADRS was recalibrated to remove differential and proportional biases., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Research and Ethics Committee, Veer Surendra Sai Institute of Medical Sciences and Research issued approval 029-2022/I-S-T/03. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Santi et al.)

Background Context: Intraoperative stitched O-arm images are commonplace during spinal deformity correction surgeries; however, the accuracy of stitched images for measuring angular measures is unknown.Purpose: To examine the effect of radiographic parallax effect of stitched O-arm images by assessing the regional curve agreement with measurements from computed tomography (CT).Study Design/setting: Experimental radiographic study.Patient Sample: Four whole body cadavers (age: 81±14, sex: 2M/2F) and two fabricated spine model phantoms from surgical cases, one with extreme scoliosis and one normal spine, were utilized.Outcome Measures: The limits of agreement for angular measures between CT (gold-standard) and intraoperative stitched fluoroscopic images were calculated. Further, intra- and inter-rater reliability was measured.Methods: A series of adjacent anterior-posterior and lateral images were acquired cranial to caudal using an O-arm in three table configurations (standard position, off-axis in the coronal plane, and reverse Trendelenburg) and stitched manually. Regional angular measures were extracted, and the limits of agreement were calculated between each table position and CT using a Bland-Altman approach.Results: The observers displayed excellent inter-rater reliability across table positions (range: 0.944-0.989) and intra-rater reliability (0.979-0.995). The limits of agreement results showed a similar and better agreement was observed for the Standard and Reverse Trendelenburg than the Off-Axis position.Conclusions: This work shows reliable regional curvature measurements can be calculated with good agreement with CT in common table positions, but care should be taken to ensure the patient is perpendicular to the X-rays, particularly in the lateral view. [ABSTRACT FROM AUTHOR]

Hematocrit (Hct) values after the initiation of cardiopulmonary bypass (CPB) must be maintained appropriately to avoid perioperative complications. Therefore, an accurate prediction is required. However, the standard prediction equation often results in actual values that are lower than the predicted values. This study aimed to clarify the limits of agreement (LOA) and bias of the prediction equations and investigate better the prediction equations. A retrospective study was performed on adult patients between April 2015 and December 2020. Study 1 included 158 patients, and Study 2 included 55 patients. The primary outcomes were the LOA and bias between the predicted and measured Hct values after the initiation of CPB, and two studies were conducted. In Study 1, total blood volume (TBV) was estimated, and the new blood volume index (BVI) was calculated. BVI was also evaluated for the overall value and gender differences. Therefore, the patient's background was compared by gender differences. In, Study 2 the conventional predicted equation (Eq. 1), the predicted equation using the new BVI (Eq. 2), and the predicted equation using the new BVI including physiological factors in the TBV equation (Eq. 3) were compared. In Study 1, BVI was 53 (44–67) mL/kg. In Study 2, bias ± LOA was − 2.5 ± 6.8% for Eq. 1, 0.1 ± 6.6% for Eq. 2, and 0.4 ± 6.2% for Eq. 3. The new equation is expected to predict the Hct value after the initiation of CPB with better LOA and bias than the conventional equation. [ABSTRACT FROM AUTHOR]

Background: Pulse wave transit time is a novel method of estimating continuous cardiac output (esCCO). Since there are not many studies evaluating esCCO, we compared it with arterial pressure based cardiac output (APCO) method (FloTrac). Methods: In this prospective single-center observational study, we included 50 adult patients planned to undergo supramajor oncosurgeries, where major blood loss and extensive fluid shifts were expected. Cardiac output (CO) measurements were obtained by both methods at five distinct time points, giving us 250 paired readings of stroke volume index (SVI) and cardiac index (CI). We analyzed these readings using Pearson's correlation coefficient and Bland-Altman plots, along with other appropriate statistical tests. Results: There was significant correlation between CI and SVI measured by the esCCO and APCO. Bland-Altman plot analysis for CI showed a bias of -0.44 L/minute/m², precision of 0.74, and the limits of agreement of -1.89 and +1.01, while the percentage error was 46.29%. Bland-Altman analysis for SVI showed a bias -5.07 mL with a precision of 9.36, and the limits of agreement to be -23.4 to +13.28. The percentage error was 46.56%. Conclusion: This study demonstrated that esCCO tended to underestimate the CI to a large degree, particularly while estimating the cardiac output in the lower range. We found that the limits of agreement between two methods were wide, which are not likely to be clinically acceptable. Further studies with larger number of data points, obtained in a similar subset of patients, for cardiac output measurement in the perioperative period will certainly help determine if pulse wave transit time (PWTT) is here to stay (CTRI No.: CTRI/2019/08/020543). [ABSTRACT FROM AUTHOR]

