Altman Method Research Articles

Validity of a Web-Based 24-Hour Dietary Recall of Energy and Nutrient Intakes in Japanese Adults

Recently, web-based dietary assessment tools for the targeted population have been developed and used to estimate the dietary intake level in several epidemiological studies. This study aimed to examine the validity of estimating energy and nutrient intake by the web-based 24 h dietary recall (Web24HR), which we developed for the Japanese population. Overall, 228 adults aged ≥20 years who agreed to participate were included. Web24HR was administered three times per person: twice within 3 weeks and once 3 months later. The data on 3-day weighed food records (WFR) at 3-month intervals in the four seasons were collected using the reference method. The intake of energy and nutrients between Web24HR and WFR were compared using Pearson’s correlation coefficients and the Bland–Altman analysis. As results, the correlations were moderate for both men (median r = 0.51) and women (median r = 0.38) except for iodine, retinol, retinol equivalents, and β-tocopherol. The Bland–Altman method revealed that the bias in intake was within ±10% for most nutrients, except for cholesterol, iodine, vitamin C, and the water content, in both sexes. Additionally, monounsaturated fatty acids in men and β-cryptoxanthin in women exhibited an underestimation of more than 10%. In conclusion, the Web24HR intake assessment showed moderate correlations for most nutrients in both sexes. The bias in intake was within ±10% for most nutrients, but there were discrepancies for some nutrients. This tool’s performance is comparable to Japan’s standard dietary exposure assessment methods and will be helpful for future applications in epidemiological studies, though caution is needed for certain nutrient assessments.

ClearLLab 10C reagents panel can be applied to analyze paucicellular samples by flow cytometry.

The FDA-approved ClearLLab 10C Reagents Panel (Beckman Coulter) simplified the diagnosis of leukemias and lymphomas by flow cytometry. However, the requirement of using 3 × 106 cells/mL cannot be met for paucicellular samples. Therefore, we tested whether this 10-color panel can be reliably employed to analyze specimens with low cell concentrations. Serial dilutions of 16 samples (5 normal, 11 abnormal), yielding concentrations ranging from 3.0 × 106 to 0.0469 × 106 cells/mL (64-fold difference), were stained using the B-cell and T-cell panels of the ClearLLab 10C system, and mean fluorescence intensity (MFI) was measured for each antibody. For each cell dilution, the deviation from the value obtained with the FDA-approved concentration of 3.0 × 106 cells/mL was calculated. The agreement between the highest and lowest cell concentration data was evaluated by the Bland and Altman method, Pearson's and Spearman's correlation analyses, and linear regression. In all patients, the antigen expression pattern was similar at all cell concentrations tested, and the mean deviation of the MFI from the value obtained using 3.0 × 106 cells/mL never exceeded 10% for any of the antibodies. The Bland-Altman method demonstrated the similarity between results obtained with the FDA-approved cell concentration and a 64-fold diluted cell suspension, and a high positive correlation was found between MFI acquired under these two conditions. The tests utilizing the lowest density of cells yielded the same patterns of antigen expression in all patients as those performed with the FDA-approved concentration, documenting a 100% concordance between these two protocols. The ClearLLab 10C panel can reliably determine the expression of markers of leukemias and lymphomas in paucicellular samples containing as little as 0.0469 × 106 cells/mL (64-fold lower than the FDA-approved concentration). This finding markedly expands the applicability of the ClearLLab 10C platform in a clinical setting.

