A comparison of three approaches to measuring frailty to determine adverse health outcomes in critically ill patients.

BACKGROUND: studies comparing different frailty measures in intensive care unit settings are lacking. We aimed to compare the frailty index based on physiological and laboratory tests (FI-Lab), modified frailty index (MFI) and hospital frailty risk score (HFRS) to predict short-term outcomes for critically ill patients. METHODS: we conducted a secondary analysis of data from the Medical Information Mart for Intensive Care IV database. Outcomes of interest included in-hospital mortality and discharge with need for nursing care. RESULTS: the primary analysis was conducted with 21,421 eligible critically ill patients. After adjusting for confounding variables, frailty as diagnosed by all three frailty measures was found to be significantly associated with increased in-hospital mortality. In addition, frail patients were more likely to receive further nursing care after being discharged. All three frailty scores could improve the discrimination ability of the initial model generated by baseline characteristics for adverse outcomes. The FI-Lab had the best predictive ability for in-hospital mortality, whereas the HFRS had the best predictive performance for discharge with need for nursing care amongst the three frailty measures. A combination of the FI-Lab with either the HFRS or MFI improved the identification of critically ill patients at increased risk of in-hospital mortality. CONCLUSIONS: frailty, as assessed by the HFRS, MFI and FI-Lab, was associated with short-term survival and discharge with need for nursing care amongst critically ill patients. The FI-Lab was a better predictor of in-hospital mortality than the HFRS and MFI. Future studies focusing on FI-Lab are warranted.

Seasonal association between ambient ozone and mortality in Zhengzhou, China.

Different seasonal health effects of ambient ozone (O3) have been reported in previous studies. This might be due to inappropriate adjustment of temperature in different seasons. We used daily data on non-accidental mortality and ambient air pollution in Zhengzhou from January 19, 2013 to June 30, 2015. Season-stratified analyses using generalized additive models were conducted to evaluate the seasonal associations with adjustment of temperature with different lagged days (lag0-1 for warm season, lag0-14 for cold season). We recorded a total of 70,443 non-accidental deaths in Zhengzhou during the study period. Significant associations were observed between ambient O3 and mortality in cold season. Every 10-µg/m3 increment of 24-h O3 of 1-day lagged time was associated with a 1.38% (95% CI 0.60, 2.16%) increase in all cause mortality, 1.35% (95% CI 0.41, 2.30%) increase in cardiovascular mortality, and 1.78% (95% CI 0.43, 3.14%) increase in respiratory mortality. Similar associations were observed when using daily 1- and 8-h maximum concentrations of O3. No significant association was found during warm season. This study suggests a more pronounced ozone-mortality association in cold season in Zhengzhou, and we suggest that different lagged temperatures should be considered when examining the seasonal health effects of ambient ozone.

Enhancing predictive validity of motoric cognitive risk syndrome for incident dementia and all-cause mortality with handgrip strength: insights from a prospective cohort study.

Background: This study aimed to assess whether integrating handgrip strength (HGS) into the concept of motoric cognitive risk (MCR) would enhance its predictive validity for incident dementia and all-cause mortality. Methods: A cohort of 5, 899 adults from the Health and Retirement Study underwent assessments of gait speed, subjective cognitive complaints, and HGS were involved. Over a 10-year follow-up, biennial cognitive tests and mortality data were collected. Cox proportional hazard analyses assessed the predictive power of MCR alone and MCR plus HGS for incident dementia and all-cause mortality. Results: Patients with MCR and impaired HGS (MCR-HGS) showed the highest adjusted hazard ratios (AHR) for dementia (2.33; 95% CI, 1.49-3.65) and mortality (1.52; 95% CI, 1.07-2.17). Even patients with MCR and normal HGS (MCR-non-HGS) experienced a 1.77-fold increased risk of incident dementia; however, this association was not significant when adjusted for socioeconomic status, lifestyle factors, and medical conditions. Nevertheless, all MCR groups demonstrated increased risks of all-cause mortality. The inclusion of HGS in the MCR models significantly improved predictive discrimination for both incident dementia and all-cause mortality, as indicated by improvements in the C-statistic, integrated discrimination improvement (IDI) and net reclassification indices (NRI). Conclusion: Our study underscores the incremental predictive value of adding HGS to the MCR concept for estimating risks of adverse health outcomes among older adults. A modified MCR, incorporating HGS, could serve as an effective screening tool during national health examinations for identifying individuals at risk of dementia and mortality.