Background: The Bland-Altman plot with the limits of agreement has been widely used as an absolute index for assessing test-retest reliability or reproducibility between two measurements. We have observed that in the settings where the relative index such as concordance correlation coefficient (CCC) or intraclass correlation coefficient is employed, the limits of agreement approach may be inconsistent with the scaled index. Particularly, the broad width of the limits of agreement may indicate a lack of agreement when the two measurements are highly concordant but an acceptable difference is not known and the common variance of the data is large. This research aims to create a novel, CCC-based guidance for graphical evaluation of reproducibility or reliability.Methods: The concordance correlation coefficient is used to create a 100(1-α)% reference band from two measurements. Simulation studies and real examples, including the peak expiratory flow rate data in Bland and Altman's paper and the test-retest reproducibility data of the Radiomics study, are implemented to assess the use of the reference band.Results: In the absence of an acceptable difference between measurements, we found that the limits of agreement may not be consistent with the concordance correlation coefficient. Our simulation study results and real data application show that the proposed method can provide practitioners with a novel graphical evaluation that is consistent with results from the concordance correlation coefficient.Conclusions: Our proposed novel scaled index-based guidance can be used for the graphical evaluation of reproducibility or reliability and may have advantages over the limits of agreement in settings where the concordance correlation coefficient is employed. [ABSTRACT FROM AUTHOR]

The assessment of agreement in method comparison and observer variability analysis of quantitative measurements is usually done by the Bland–Altman Limits of Agreement, where the paired differences are implicitly assumed to follow a normal distribution. Whenever this assumption does not hold, the 2.5% and 97.5% percentiles are obtained by quantile estimation. In the literature, empirical quantiles have been used for this purpose. In this simulation study, we applied both sample, subsampling, and kernel quantile estimators, as well as other methods for quantile estimation to sample sizes between 30 and 150 and different distributions of the paired differences. The performance of 15 estimators in generating prediction intervals was measured by their respective coverage probability for one newly generated observation. Our results indicated that sample quantile estimators based on one or two order statistics outperformed all of the other estimators and they can be used for deriving nonparametric Limits of Agreement. For sample sizes exceeding 80 observations, more advanced quantile estimators, such as the Harrell–Davis and estimators of Sfakianakis–Verginis type, which use all of the observed differences, performed likewise well, but may be considered intuitively more appealing than simple sample quantile estimators that are based on only two observations per quantile.

Background: The Abarquez formula (aVR QRS amplitude x 2.264) + (age x 0.645) has been offered to provide an estimate for LVEF measured by 2D Echo. However, studies aiming to establish agreement between the Abarquez formula and LVEF measured by 2D Echo are lacking. Aims and Objectives: The aim of this study was to compare the LVEF estimated from 12-lead ECG using the Abarquez formula with the LVEF measured using the 2DED in the following subpopulations: 18-35 years old, 36-60 years old, >60 years old, male, and female patients. To compare these two measurements, the limits of agreement (LoA) by Altman and Bland was used. Materials and Methods: Adult patients admitted in the VLMC from January to May 2019 with both a 12-lead ECG and a 2D Echo were included in the study. LVEF from 2D Echo and LVEF estimated using the Abarquez formula were recorded. Comparison of the two measurements was performed by Altman and Bland method using LoA at 95% confidence interval. This analysis was done using Analyse-It Software. Comparison of the mean differences between the two measurement methods was also done using STATA. Results: LVEF estimate using the Abarquez formula was found to significantly differ from LVEF measured using 2D Echo. Conclusions: The Abarquez formula cannot be used as a surrogate for LVEF measure by 2D Echo.

