OBJECTIVE: Harmonization has been recommended by the International Organization for Standard (ISO) to achieve equivalent results across in vitro diagnostic measurement devices (IVD-MDs). We aim to evaluate the effectiveness of Bland-Altman plot-based harmonization algorithm (BA-BHA) created in this study and compare it with weighted Deming regression-based harmonization algorithm (WD-BHA) proposed in ISO 21151:2020.
METHODS: Eighty patient sera were used as the harmonization reference material (HRM) to develop IVD-MD-specific harmonization algorithms. Another panel of 40 patient sera was used to validate the effectiveness of harmonization algorithms. We compared regression slopes, intercepts, Bland-Altman plot layouts, percent differences, limits of agreement (LoAs), between-method coefficients of variation (CV) before and after harmonization.
RESULTS: After harmonization by WD-BHA, acceptable slopes and intercepts between measured values and HRM targets were observed in weighted Deming regression, but not in Passing-Bablok analysis. Mean differences were -5.5 to 5.0 % and differences at specific levels were -33.9 to 23.9 %. LoAs were -64.6 to 74.6 %. Between-method CV was 22.9 % (±12.9 %). However, after harmonization by BA-BHA, both weighted Deming and Passing-Bablok regressions equations presented harmonized results. Mean differences were -0.3 to 0.2 % and differences at specific levels were -1.1 to 1.6 %. LoAs were -23.3 to 23.2 %. Between-method CV was 8.4 % (±4.0 %). The data points were evenly distributed at both sides of the mean in Bland-Altman plots.
CONCLUSIONS: The inequivalence of test results between different methods can be improved but unacceptable analytical differences at specific levels may be hidden in terms of an acceptable slope and intercept on WD-BHA. The new protocol BA-BHA may be a viable alternative to optimize the harmonization for immunoassays.

OBJECTIVE: The symptoms of major depressive disorder (MDD) are nowadays being assessed with the Hamilton and Montgomery-Åsberg Depression Rating Scales. However, there are few studies on the comparison of these two scales. Our study aimed to determine the correlation between the Hamilton Depression Rating Scale (HDRS) and Montgomery-Åsberg Depression Rating Scale (MADRS) scores at baseline through 12 weeks.
METHODS: An ongoing randomized, open-label, three-arm study\'s interim analysis is portrayed here. The participants were assessed with HDRS and MADRS at baseline, four, eight, and 12 weeks after receiving oral tablets of either vilazodone (20-40 mg/d), escitalopram (10-20 mg/d), or vortioxetine (5-20 mg/d). This study is prospectively registered with the Clinical Trial Registry, India (CTRI/2022/07/043808).
RESULTS: Of 71 recruited individuals, 49 (69%) completed the 12-week visit. At baseline, the three groups\' median HDRS scores were 30.0, 29.5, and 29.0 (p=0.76), and at 12 weeks, they reduced to 19.5, 19.5, and 18.0 (p=0.18). At baseline, the group-wise median MADRS scores were 36, 36, and 36 (p=0.79); at 12 weeks, they were 24, 24, and 23 (p=0.03). The Pearson correlation revealed that the association between the changes in scores from baseline was strongest for escitalopram (r=0.70, p=0.002) followed by vortioxetine (r=0.59, p=0.01) and vilazodone (r=0.59, p=0.02). The Bland-Altman analysis showed that the mean difference between the scores was 5.11 (95% CI: 3.08-7.14).
CONCLUSIONS: According to this interim study, HDRS and MADRS scores declined after 12 weeks of therapy. Both scores had strong positive correlation, and the difference between the scores reduced with time.

Neutrophil myeloperoxidase (MPO) is an essential enzyme for the innate immune system. Measuring MPO activity is vital for understanding neutrophil characteristics and functions in various diseases. MPO activity can be measured using several methods, including spectrophotometric and fluorometric protocols. This paper introduces a fluorometric method for specifically quantifying MPO activity based on the H2O2-dependent oxidation of thiamine. We optimized this new method using the robust statistical approach response surface methodology (RSM) and Box Benken Design (BBD). We extensively examined the effects of several experimental parameters using the RSM methodology and determined the best conditions for accurate and sensitive MPO activity measurement. The optimal conditions were determined using the analysis of variance (ANOVA) for second-order polynomial equations. The resulting F-value (4.86) indicated that the model was significant. However, the lack-of-fitness F-value (1.79) suggested it did not differ significantly from the corresponding p-value. The greatest MPO activity (30 ± 2 U L-1) was obtained under optimum conditions, which were 1000 µM of H2O2, 10 min incubation time, and 1000 µM of thiamine. Our results suggest that this advanced fluorometric method has significant accuracy, sensitivity, and linearity up to 60 IU. The new and standard colorimetric methods also showed a good correlation. These results indicate that the new fluorometric method can be dependable and efficient for assessing MPO activity. The new method is characterized by excellent accuracy, sensitivity, and linearity, making it a valuable protocol for researchers and clinicians interested in assessing MPO activity.