Feasibility of real-time compression frequency and compression depth assessment in CPR using a “machine-learning” artificial intelligence tool

BackgroundVideo assisted cardiopulmonary resuscitation (V-CPR) has demonstrated to be efficient in improving CPR quality and patient outcomes, as Emergency Medical Service (EMS) dispatchers can use the video stream of a caller for diagnostic purposes and give instructions in a CPR scenario. However, the new challenges faced by EMS dispatchers during video-guided CPR (V-CPR)—such as analyzing the video stream, providing feedback to the caller, and managing stress—demand innovative solutions. This study explores the feasibility of incorporating an open-source “machine-learning” tool (artificial intelligence – AI), to evaluate the feasibility and accuracy in correctly detecting the actual compression frequency and compression depth in video footage of a simulated CPR. DesignMediaPipe Pose Landmark Detection (Google LLC, Mountain View, CA, USA), an open-source AI software using “machine-learning” models to detect human bodies in images and videos, was programmed to assess compression frequency an depth in nine videos, showing CPR on a resuscitation manikin. Compression frequency and depth were assessed from compression to compression with AI software and were compared to the manikin’s internal software (QCPR, Laerdal, Stavanger, Norway). After testing for Gaussian distribution, means of non-gaussian data were compared using Wilcoxon matched-pairs signed rank test and the Bland Altman method. Main resultsMediaPipe Pose Landmark Detection successfully identified and tracked the person performing CPR in all nine video sequences. There were high levels of agreement between compression frequencies derived from AI and manikin’s software. However, the precision of compression depth showed major inaccuracies and was overall not accurate. ConclusionsThis feasibility study demonstrates the potential of open-source “machine-learning” tools in providing real-time feedback on V-CPR video sequences. In this pilot study, an open-source landmark detection AI software was able to assess CPR compression frequency with high agreement to actual frequency derived from the CPR manikin. For compression depth, its performance was not accurate, suggesting the need for adjustment. Since the software used is currently not intended for medical use, further development is necessary before the technology can be evaluated in real CPR.

Comparison of two proxies for the preconception weight using data from a pre-pregnancy cohort in Benin: Weight measured in the first trimester of pregnancy vs estimated by Thomas' formula.

Accurate determination of pre-pregnancy weight is essential for optimal pregnancy monitoring and antenatal care. Determining pre-pregnancy weight in limited-resources settings is challenging for both clinical practice and public health research. From a 2014-2017 pre-pregnancy cohort in Benin, we evaluated the agreement between the measured pre-pregnancy weight (MPPW) and two proxies: (i) the first trimester pregnancy weight (FTPW) and (ii) the estimated pre-pregnancy weight (EPPW) using Thomas & al. formula. We analysed data from 302 pregnant women with both pre-pregnancy weight measured within 3 months before conception and weight measured during the first trimester. Using segmented linear regression, we first assessed up to which gestational age the weight measured during the first trimester could reasonably estimate the MPPW. Then the Bland & Altman method was used to assess agreement between MPPW and the two proxies. Additional analyses were performed to assess the sensitivity of results to the timing of measurement of either MPPW or the two proxies. On average, FTPW did not feature significant difference with MPPW up to 13.03 (11.99-14.06) weeks of gestational age. FTPW, measured on average at 7 ± 2.4 weeks of gestation, and the EPPW showed similar Bland & Altman limits of agreement with the MPPW. However, while the FTPW slightly underestimated the MPPW by a mean of-0.16 (-0.08; +0.39) kg, the EPPW overestimated it by a mean of + 0.43 (+0.20; +0.66) kg. Minor differences in these results were observed when the MPPW was assessed earlier or within three months before pregnancy, or according to the gestational age at the time of the proxy's measurement. In conclusion, in Southern Benin and up to 12-14 weeks of pregnancy, the FTPW appeared to be a good proxy of the MPPW while using Thomas' formula did not enhance pre-pregnancy weight estimation.

Financial Distress Analysis of Companies Carrying Out Mass Layoffs Throughout 2023 using the Altman Z-Score Method, Springate Method, and Zmijewski Method

This research aims to estimate the financial condition of four companies that will carry out mass layoffs throughout 2023 using three financial distress prediction methods, namely the Z-Score Altman method, the Springate method and the Zmijewski method. Secondary data was used sourced from the financial reports of each company from 2022 to 2023. The research results showed that financial performance was analyzed using the Z-Score Altman method, the Springate method and the Zmijewski method in four companies, namely PT Net Visi Media Tbk for the period 2022-2023 classified as having the potential to experience bankruptcy, PT GoTo Gojek Tokopedia Tbk for the 2022-2023 period is classified as having a high potential for bankruptcy, PT Bukalapak.com Tbk for the 2022-2023 period is classified as being in good health, and JD.com, Inc. (JD) for the 2022-2023 period is classified as having absolutely no potential for bankruptcy.