Abstract Background Studies of agreement examine the distance between readings made by different devices or observers measuring the same quantity. If the values generated by each device are close together most of the time then we conclude that the devices agree. Several different agreement methods have been described in the literature, in the linear mixed modelling framework, for use when there are time-matched repeated measurements within subjects. Methods We provide a tutorial to help guide practitioners when choosing among different methods of assessing agreement based on a linear mixed model assumption. We illustrate the use of five methods in a head-to-head comparison using real data from a study involving Chronic Obstructive Pulmonary Disease (COPD) patients and matched repeated respiratory rate observations. The methods used were the concordance correlation coefficient, limits of agreement, total deviation index, coverage probability, and coefficient of individual agreement. Results The five methods generated similar conclusions about the agreement between devices in the COPD example; however, some methods emphasized different aspects of the between-device comparison, and the interpretation was clearer for some methods compared to others. Conclusions Five different methods used to assess agreement have been compared in the same setting to facilitate understanding and encourage the use of multiple agreement methods in practice. Although there are similarities between the methods, each method has its own strengths and weaknesses which are important for researchers to be aware of. We suggest that researchers consider using the coverage probability method alongside a graphical display of the raw data in method comparison studies. In the case of disagreement between devices, it is important to look beyond the overall summary agreement indices and consider the underlying causes. Summarising the data graphically and examining model parameters can both help with this.

Abstract Background Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results Modelled geographical access (P) is generally lower than self-reported access (R), but there is a geography to this relationship. In India and Pakistan, potential access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)]

The comparison of two quantitative measuring devices is often performed with the Limits of Agreement proposed by Bland and Altman in their seminal Lancet paper back in 1986. Sample size considerations were rare for such agreement analyses in the past, but recently several proposals have been made depending on how agreement is to be assessed and the number of replicates to be used. We have summarized recent developments and recommendations in various situations including a distinction between method comparison and observer variability studies. These include current state-of-the-art analysis of and reporting guidelines for agreement studies. General recommendations close the paper. [ABSTRACT FROM AUTHOR]

The correlation coefficient is a statistical measure often used in studies to show an association between variables or to look at the agreement between two methods. In this paper, we will discuss not only the basics of the correlation coefficient, such as its assumptions and how it is interpreted, but also important limitations when using the correlation coefficient, such as its assumption of a linear association and its sensitivity to the range of observations. We will also discuss why the coefficient is invalid when used to assess agreement of two methods aiming to measure a certain value, and discuss better alternatives, such as the intraclass coefficient and Bland–Altman's limits of agreement. The concepts discussed in this paper are supported with examples from literature in the field of nephrology. [ABSTRACT FROM AUTHOR]

This article deals with Bayesian inference in the comparison of measurement systems. Agreement between two systems can be evaluated using data from several measurement systems and using only data from the two systems being compared. With a measurement error model for replicated observations and the probability of agreement to compare measurement systems, we develop methods to compare measurement systems with either homoscedastic or heteroscedastic measurement errors under the Bayesian paradigm via Markov chain Monte Carlo methods. A graphical tool is described to check model adequacy. The methodology developed in the article is illustrated using a real dataset and through simulations. [ABSTRACT FROM AUTHOR]