BACKGROUND: It is important that easy-to-use measures like subjective questions about physical activity (PA) and sedentary behaviour are valid and reliable providing accurate measures, when they are used in health promotion work aiming to support people to improve their lifestyle habits such as PA. The aim of this study was to evaluate the concurrent validity of a structured interview form estimating self-reported PA and a question about sitting time used in Swedish targeted health dialogues in the context of primary health care.
METHODS: The study was conducted in the southern part of Sweden. To evaluate concurrent validity of the interview form, time spent in moderate-to-vigorous physical activities (MVPA) and energy expenditure related to MVPA estimated by an interview form was compared with the same measures assessed by an ActiGraph GT3X-BT accelerometer. To evaluate a question about sitting time, the Swedish School of Sport and Health Sciences\' single-item question about sitting time (SED-GIH) was compared with measures from an activPAL inclinometer. Statistical analyses included deriving Bland‒Altman plots and calculating Spearman\'s rank correlation coefficients.
RESULTS: Bland‒Altman plots indicated lower absolute variation in the difference between self-reported and device-based PA measures for lower PA levels, both for energy expenditure and time spent in MVPA. No systematic over- or underestimation was observed. The Spearman\'s correlation coefficient between self-reported and device-based PA measures was 0.27 (p = 0.014) for time spent in MVPA and 0.26 (p = 0.022) for energy expenditure. The correlation coefficient between the single item question and device-based sitting time measures was 0.31 (p = 0.002). Sitting time was underestimated by 74% of the participants.
CONCLUSIONS: The PA interview form and the SED-GIH question on sitting time may be of value in targeted health dialogues in primary health care with the intention to support sedentary and insufficiently physically active persons in increasing their physical activity and limiting their sitting time. The questionnaires are easy to use and are more cost effective than device-based measures, especially regarding population-based interventions conducted in primary health care for thousands of participants such as targeted health dialogues.
BACKGROUND: Not applicable.

Quantifying the smoothness of different layers of the retina can potentially be an important and practical biomarker in various pathologic conditions like diabetic retinopathy. The purpose of this study is to develop an automated machine learning algorithm which uses support vector regression method with wavelet kernel and automatically segments two hyperreflective retinal layers (inner plexiform layer (IPL) and outer plexiform layer (OPL)) in 50 optical coherence tomography (OCT) slabs and calculates the smoothness index (SI). The Bland-Altman plots, mean absolute error, root mean square error and signed error calculations revealed a modest discrepancy between the manual approach, used as the ground truth, and the corresponding automated segmentation of IPL/ OPL, as well as SI measurements in OCT slabs. It was concluded that the constructed algorithm may be employed as a reliable, rapid and convenient approach for segmenting IPL/OPL and calculating SI in the appropriate layers.

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.
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.
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.
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.

Intelligent analysis of present lifestyle may help to understand the development of the chronic diseases and the relationship of these diseases together. It is possible to reduce or prevent the development of these diseases. In this work, a novel intelligent method is introduced and applied for early detection of type 2 diabetic. Intelligent analysis depends mainly on evaluation life-threatening conditions (obesity, hypertension, smoking status, alcohol drinking status and low level of physical activities) to extract knowledge from linguistic variablesand design a new cognitive tool to assist in the prediction process.This method consists from three stages: in the first stage, data was collected from 100 healthy volunteers, which includes evaluations of life-threatening conditions. The second stage is implementation of fuzzy model for early prediction of type 2 diabetes. Predicted blood glucose values of proposal technique were compared with average fasting blood glucose values based on analysis of Bland-Altman plot. Furthermore, fuzzy system model presents superior results (accuracy = 81%, precision = 0.57% and recall = 0.83%).