Comparing bioimpedance spectrometry and traditional creatinine kinetics methods for the assessment of muscle mass in peritoneal dialysis patients.

Sarcopenia is a common and serious problem in patients receiving peritoneal dialysis (PD). Lean tissue mass (LTM) by bioimpedance spectrometry is a reasonably accurate method for measuring muscle mass. Fat-free edema-free body mass (FEBM) as determined by the creatinine kinetics method is a traditional method but evidence to support its use is limited. We studied 198 new PD patients. Their serial LTM and FEBM were reviewed and compared by the Bland and Altman method. Multi-variable regression model was used to determine factors associated with the disparity between the two methods. There was a significant but moderate correlation between LTM and FEBM (r=0.309, P<.0001). LTM was consistently higher than FEBM, with an average difference 13.98kg (95% confidence interval -5.90 to 33.86kg), and the difference strongly correlated with LTM (r=0.781, P<.0001). By multivariable linear regression analysis, LTM and residual renal function were independent predictors of the LTM-FEBM difference. Where the measurements were repeated in 12months, there was no significant correlation between ∆LTM and ∆FEBM (r=-0.031, P=.799). There is a significant difference between LTM and FFBM. This discrepancy correlated with LTM and residual renal function, highlighting the limitations of FFBM in assessing skeletal muscle mass.

A new artificial intelligence program for the automatic evaluation of scoliosis on frontal spinal radiographs: Accuracy, advantages and limitations

BACKGROUND: Scoliosis is one of the most common spinal deformations that are usually diagnosed on frontal radiographs using Cobb’s method. Automatic measurement methods based on artificial intelligence can overcome many drawbacks of the usual method and can significantly save radiologist’s time. AIM: To analyze the accuracy, advantages, and disadvantages of a newly developed artificial intelligence program for the automatic diagnosis of scoliosis and measurement of Cobb’s angle on frontal radiographs. MATERIALS AND METHODS: In total, 114 digital radiographs were used to test the agreement of Cobb’s angle measurements between the new automatic method and the radiologist using the Bland–Altman method on Microsoft Excel. A limited clinical accuracy test was also conducted using 120 radiographs. The accuracy of the system in defining the scoliosis grade was evaluated by sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve. RESULTS: The agreement of Cobb’s angle measurement between the system and the radiologist’s calculation was found mostly in grade 1 and 2 scoliosis. Only 2.8% of the results showed a clinically significant angle variability of 5°. The diagnostic accuracy metrics of the limited clinical trial in City Mariinsky Hospital (Saint Petersburg, Russia) also proved the reliability of the system, with a sensitivity of 0.97, specificity of 0.88, accuracy (general validity) of 0.93, and area under the receiver operating characteristic curve of 0.93. CONCLUSION: Overall, the artificial intelligence program can automatically and accurately define the scoliosis grade and measure the angles of spinal curvatures on frontal radiographs.

Flow quantification within the aortic ejection tract using 4D flow cardiac MRI in patients with bicuspid aortic valve: Implications for the assessment of aortic regurgitation