Purpose: Contrast sensitivity (CS) has been proposed as a potential method for patients to assess their vision at home. The CamBlobs2 contrast sensitivity test is meant to be performed easily in the clinic or at home. The purpose of this study was to determine the intra‐visit coefficient of repeatability of the CamBlobs2 compared with the near Pelli‐Robson test, and the limits of agreement between these two tests on normally‐sighted subjects. Methods: Twenty‐two normally‐sighted subjects (mean age 28 ± 4 years) completed two trials of the near Pelli‐Robson and CamBlobs2 contrast sensitivity tests within a single visit. Tests were performed monocularly on each eye in random order. Pelli‐Robson tests were scored as 0.05 logCS for each letter read correctly after deducting the first triplet. CamBlob2 tests were scored as the highest line where two or fewer blobs were marked correctly. The coefficient of repeatability was determined as 1.96 times the standard deviation of the difference between the two measurements using the same type of chart on the same eye. The limits of agreement between the two tests were evaluated using Bland‐Altman analysis. Results: The mean difference between intra‐visit measurements for both the near Pelli‐Robson and CamBlobs2 was less than 0.05 logCS and the coefficient of repeatability was within ±0.20 log CS for both left and right eyes. The mean ± standard deviation differences between near Pelli‐Robson and CamBlobs2 scores was −0.08 ± 0.08 (limits of agreement: −0.24 to 0.09) for right eyes and −0.05 ± 0.10 (limits of agreement: −0.23 to 0.14) logCS for left eyes based on average measurements. Conclusions: The intra‐visit repeatability of CamBlobs2 was consistent with the near Pelli‐Robson contrast sensitivity test (±0.20 logCS). With a 0.05 correction, the CamBlobs2 scores showed excellent agreement with the near Pelli‐Robson contrast sensitivity test. [ABSTRACT FROM AUTHOR]

Bland-Altman analysis is a very commonly used method in the biomedical research. This method is used to study the agreement between two measurements that are in continuous scale. Although this method is commonly used in medical research, the statistical software packages do not have the menu-driven operation for the Bland-Altman analysis. Hence this paper intends to provide an R function (BA.plot) for Bland-Altman analysis.

Recent advances in machine learning have made automated scoring of learner speech widespread, and yet validation research that provides support for applying automated scoring technology to assessment is still in its infancy. Both the educational measurement and language assessment communities have called for greater transparency in describing scoring algorithms and research evidence about the reliability of automated scoring. This paper reports on a study that investigated the reliability of an automarker using candidate responses produced in an online oral English test. Based on 'limits of agreement' and multi-faceted Rasch analyses on automarker scores and individual examiner scores, the study found that the automarker, while exhibiting excellent internal consistency, was slightly more lenient than examiner fair average scores, particularly for low-proficiency speakers. Additionally, it was found that an automarker uncertainty measure termed Language Quality, which indicates the confidence of speech recognition, was useful for predicting automarker reliability and flagging abnormal speech. [ABSTRACT FROM AUTHOR]

The Bland-Altman method, which assesses agreement via an assessment set constructed by the difference of the measurement variables, has received great attention. Other assessment approaches have been proposed following the same difference-based framework. However, the exact assessment set constructed by the difference is achievable only for measurements with certain joint distributions. To provide a more general assessment framework, we propose two approaches. First, when the measurement distribution is known, we propose a parametric approach that constructs the assessment set through a measure of closeness corresponding to the distribution. Second, when the measurement distribution is unknown, we propose a nonparametric approach that constructs the assessment set through quantile regression. Both approaches quantify the degree of agreement with the presence of both systematic and random measurement errors, and enable one to go beyond the difference-based approach. Results of simulation and data analyses are presented to compare the two approaches. [ABSTRACT FROM AUTHOR]

• The Mxa shows fair reliability in healthy volunteers when based on 3-second averages, both in the supine position and during head-up tilt. • The variance increases during passive standing compared to supine position. • Standard error of measurement and Limits of agreement showed smallest differences when based on 3-second averages. The transcranial Doppler ultrasound-derived mean flow index (Mxa) is widely used for assessing dynamic cerebral autoregulation (dCA) in different clinical populations. This study aimed at estimating the relative and absolute reliability of Mxa in healthy participants in the supine position and during head-up tilt (HUT). Fourteen healthy participants were examined on two separate occasions during which, mean middle cerebral artery blood flow velocity (MCAv), non-invasive blood pressure, and heart rate were continuously recorded in the supine position and during HUT. Mxa was calculated as the correlation coefficient between mean arterial blood pressure and MCAv using either 3-, 5-, or 10-second averages collected over a 300 second period. Intraclass correlation coefficient (ICC 1.1) was calculated to assess relative reliability, while the standard error of measurement (SEM), and limits of agreement (LOA) were used to assess absolute reliability. Mxa-based 3-second averages yielded a similar relative and absolute reliability in both positions. When Mxa was calculated from 5-second averages, the most reliable values were obtained during HUT. The poorest reliability was achieved using 10-second averages, regardless of posture. The Mxa shows fair reliability with acceptable LOA in healthy volunteers when based on 3-second averages, both in the supine position and during HUT. [ABSTRACT FROM AUTHOR]