Association of frailty and sarcopenia with short-term mortality in older critically ill patients.

BACKGROUND: There is still no study on the use of the SARC-CalF questionnaire for older critically ill patients. Moreover, there is limited evidence on whether a combination of sarcopenia and frailty can provide incremental improvements in risk stratification for older critically ill patients. METHODS: A total of 653 patients older than 60 years were recruited. We used the clinical frailty scale (CFS) and SARC-CalF questionnaire to assess the frailty status and sarcopenia risk, respectively, of older patients shortly after admission to the ICU. The effect of frailty and sarcopenia risk on ICU mortality and 30-day mortality was evaluated. RESULTS: A total of 147 (22.5%) patients died in the ICU, and 187 (28.6%) patients died within 30 days after ICU admission. The CFS score was associated with increased ICU mortality [per 1-score increase: odds ratio (OR) = 1.222, 95% confidential interval (CI): 1.003-1.489] and 30-day mortality (per 1-score increase: OR = 1.307, 95% CI: 1.079-1.583). The SARC-CalF score was also associated with increased ICU mortality (per 1-score increase: OR = 1.204, 95% CI: 1.120-1.294) and 30-day mortality (per 1-score increase: OR = 1.247, 95% CI: 1.163-1.337). The addition of the CFS + SARC-CalF score to Acute Physiology and Chronic Health Evaluation (APACHE) II improved discrimination and reclassified ICU and 30-day mortality risk. CONCLUSIONS: Sarcopenia risk assessed by the SARC-CalF questionnaire provided independent prognostic information for older critically ill patients. A combination of sarcopenia and frailty improved the prediction of mortality for older critically ill patients and thus might be useful in the clinical decision-making process.

Evaluating early lymphocyte-to-monocyte ratio as a predictive biomarker for delirium in older adult patients with sepsis: insights from a retrospective cohort analysis.

Background: This study aims to explore the value of the Lymphocyte-to-Monocyte Ratio (LMR) in predicting delirium among older adult patients with sepsis. Methods: Retrospective data were obtained from the MIMIC-IV database in accordance with the STROBE guidelines. Patients aged 65 and above, meeting the Sepsis 3.0 criteria, were selected for this study. Delirium was assessed using the Confusion Assessment Method for the ICU (CAM-ICU). Demographic information, comorbid conditions, severity of illness scores, vital sign measurements, and laboratory test results were meticulously extracted. The prognostic utility of the Lymphocyte-to-Monocyte Ratio (LMR) in predicting delirium was assessed through logistic regression models, which were carefully adjusted for potential confounding factors. Results: In the studied cohort of 32,971 sepsis patients, 2,327 were identified as meeting the inclusion criteria. The incidence of delirium within this subgroup was observed to be 55%. A univariate analysis revealed a statistically significant inverse correlation between the Lymphocyte-to-Monocyte Ratio (LMR) and the risk of delirium (p < 0.001). Subsequent multivariate analysis, which accounted for comorbidities and illness severity scores, substantiated the role of LMR as a significant predictive marker. An optimized model, achieving the lowest Akaike Information Criterion (AIC), incorporated 17 variables and continued to demonstrate LMR as a significant prognostic factor (p < 0.01). Analysis of the Receiver Operating Characteristic (ROC) curve indicated a significant enhancement in the Area Under the Curve (AUC) upon the inclusion of LMR (p = 0.035). Conclusion: The Lymphocyte-to-Monocyte Ratio (LMR) serves as a significant, independent prognostic indicator for the occurrence of delirium in older adult patients with sepsis. Integrating LMR into existing predictive models markedly improves the identification of patients at elevated risk, thereby informing and potentially guiding early intervention strategies.

Diffusivities and Atomic Mobilities in BCC Ti-Fe-Cr Alloys.