PurposeThe purpose of this study was to evaluate the performance of four-dimensional (4D) flow cardiac MRI in quantifying aortic flow in patients with bicuspid aortic valve (BAV). Materials and methodsPatients with BAV who underwent transthoracic echocardiography (TTE) and 4D flow cardiac MRI were prospectively included. Aortic flow was quantified using two-dimensional phase contrast velocimetry at the sinotubular junction and in the ascending aorta and using 4D flow in the regurgitant jet, in the left ventricular outflow tract, at the aortic annulus, the sinotubular junction, and the ascending aorta, with or without anatomical tracking. Flow quantification was compared with ventricular volumes, pulmonary flow using Pearson correlation test, bias and limits of agreement (LOA) using Bland Altman method, and with multiparametric transthoracic echocardiography quantification using weighted kappa test. ResultsEighty-eight patients (63 men, 25 women) with a mean age of 50.5 ± 14.8 (standard deviation) years (age range: 20.8–78.3) were included. Changes in flow with or without tracking were modest (< 5 mL). The best correlation was obtained at the aortic annulus for forward volume (r = 0.84; LOA [-28.4; 25.3] mL) and at the regurgitant jet and sinotubular junction for regurgitant volume (r = 0.68; LOA [-27.8; 33.8] and r = 0.69; LOA [-28.6; 24.2] mL). A combined approach for regurgitant fraction and net volume calculations using forward volume measured at ANN and regurgitant volume at sinotubular junction performed better than each level taken separately (r = 0.90; LOA [-20.7; 10.0] mL and r = 0.48, LOA [-33.8; 33.4] %). The agreement between transthoracic echocardiography and 4D flow cardiac MRI for aortic regurgitation grading was poor (kappa, 0.13 to 0.42). ConclusionIn patients with BAV, aortic flow quantification by 4D flow cardiac MRI is the most accurate at the annulus for the forward volume, and at the sinotubular junction or directly in the jet for the regurgitant volume.

Cervical Sensorimotor Function Tests Using a VR Headset-An Evaluation of Concurrent Validity.

Sensorimotor disturbances such as disturbed cervical joint position sense (JPS) and reduced reaction time and velocity in fast cervical movements have been demonstrated in people with neck pain. While these sensorimotor functions have been assessed mainly in movement science laboratories, new sensor technology enables objective assessments in the clinic. The aim was to investigate concurrent validity of a VR-based JPS test and a new cervical reaction acuity (CRA) test. Twenty participants, thirteen asymptomatic and seven with neck pain, participated in this cross-sectional study. The JPS test, including outcome measures of absolute error (AE), constant error (CE), and variable error (VE), and the CRA test, including outcome measures of reaction time and maximum velocity, were performed using a VR headset and compared to a gold standard optical motion capture system. The mean bias (assessed with the Bland-Altman method) between VR and the gold standard system ranged from 0.0° to 2.4° for the JPS test variables. For the CRA test, reaction times demonstrated a mean bias of -19.9 milliseconds (ms), and maximum velocity a mean bias of -6.5 degrees per seconds (°/s). The intraclass correlation coefficients (ICCs) between VR and gold standard were good to excellent (ICC 0.835-0.998) for the JPS test, and excellent (ICC 0.931-0.954) for reaction time and maximum velocity for the CRA test. The results show acceptable concurrent validity for the VR technology for assessment of JPS and CRA. A slightly larger bias was observed in JPS left rotation which should be considered in future research.

Reliability of the assessment of the clinical dementia rating scale from the analysis of medical records in comparison with the reference method

BackgroundThe Clinical Dementia Rating (CDR) scale allows to detect the presence of dementia and to assess its severity, however its evaluation requires a significant time (45 min). We evaluated the agreement between two methods of collection of the CDR: face-to-face interview or based on the information available in the patient’s medical record.MethodsThe CLIMER study was conducted among patients attending a memory center. The CDR scale was evaluated during face-to-face interviews between neuropsychologists and patients and their caregivers and based on blind analysis of the information of the patients’ medical record by neuropsychologists. The agreement of the CDR sum of boxes (CDR-SB), the 5-point scale CDR and the different domains of the CDR evaluated between the different methods was measured using intraclass correlation (ICC) coefficient, Bland and Altman method, and linearly weighted Kappa.ResultsThe study included 139 patients (means ± SD age 80.1 ± 6, 58.3% women, 71.9% with dementia). The ICC for the CDR-SB score assessed by face-to-face and with all the information available in the patient’s medical record was 0.95 (95% CI: 0.93–0.97). The mean difference between the CDR-SB score assessed by face-to-face and with the medical record was 0.098 ± 1.036, and 92.4% of the patients lay within the 95% limits of agreement. The ICC for the 5-point scale CDR assessed by face-to-face and with the patient’s medical record was 0.92 (95% CI: 0.88–0.95) when all the available information of the patient’s medical record was used. The linear weighted Kappa coefficients was 0.79 (95% CI: 0.68–0.91) for the 5-point scale CDR comparison between the two evaluation methods. The analysis by domain of the CDR showed ICC ranging from 0.65 to 0.91 depending of the domains and the methods of evaluation.ConclusionThis study showed an excellent level of agreement of the evaluation of the CDR- SB and the 5-point scale CDR when using all the information of the patient’s medical record compared to the face-to-face interview.Trial registrationhttps//clinicaltrials.gov/ct2/show/NCT04763941 Registration Date 02/17/2021.