Background: The use of automated (oscillometric) blood pressure (BP) devices is not validated in atrial fibrillation (AF) patients. Objectives: To assess the reliability of three oscillometric BP devices, and the agreement with invasive arterial blood pressure(IBP) in AF patients. Methods: 48 AF patients with randomized sequences of 10 consecutive BP measurements with two pairs of devices: (1) OmronR7™(wrist) and OmronHEM907™(arm); (2) OmronR7™ and Microlife WatchBPhome(arm). Reliability and agreement of each device were assessed by the intra-class correlation coefficient (ICC) for the continuous BP measurements and Bland & Altman methodology, respectively. In 10 additional AF patients, 10 consecutive measurements with IBP and OmronHEM907™, and IBP and Microlife WatchBPhome were performed. Results: The OmronR7™ was not able to obtain any BP Readings. Arm devices presented better ICC for systolicBP(SBP) than for diastolicBP(DBP) (Omron HEM907™:0.94 [0.90; 0.97] vs. 0.77 [0.67; 0.89]; Microlife WatchBPhome:0.92 [0.88; 0.96] vs.0.79 [0.69; 0.89]).The correlation coefficient between Microlife WatchBPhome and IBP computed using the average of repeated measurements from two to ten measurements improved up to the third and remained stable afterwards. The agreement between IBP and SBP, and IBP and DBP, was moderate as illustrated by a wide limit of agreement [−24; 26](SBP) and [−15;17](DBP) for Microlife WatchBPHome, respectively and [−30; 13](SBP) and [−7; 15](DBP) for OmronHEM907. Conclusions: BP measurement using the two arm oscillometric devices achieved a high reliability for SBP. The agreement between IBP and arm devices was low but using the average of three consecutive measurements improved the results substantially.

Abstract Background Dietary assessment methods that can provide high quality data while limiting participant burden and resource requirements in epidemiological research are highly sought after and continue to evolve. The use of mobile phone technology in research has increased rapidly over the last decade and offers multiple advantages to the researcher over traditional data collection methods. This study tested the acceptability and relative validity of a commercial smart phone application (app) for use as an epidemiological dietary assessment tool, compared with a traditional dietary assessment method. Methods Study participants completed a 4-d food diary using a modified version of the Easy Diet Diary app and two 24-h dietary recalls during the same week, for comparison. At the end of data collection, participants completed a questionnaire on their experience with both methods. Average proportions of energy from macronutrients and fibre, iron, and calcium densities from the app and 24-h recalls were compared after log transformation, by calculating mean agreement, limits of agreement (LOA), and Pearson’s correlations. The prevalence of dietary under-reporting was compared in each method using the Goldberg method. Results A total of 50 adults (82% women) provided data for analysis (mean age, 31 y; mean BMI, 22.4 kg/m2; 14% overweight or obese). Participant feedback showed high levels of acceptance of the app; 83% preferred using the app to completing 24-h dietary recalls. The average difference in energy intake (mean agreement) between methods was 268 kJ/d. For all intakes except alcohol, the average difference between methods was not significantly different from zero. Most limits of agreement were within an acceptable range. The prevalence of dietary misreporting was similar in both methods. Conclusions These findings demonstrate good feasibility for applying this commercially-developed smartphone app in epidemiological research.