In this research, the diffusion behaviors within the Ti-Fe-Cr ternary system were examined at the temperatures of 1273 K and 1373 K through the diffusion couple technique. This study led to the determination of both ternary inter-diffusion and impurity diffusion coefficients in the body-centered cubic (bcc) phase for the Ti-Fe-Cr alloy, utilizing the Whittle-Green and Hall methods. The statistics show that the average diffusion coefficients D˜FeFeTi and D˜CrCrTi measured at 1273 K were 1.34 × 10-12 and 3.66 × 10-13, respectively. At 1373 K, the average values of D˜FeFeTi and D˜CrCrTi were 4.89 × 10-12 and 1.43 × 10-12. By adopting the CALPHAD method, a self-consistent database for atomic mobility in the bcc phase of the Ti-Fe-Cr system was established. This database underwent refinement by comparing the newly acquired diffusion coefficients with data from the existing literature. Diffusion simulations for the diffusion couples were performed, drawing on the established database. The error between the simulated diffusion coefficient and the experimental measurement data is within 15%, and the simulated data of the component distance distribution and diffusion path are in good agreement with the experimental data. The simulations generated results that aligned well with the observed experimental diffusion characteristics, thereby affirming the reliability and accuracy of the database.

Association of Frailty with Adverse Outcomes in Patients with Critical Acute Myocardial Infarction: A Retrospective Cohort Study.

Background: Frailty is a risk factor for acute myocardial infarction (AMI). This study examined the association between the modified frailty index (MFI) and adverse outcomes in patients with critical AMI. Methods: Data were obtained from the Medical Information Mart for Intensive Care IV database. Logistic and Cox regression models and a competing risk model were applied. Results: Of 5003 patients, 1496 were non-frail and 3507 were frail. Frailty was significantly associated with in-hospital mortality (per point, OR 1.13, 95% CI: 1.05-1.21; frail vs non-frail, OR 1.31, 95% CI: 1.04-1.65) and 1-year mortality (per point, HR 1.15, 95% CI: 1.11-1.20; frail vs non-frail, HR 1.37, 95% CI: 1.20-1.58). Frailty was significantly associated with post-discharge care needs (per point, OR 1.23, 95% CI: 1.14-1.33; frail vs non-frail, OR 1.47, 95% CI: 1.22-1.78). In the competing risk models, frailty was significantly associated with a lower probability of being discharged from the ICU (per point, HR 0.87, 95% CI: 0.85-0.90; frail vs non-frail, HR 0.73, 95% CI: 0.68-0.79) and hospital (per point, HR 0.82, 95% CI: 0.80-0.85; frail vs non-frail, HR 0.62, 95% CI: 0.57-0.68). Subgroup analyses showed the association of frailty with in-hospital and 1-year mortality was stronger in patients with a SOFA score ≤2 than in those with a SOFA score >2 (both p<0.05 for interaction). Conclusion: Frailty assessed by the MFI was an independent predictor of adverse outcomes in patients with critical AMI and may be helpful for prognostic risk stratification.

Motoric cognitive risk syndrome as a predictor of incident disability: A 7 year follow-up study.

Background: Though motoric cognitive risk syndrome (MCR) share risk factors with disability, whether it predict disability remains understudied. Objectives: This study aims to examine the association between MCR and incident disability. Design: Longitudinal study. Methods: MCR was defined as subjective cognitive complaints and objective slow gait speed. Two subtypes of MCR were defined by whether memory impairment (MI) was also present, MCR-MI and MCR-non-MI. Incident activities of daily living (ADL) disability and instrumental activities of daily living (IADL) disability were outcome measures. Multiple logistic regression analysis was used to assess the independent effect of MCR at baseline on the odds of ADL/IADL disability at a 7 year follow-up. Results: Among the subjects who were not disabled at baseline and followed for 7 years, 34.66% reported incident ADL disability, and 31.64% reported incident IADL disability. Compared with participants without MCR at baseline, those with MCR had 58% increased odds of incident ADL disability (OR=1.58, 95% CI: 1.19-2.09) and 46% increased odds of incident IADL disability (OR=1.46, 95% CI: 1.13-1.88) after 7 years. MCR-non-MI was associated with a 56.63% increased risk of ADL disability and a 34.73% increased risk of IADL disability. MCR-MI was associated with an even higher risk of IADL disability (OR = 2.14, 95% CI: 1.18-3.88). Conclusions: MCR is an independent risk factor for both incident ADL and IADL disability. MCR-MI predicts a higher risk for disability than MCR-non-MI. Early identification of MCR among older adult is recommended and may decrease future risk of disability.

Orientation Control for Nickel-Based Single Crystal Superalloys: Grain Selection Method Assisted by Directional Columnar Grains.