Critical appraisal of the CLSI guideline EP09c "measurement procedure comparison and bias estimation using patient samples".

In laboratory setting evaluating the agreement between two measurement methods is a very frequent practice. Unfortunately, the guidelines to refer to are not free from criticisms from a statistical methodological point of view. We reviewed the Clinical and Laboratory Standards Institute guideline EP09c, 3rd ed. pointing out some drawbacks and some aspects that have not been well defined, leaving situations of uncertainty and/or of excessive subjectivity in the judgement. We have stressed the need of having replicates to estimate the systematic and the proportional biases of the measurement methods to be compared. Indeed, unequal variance of the two measurement methods gives a slope and intercept of the regression between the difference and the mean of the two values of the measurement methods to be compared that can be absolutely calculated from their means, their variances and their correlation coefficient. So,it is not possible to disentangle true from spurious biases. For laboratory professionals we have developed a worked exemplification of an agreement assessment. We have stressed the need of other approaches than the classic Bland and Altman method to calculate the systematic and proportional biases of two measurement methods compared for their agreement in a study with replicates.

Correlation, agreement and concordance of cardiac output estimated by transthoracic ultrasound and transesophageal Doppler with pulmonary artery thermodilution in anesthetized cats

ObjectiveTo characterize the correlation, agreement and concordance of cardiac output (CO) measured with transthoracic ultrasound and the correlation and concordance of aortic blood flow (ABF) minute distance (MD) measured by transesophageal Doppler with CO measured by pulmonary artery thermodilution (PATD) in cats. Study designExperimental study. AnimalsA group of six healthy male neutered cats, aged 2–8 years and weighing 5.3 ± 0.3 kg. MethodsCats were anesthetized with isoflurane in oxygen. CO was measured by PATD (COPATD) and transthoracic echocardiography (COECHO). ABF MD was measured using an esophageal Doppler flow probe aligned with descending ABF. All measurements were made under three conditions: dexmedetomidine (20 μg kg–1) intravenously; atipamezole (200 μg kg–1) intramuscularly and atropine (20 μg kg–1) intravenously as needed to achieve a minimum heart rate of 140 beats minute–1; and dopamine (20 μg kg–1 minute–1) intravenously in that order. Correlation between COPATD and COECHO, and COPATD and Doppler MD was evaluated using repeated measures correlation. Agreement between COPATD and COECHO was evaluated using Bland–Altman method. Differences between consecutive pairs of CO measurements were calculated for concordance analysis. ResultsCorrelation between COPATD and COECHO and between COPATD and MD was significant (p < 0.001), with correlation coefficients greater than 0.92. A bias of > 27% and upper limits of agreement of 66% were found between COPATD and COECHO. Concordance rate with COPATD was 76–80% for COECHO and 72% for MD. Conclusions and clinical relevanceEchocardiographic methods for the measurement of CO showed poor agreement and concordance with PATD. MD showed poor concordance with PATD. As such, these methods cannot be used as an alternative to PATD nor can they appropriately track changes in CO in anesthetized cats.

The Impact of PEEP on Ventilation Distribution in ARDS.