Estimating muscle volume (MV) using variable numbers of cross-sectional area (CSA) slices obtained from magnetic resonance imaging (MRI) introduces an error that is known in adults, but not in children and adolescents, whereby body sizes differ due to growth and maturation. Therefore, 15 children and adolescents (11 males, 14.8 ± 2.1 years) underwent MRI scans of the right thigh using a 1.5 T scanner to establish this error. A criterion MV was determined by tracing around and summing all CSAs, with MV subsequently estimated using every second, third, fourth and fifth CSA slice. Bland–Altman plots identified mean bias and limits of agreement (LoA) between methods. Error rates between 1.0 and 10.4% were seen between criterion and estimated MV. Additional analyses identified an impact of formulae selection, with a cylindrical formula preferred to a truncated cone. To counter high error between criterion and estimated MV due to the discrepancies in the number of CSA slices analysed, length-matched criterion volumes were established, with reduced error rates (0.5–2.0%) being produced as a result. CSA at 50% thigh-length also predicted MV, producing a high error (13.8–39.6%). Pearson's correlation coefficients determined relationships between error and measures of body size/composition, with all body size/composition measures being correlated (r = −0.78–0.86, p < 0.05) with the error between criterion and estimated MV. To conclude, MV can be accurately estimated using fewer CSA slices. However, the associated error must be considered when calculating MV in children and adolescents, as body size biases estimates. [ABSTRACT FROM AUTHOR]

Background: The Abarquez formula (aVR QRS amplitude x 2.264) + (age x 0.645) has been offered to provide an estimate for LVEF measured by 2D Echo. However, studies aiming to establish agreement between the Abarquez formula and LVEF measured by 2D Echo are lacking. Aims and Objectives: The aim of this study was to compare the LVEF estimated from 12-lead ECG using the Abarquez formula with the LVEF measured using the 2DED in the following subpopulations: 18-35 years old, 36-60 years old, >60 years old, male, and female patients. To compare these two measurements, the limits of agreement (LoA) by Altman and Bland was used. Materials and Methods: Adult patients admitted in the VLMC from January to May 2019 with both a 12-lead ECG and a 2D Echo were included in the study. LVEF from 2D Echo and LVEF estimated using the Abarquez formula were recorded. Comparison of the two measurements was performed by Altman and Bland method using LoA at 95% confidence interval. This analysis was done using Analyse-It Software. Comparison of the mean differences between the two measurement methods was also done using STATA. Results: LVEF estimate using the Abarquez formula was found to significantly differ from LVEF measured using 2D Echo. Conclusions: The Abarquez formula cannot be used as a surrogate for LVEF measure by 2D Echo. [ABSTRACT FROM AUTHOR]

Assessment of agreement between measurement methods is an important problem in medical practice and research. Several two one-sided tests (TOST) procedures have been proposed to evaluate whether two methods have sufficient agreement. These TOST techniques of limits of agreement or normal percentiles are natural generalizations of the favorable TOST procedure of mean differences. But their fundamental behavior of Type I error control has not been examined. This article describes an improved and exact approach for declaring agreement between two measurement methods when the range of central proportion of paired differences is within the designated threshold interval around zero. Theoretical examinations and numerical investigations are provided to justify the advantages of the proposed approach and to illustrate the shortcomings of the existing TOST procedures for assessing agreement between two methods. To facilitate the suggested agreement appraisal in design planning, the corresponding power and sample size formulas are also derived. Both SAS and R algorithms are presented for conducting agreement test, power calculation, and sample size determination in method comparison studies. [ABSTRACT FROM AUTHOR]

Background: Studies of agreement examine the distance between readings made by different devices or observers measuring the same quantity. If the values generated by each device are close together most of the time then we conclude that the devices agree. Several different agreement methods have been described in the literature, in the linear mixed modelling framework, for use when there are time-matched repeated measurements within subjects.Methods: We provide a tutorial to help guide practitioners when choosing among different methods of assessing agreement based on a linear mixed model assumption. We illustrate the use of five methods in a head-to-head comparison using real data from a study involving Chronic Obstructive Pulmonary Disease (COPD) patients and matched repeated respiratory rate observations. The methods used were the concordance correlation coefficient, limits of agreement, total deviation index, coverage probability, and coefficient of individual agreement.Results: The five methods generated similar conclusions about the agreement between devices in the COPD example; however, some methods emphasized different aspects of the between-device comparison, and the interpretation was clearer for some methods compared to others.Conclusions: Five different methods used to assess agreement have been compared in the same setting to facilitate understanding and encourage the use of multiple agreement methods in practice. Although there are similarities between the methods, each method has its own strengths and weaknesses which are important for researchers to be aware of. We suggest that researchers consider using the coverage probability method alongside a graphical display of the raw data in method comparison studies. In the case of disagreement between devices, it is important to look beyond the overall summary agreement indices and consider the underlying causes. Summarising the data graphically and examining model parameters can both help with this. [ABSTRACT FROM AUTHOR]