This study sought to achieve radiation dose reductions for patients receiving uterine artery embolisation (UAE) by evaluating radiation dose measurements for the preceding generation (Allura) and upgraded (Azurion) angiography system. Previous UAE regression models in the literature could not be applied to this centre\'s practice due to being based on different angiography systems and radiation dose predictor variables. The aims of this study were to establish whether radiation dose is reduced with the upgraded angiography system and to develop a regression model to determine predictors of radiation dose specific to the upgraded angiography system. A comparison between Group I (Allura,n= 95) and Group II (Azurion,n= 95) demonstrated a significant reduction in kerma-area product (KAP) and Ka, r (reference air kerma) by 63% (143.2 Gy cm2vs 52.9 Gy cm2;P< 0.001,d= 0.8) and 67% (0.6 Gy vs 0.2 Gy;P< 0.001,d= 0.8), respectively. The multivariable linear regression (MLR) model identified the UAE radiation dose predictors for KAP on the upgraded angiography system as total fluoroscopy dose, Ka, r, and total uterus volume. The predictive accuracy of the MLR model was assessed using a Bland-Altman plot. The mean difference was 0.39 Gy cm2and the limits of agreement were +28.49 and -27.71 Gy cm2, and thus illustrated no proportional bias. The resultant MLR model was considered system-dependent and validated the upgraded angiography system and its advance capabilities to significantly reduce radiation dose. Interventional radiologist and interventional radiographer familiarisation of the system\'s features and the implementation of the newly established MLR model would further facilitate dose optimisation for all centres performing UAE procedures using the upgraded angiography system.

The unrelated mean effects (UME) model has been proposed for evaluating the consistency assumption globally in the network of interventions. However, the UME model does not accommodate multiarm trials properly and omits comparisons between nonbaseline interventions in the multiarm trials not investigated in 2-arm trials.
We proposed a refinement of the UME model that tackles the limitations mentioned above. We also accompanied the scatterplots on the posterior mean deviance contributions of the trial arms under the network meta-analysis (NMA) and UME models with Bland-Altman plots to detect outlying trials contributing to poor model fit. We applied the refined and original UME models to 2 networks with multiarm trials.
The original UME model omitted more than 20% of the observed comparisons in both networks. The thorough inspection of the individual data points\' deviance contribution using complementary plots in conjunction with the measures of model fit and the estimated between-trial variance indicated that the refined and original UME models revealed possible inconsistency in both examples.
The refined UME model allows proper accommodation of the multiarm trials and visualization of all observed evidence in complex networks of interventions. Furthermore, considering several complementary plots to investigate deviance helps draw informed conclusions on the possibility of global inconsistency in the network.
We have refined the unrelated mean effects (UME) model to incorporate multiarm trials properly and to estimate all observed comparisons in complex networks of interventions.Forest plots with posterior summaries of all observed comparisons under the network meta-analysis and refined UME model can uncover the consequences of potential inconsistency in the network.Using complementary plots to investigate the individual data points\' deviance contribution in conjunction with model fit measures and estimated heterogeneity aid in detecting possible inconsistency.

Background Smartphone technology is rapidly evolving and advancing, with many of them offering health applications being used for oximetry purposes, including the Samsung Health/S Health application. Measuring oxygen saturation is one of the important indications to monitor patients with COVID-19, as well as other health conditions. These applications can be used for measuring oxygen saturation to provide a convenient solution for clinical decisions. Methods Oxygen saturation measurements were collected using the Samsung Health application for Samsung Galaxy smartphone with a sensor and camera flash and a low-cost portable digital display (liquid crystal display (LCD)) finger pulse oximeter. Intra-session reliability was established to determine the consistency between the measures. Intra-class correlation coefficients (ICCs) were calculated with 95% confidence intervals (CIs) reported for both methods. The Bland-Altman plot was used to compare the level of agreement between the two measurement methods. Results There was a statistically significant average difference between pulse oximeter and Samsung Health application measurements (t125 = 4.407, p < 0.001), and on average, pulse oximeter measurement was 0.510 points higher than Samsung Health application measurement (95% CI = 0.281-0.740). The pulse oximeter and Samsung Health application scores were moderately correlated (r = 0.462). The results of the intra-session reliability test produced an acceptable ICC value of 0.557, indicating moderate reliability and consistent results for the measurement of oxygen saturation with both methods. The Bland-Altman plot showed a consistently equal distribution of data points scattered above and below zero. Conclusion Smartphone health applications can be used with moderate reliability to measure oxygen saturation.