The first aim of this study was to evaluate the capacity of electrical impedance tomography (EIT) to identify the effect of PEEP on regional ventilation distribution and the regional risk of collapse, overdistention, hypoventilation, and pendelluft in mechanically ventilated patients. The second aim was to evaluate the feasibility of EIT for estimating airway opening pressure (AOP). The EIT signal was recorded both during baseline cyclic ventilation and slow insufflation for one breath for 9 subjects with moderate-to-severe ARDS. From these data, the AOP and volumes insufflated to lung regions with or without the risk of either collapse, overdistention, hypoventilation, or pendelluft were assessed at 3 PEEP levels (5, 10, and 15 cm H2O). PEEP levels were compared by Friedman analysis of variance and the AOP measured by EIT evaluated using an F-test and the Bland and Altman method. The volume for which there was no specific risk significantly decreased at the highest PEEP from 55 ± 31% tidal volume (VT) at PEEP 5 or 82 ± 18% VT at PEEP 10 to 10 ± 30% VT at PEEP 15 (P = .038 between PEEP 5 vs PEEP 15; P = .01 between PEEP 10 vs PEEP 15). The volume associated with overdistention significantly increased with increasing PEEP, whereas that associated with atelectrauma significantly decreased. Pendelluft significantly decreased with increasing PEEP: VT of 8.9 ± 18.6%, 3.6 ± 7.0%, and 3.2 ± 7.1% for PEEP 5, PEEP 10, and PEEP 15, respectively. The center of ventilation tended to increase in the dependent direction with higher PEEP. The AOPs assessed by EIT and from the pressure-volume curve were in good agreement (bias 0.48 cm H2O). Our results suggest that EIT could aid clinicians in making personalized and reasoned choices in setting the PEEP for subjects with ARDS.

Cucumber Downy Mildew Disease Prediction Using a CNN-LSTM Approach

It is of great significance to develop early prediction technology for controlling downy mildew and promoting cucumber production. In this study, a cucumber downy mildew prediction method was proposed by fusing quantitative disease information and environmental data. Firstly, the number of cucumber downy mildew spores during the experiment was collected by a portable spore catcher, and the proportion of cucumber downy mildew leaf area to all cucumber leaf area was recorded, which was used as the incidence degree of cucumber plants. The environmental data in the greenhouse were monitored and recorded by the weather station in the greenhouse. Environmental data outside the greenhouse were monitored and recorded by a weather station in front of the greenhouse. Then, the influencing factors of cucumber downy mildew were analyzed based on the Pearson correlation coefficient method. The influencing factors of the cucumber downy mildew early warning model in greenhouse were identified. Finally, the CNN-LSTM (Convolutional Neural Network-Long Short-Term Memory) algorithm was used to establish the cucumber downy mildew incidence prediction model. The results showed that the Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and determination coefficient (R2) of the CNN-LSTM network model were 0.069, 0.0098, 0.0991, and 0.9127, respectively. The maximum error between the predicted value and the true value for all test sets was 16.9398%. The minimum error between the predicted value and the true value for all test sets was 0.3413%. The average error between the predicted and true values for all test sets was 6.6478%. The Bland–Altman method was used to analyze the predicted and true values of the test set, and 95.65% of the test set data numbers were within the 95% consistency interval. This work can serve as a foundation for the creation of early prediction models of greenhouse crop airborne diseases.

Study of the functional residual capacity of the lungs caused by nitrogen leaching during multiple respirations and the diffusion capacity of the lungs in patients with bronchial asthma and chronic obstructive pulmonary disease