Background: Health researchers may struggle to choose suitable validated dietary assessment tools (DATs) for their target population. The aim of this review was to identify and collate information on validated UK DATs and validation studies for inclusion on a website to support researchers to choose appropriate DATs.Design: A systematic review of reviews of DATs was undertaken. DATs validated in UK populations were extracted from the studies identified. A searchable website was designed to display these data. Additionally, mean differences and limits of agreement between test and comparison methods were summarized by a method, weighting by sample size.Results: Over 900 validation results covering 5 life stages, 18 nutrients, 6 dietary assessment methods, and 9 validation method types were extracted from 63 validated DATs which were identified from 68 reviews. These were incorporated into www.nutritools.org. Limits of agreement were determined for about half of validations. Thirty four DATs were FFQs. Only 17 DATs were validated against biomarkers, and only 19 DATs were validated in infant/children/adolescents.Conclusions: The interactive www.nutritools.org website holds extensive validation data identified from this review and can be used to guide researchers to critically compare and choose a suitable DAT for their research question, leading to improvement of nutritional epidemiology research. [ABSTRACT FROM AUTHOR]

Recently, a new estimation procedure has been developed to assess bias and precision of a new measurement method, relative to a reference standard. However, the author did not develop confidence bands around the bias and standard deviation curves. Therefore, the goal in this paper is to extend this methodology in several important directions. First, by developing simultaneous confidence bands for the various parameters estimated to allow formal comparisons between different measurement methods. Second, by proposing a new index of agreement. Third, by providing a series of new graphs to help the investigator to assess bias, precision, and agreement between the two measurement methods. The methodology requires repeated measurements on each individual for at least one of the two measurement methods. It works very well to estimate the differential and proportional biases, even with as few as two to three measurements by one of the two methods and only one by the other. The repeated measurements need not come from the reference standard but from either measurement methods. This is a great advantage as it may sometimes be more feasible to gather repeated measurements with the new measurement method. [ABSTRACT FROM AUTHOR]

Background: Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives: This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods: Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results: Modelled geographical access (P) is generally lower than self-reported access (R), but there is a geography to this relationship. In India and Pakistan, potential access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)] <.001, limits of agreement: [− 273.81; 56.40] and [− 264.10; 94.25] respectively. In Mozambique, mean differences between the two measures of access were significantly different from 0 [P (H0: Mean difference = 0) = 0.31, limits of agreement: [− 187.26; 199.96]]. Conclusion: Modelling access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling access should not be viewed through a geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494 [ABSTRACT FROM AUTHOR]

When a method comparison study is performed, the aim is to evaluate the agreement of measurements of different methods. We present the Bland–Altman plot with limits of agreement as the correct analysis methodology. We also discuss other scaled and unscaled indices of agreement and commonly used inappropriate approaches. [ABSTRACT FROM AUTHOR]