Relevance. This article discusses the use of nitrogen depletion and lung diffusivity measurements to assess functional lung capacity (FLC) in patients with bronchial asthma (BA) and chronic obstructive pulmonary disease (COPD).Relevance. This article discusses the use of nitrogen depletion and lung diffusivity measurements to assess functional lung capacity (FLC) in patients with bronchial asthma (BA) and chronic obstructive pulmonary disease (COPD).The purpose. Comparative assessment of FRC values measured using diffusion tests and nitrogen-leaching methods during multiple respirations.Material and methods. An observational cross-sectional study was conducted. The examination results of the two groups were compared. Group 1: included 30 patients with BA of 3–4 severity — 13 men (43.4 %) and 17 women (56.6 %); the average age was 50.6±4.3 years at the stage of subsiding exacerbation. Group 2: included 30 patients with moderate COPD — 13 men (43.4 %) and 17 women (56.6 %), average age was 50.6±4.3 years. The functional residual capacity of the lungs was determined using the multiple-breath nitrogen washout method, whereas the diffusion capacity of the lungs. The statistical analysis and visualization of the obtained data were performed using the statistical computing environment R 4.3.0 (R Foundation for Statistical Computing, Vienna, Austria). Differences were considered statistically significant at a p&lt;0.05. The Bland — Altman method was used to assess the consistency of the FRC measurements obtained from the two methods.Results. Two groups of patients were examined: first group — 30 patients with BA of 3–4 severity; second group — 30 patients with COPD. When statistically analyzed between the two methods, no significant differences were observed in the FRC values using the nitrogen washout method and lung diffusivity. The Bland-Altman method produced similar statistical results.Conclusion. Measurement of FRC in patients with asthma and COPD can be performed using both lung diffusivity and multibreath nitrogen washout methods.

Development and validation of a pain scale in guinea pig (Cavia porcellus)

BackgroundThis study aimed to develop and validate a pain assessment scale for guinea pigs to be performed in clinics by veterinarians. The scale was established using pre-existing pain scales from other species and was based on signs expressed by guinea pigs in pain already identified in the literature. The scale consists of 14 descriptors grouped into four categories: appearance, functional, physiological and behavioral. Each item on the scale was assigned a score based on the observation and handling of the animals. The total score obtained ranged from 0 to 26, with more intense pain scoring higher. MethodsFifty-eight adult guinea pigs presenting at the authors' Teaching Hospital between March 2021 and November 2022 were assessed. Guinea pigs were filmed during their consultation and an information sheet was completed. The information sheet provided details on the animals' appetite, fecal production, and behavior at home. The videos and corresponding information sheets were then reviewed to attribute a pain score to each animal. The pain scores were measured twice by a same observer one month apart to assess repeatability and by a second observer to assess reproducibility. The validity was assessed by correlating the pain scores given by the novel scale with scores using a numerical rating scale (NRS) as a gold standard method. ResultsThe initial Cronbach's alpha obtained was 0.77, which was satisfactory. However, it highlighted that items concerning pruritus and spasmodic movements should be deleted to strengthen internal consistency. Then, Lin's coefficient and Bland and Altman's graphical method highlighted that the scale had an almost strong repeatability and intra-operator reproducibility. Moreover, the correlation between pain intensities obtained with the novel scale and the scores given using NRS was correct (Kappa = 0.72). The specificity was 87.5%, but the sensitivity of the scale was 52.0%. Each item's repeatability and reproducibility were assessed to identify items that would benefit from added clarification. ConclusionOur work is the first step in establishing a pain scale in guinea pigs. However, it should not yet be used in a clinical context. Indeed, the scale was not good at detecting pain when a guinea pig was actually painful. Further studies, including improvement of certain items and testing a larger sample of animals, are ongoing.

Financial Distress Analysis to Predict Company Bankruptcy Using the Modified Altman Method

Financial distress is a condition where the company experiences a decline in its financial condition before bankruptcy. To avoid this condition, the company must pay attention to its financial condition both in terms of its balance sheet and income statement using financial statement analysis techniques, such as the Altman model. The purpose of this study is to analyze the occurrence of Financial Distress to predict company bankruptcy using the Modified Altman method using 3 classification categories namely safe, gray, and distress. A quantitative approach was used in this study with a total population of all companies listed on the JII and the sample selection using a purposive sampling technique so that a sample of 13 companies was obtained. Based on the Altman Z-score analysis, the results show that: 8 companies are consistently in the Safe category for 5 years with a cut-off value&gt; 2.9. Then, if analyzed as a whole, the mean value obtained from all companies is 5.7688&gt; 2.9. This value illustrates that on average all companies listed on the Jakarta Islamic Index in 2018-2022 are in the safe category.

Evaluating Agility in Pre-Adolescent Basketball: A Comparative Analysis of CODAT, IAT, and RAT

Background: In basketball, agility is essential, characterized by the ability to change direction swiftly and accelerate. Traditional tests like the Illinois Agility Test (IAT) and the Reactive Agility Test (RAT) may not fully capture the agility demands specific to basketball. Purpose: This study aimed to introduce the Change of Direction and Acceleration Test (CODAT), designed specifically for young basketball players. It evaluates CODAT’s effectiveness by comparing it with IAT and RAT through comprehensive analysis. Methods: We assessed 87 pre-adolescent male basketball players, aged 9 to 13 years, with an average biological age of 11.2 years and an average estimated Peak Height Velocity (PHV) of 12.5 ± 0.5 years, using CODAT, IAT, and RAT. We employed regression analysis and the Bland–Altman method to determine CODAT’s reliability and validity. Results: The findings indicate that CODAT offers superior reliability and validity in measuring basketball-specific agility. Consistent scores highlight its potential as an effective tool for agility assessment in basketball training and talent identification. Conclusions: CODAT represents a significant advancement in agility assessment for young basketball players, advocating for its integration into sports science practices to better address the specialized demands of basketball agility.

“The least significant change on bone mineral density scan increased in patients with higher degrees of obesity”

Background: The least significant change (LSC) threshold of 0.03 g/cm² is used to interpret bone mineral density (BMD) scans in the general population. Our working hypothesis was that the current LSC threshold would not be applicable in obese populations. Aims: The aim of this study was to calculate the LSC in an obese population. Methods: We performed an interventional study among 120 obesity patients, in whom two measurements of BMD were performed at 3 sites. Pairs of measures were used to calculate the LSC, using the Bland and Altman method. Results: We calculated that the LSC was 0.046 g/cm² at the lumbar spine, 0.069 g/cm² at the femoral neck, and 0.06 g/cm² at the total hip. We also calculated the LSC for each class of obesity and observed an increase in LSC with increasing body mass index (BMI). We calculated a LSC of 0.05 g/cm² in patients with class 2 or class 3 obesity, whereas the LSC in patients with class 1 obesity is similar to the threshold used in the general population. Discussion: In obese population, like BMD, LSC is higher than the threshold value of the general population, and increases with increasing BMI.Conclusion: LSC of 0.05 g/cm² could be used in clinical practice in patients with class 2 or 3 obesity. These findings should help to improve the interpretation of BMD scans in these patients and optimize their management. Trial registration number: Comité de Protection des Personnes Ile-de France VII, France.

An Innovative Mathematical Model of the Spine: Predicting Cobb and Intervertebral Angles Using the 3D Position of the Spinous Processes Measured by Vertebral Metrics

Back pain is regularly associated with biomechanical changes in the spine. The traditional methods to assess spine biomechanics use ionising radiation. Vertebral Metrics (VM) is a non-invasive instrument developed by the authors in previous research that assesses the spinous processes’ position. However, the spine model used by VM is not accurate. To overcome it, the present paper proposes a pioneering and simple articulated model of the spine built through the data collected by VM. The model is based on the spring–mass system and uses the Levenberg–Marquardt algorithm to find the arrangement of vertebral bodies. It represents the spine as rigid geometric transformations from one vertebra to the other when the extremity vertebrae are stationary. The validation process used the Bland–Altman method to compare the Cobb and the intervertebral angles computed by the model with the radiographic exams of eight patients diagnosed with Ankylosing Spondylitis. The results suggest that the model is valid; however, previous clinical information would improve outcomes by customising the lower and upper vertebrae positions, since the study revealed that the C6 rotation slightly influences the computed angles. Applying VM with the new model could make a difference in preventing, monitoring, and early diagnosing spinal disorders.