Background: To examine the agreement between self-reported and objectively assessed physical activity (PA) according to current public health recommendations. Methods: One-hundred and fourteen British University students wore a combined accelerometer and heart rate monitor (Actiheart; AHR) to estimate 24-hour energy expenditure over 7 consecutive days. Data were extracted based on population-based MET-levels recommended to improve and maintain health. On day 8, participants were randomly assigned to complete either the short-form International Physical Activity Questionnaire (IPAQ) or the Leisure-Time Exercise Questionnaire (LTEQ). Estimates of duration (IPAQ; N = 46) and frequency (LTEQ; N = 41) of PA were compared with those recorded by the AHR. Results: Bland-Altman analysis showed the mean bias between the IPAQ and AHR to be small for moderate-intensity and total PA, however the 95% limits of agreement (LOA) were wide. The mean number of moderate bouts of PA estimated by the LTEQ was similar to those derived by the AHR but the 95% LOA between the 2 measures were large. Conclusions: Although self-report questionnaires may provide an approximation of PA at a population level, they may not determine whether an individual is participating in the type, intensity, and amount of PA advocated in current public health recommendations. [ABSTRACT FROM AUTHOR]

Before conclusions can be drawn with respect to the quality of adaptations in human gait, the day-to-day consistency of the variables of interest must be known. The present study estimated the day-to-day consistency of kinematic variables collected during barefoot walking and running. Sixteen healthy subjects performed two gait analysis sessions based on skin markers. Test sessions were at least 1 week apart. In total, 48 ranges of motion were monitored for the hip, knee, ankle, and midfoot joint. Based on differences between the repeated gait analysis sessions, the day-to-day consistency was estimated. It was found that the day-to-day consistency was of the magnitude of 3 to 4 degrees for almost all ranges of motion independently of the test condition, the investigated joints, or the cardinal body plane. It was concluded that future studies on effects of interventions or on the characterization of pathological versus normative gait should consider the provided values of day-to-day consistency to improve their interpretation and conclusions. [ABSTRACT FROM AUTHOR]

Purpose: To compare blood lactate concentration ([Bla]) at 15 s and 45 s during the 1-min rest period between each stage of an incremental test in rowers and to establish the validity of using interchangeable sampling times. Methods: Seventeen male club rowers (mean ± SD, age 28.8 ± 5.7 years, height 186.9 ± 5.1 cm, body mass 85.4 ± 6.6 kg) performed an incremental rowing ergometer test, consisting of five stages of 4 min corresponding to approximately 80% HRmax. A 10-μL earlobe blood sample was collected from each subject at 15 s and again at 45 s in the final minute of each test stage and analyzed in duplicate. A maximum of 10 s was allowed for blood collection. Results: Statistical analysis using limits of agreement and correlation indicated a high level of agreement between the two [Bla] samples for all five test stages (agreement >95%, confidence intervals [CI] = -0.5 to 1.5, r = .97, P < .05). Conclusion: These results suggest that a sampling time between 15 sand 45 s may be recommended for the valid assessment of the [Bla] threshold in rowing performance monitoring. This extends the current sampling time of 30 s used by physiologists and coaches for National and club-level Rowers. [ABSTRACT FROM AUTHOR]

This study assessed measurement agreement of jump-height measures derived from a portable forceplate sampling at 500 Hz. Female (n = 42) and male (n = 30) participants (total N = 72, age = 19.7 ± 2.8 y, height = 174.5 ± 9.3 cm, mass = 71.4 ± 12.8 kg) performed 25 separate maximal jump attempts. This incorporated 5 sets of 5 single jumps. One minute of rest was allowed between jump attempts, with a 3-min rest period between sets. For each participant, the best jump height for each set of 5 jumps was kept for analysis. No systematic bias was identified, and the best jump height was stable within participants across all 5 sets of jumps. Therefore, factors such as fatigue and learning did not affect the measures. Females did jump lower (P = < .0001) than their male counterparts, justifying additional analysis of agreement for the 2 gender groups. Heteroscedasticity was found, so ratio limits of agreement (LOAs) were calculated by using the antilog of the log-transformed data. The calculated ratio LOAs were ×/÷ 1.08 for the total group, ×/÷ 1.08 for females, and ×/÷ 1.08 for males. From the calculated ratio LOA, the jump protocol was shown to provide stable measures of jump height. In addition, the ratio LOA can be helpful to interpret findings from research that report jump height derived from the same protocol and assessing participants from the studied population (ie, active university-age male, female, or combined-gender groups). [ABSTRACT FROM AUTHOR]