The service performance of single crystal blades depends on the crystal orientation. A grain selection method assisted by directional columnar grains is studied to control the crystal orientation of Ni-based single crystal superalloys. The samples were produced by the Bridgman technique at withdrawal rates of 100 µm/s. During directional solidification, the directional columnar grains are partially melted, and a number of stray grains are formed in the transition zone just above the melt-back interface. The grain selected by this method was one that grew epitaxially along the un-melted directional columnar grains. Finally, the mechanism of selection grain and application prospect of this grain selection method assisted by directional columnar grains is discussed.

Study on the Effect of Pre-Refinement and Heat Treatment on the Microstructure and Properties of Hypoeutectic Al-Si-Mg Alloy.

Hypoeutectic Al-Si-Mg alloys with a silicon content of around 10 wt % are widely used in the aerospace and automotive fields due to their excellent casting properties. However, the occurrence of "silicon poisoning" weakens the refinement effect of a conventional refiner system such as Al-5Ti-1B. In this paper, we proposed the "pre-refinement" method to avoid the "Si poisoning" to recover the refinement effect of Al-5Ti-1B. The core concept was to adjust the order of adding the Si element to form the TiAl3 before forming the Ti-Si intermetallic compound. To prove the effectiveness of the "pre-refinement" method, three alloys of "pre-refinement", "post-refinement", and "non-refinement" of an Al-10Si-0.48Mg alloy were prepared and characterized in as-cast and heat-treatment states. The results showed that the average grain diameter of the "pre-refinement" alloy was 60.19% smaller than that of the "post-refinement" one and 81.34% smaller than that of the "non-refinement" one, which demonstrated that the proposed method could effectively avoid the "silicon poisoning" effect. Based on a refined grain size, the "pre-refinement" Al-10Si-0.48Mg alloy showed the best optimization effect in mechanical properties after a solid-solution and subsequent aging heat treatments. The best mechanical properties were found in the "pre-refinement" alloy with 2 h of solid solution treatment and 10 h of aging treatment: a hardness of 92 HV, a tensile strength of 212 MPa, and an elongation of 20%.

Association between frailty and short- and long-term mortality in patients with critical acute myocardial infarction: Results from MIMIC-IV.

Background: Frailty has been recognized as an important prognostic indicator in patients with acute myocardial infarction (AMI). However, no study has focused on critical AMI patients. We aimed to determine the impact of frailty on short- and long-term mortality risk in critical AMI patients. Methods: Data from the Medical Information Mart for Intensive Care (MIMIC)-IV database was used. Frailty was assessed using the Hospital Frailty Risk Score (HFRS). Outcomes were in-hospital mortality and 1-year mortality. Logistic regression and Cox proportional-hazards models were used to investigate the association between frailty and outcomes. Results: Among 5,003 critical AMI patients, 2,176 were non-frail (43.5%), 2,355 were pre-frail (47.1%), and 472 were frail (9.4%). The in-hospital mortality rate was 13.8%, and the 1-year mortality rate was 29.5%. In our multivariable model, frailty was significantly associated with in-hospital mortality [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.20-1.41] and 1-year mortality [hazard ratio (HR) = 1.29, 95% CI: 1.24-1.35] as a continuous variable (per five-score increase). When assessed as categorical variables, pre-frailty and frailty were both associated with in-hospital mortality (OR = 2.80, 95% CI: 2.19-3.59 and OR = 2.69, 95% CI: 1.93-3.73, respectively) and 1-year mortality (HR = 2.32, 95% CI: 2.00-2.69 and HR = 2.81, 95% CI: 2.33-3.39, respectively) after adjustment for confounders. Subgroup analysis showed that frailty was only associated with in-hospital mortality in critically ill patients with non-ST-segment elevation myocardial infarction (STEMI) but not STEMI (p for interaction = 0.012). In addition, frailty was associated with 1-year mortality in both STEMI and non-STEMI patients (p for interaction = 0.447). The addition of frailty produced the incremental value over the initial model generated by baseline characteristics for both in-hospital and 1-year mortality. Conclusion: Frailty, as assessed by the HFRS, was associated with both in-hospital and 1-year mortality in critical AMI patients. Frailty improves the prediction of short- and long-term mortality in critical AMI patients and may have potential clinical applications.

Frailty index based on laboratory tests improves prediction of short-and long-term mortality in patients with critical acute myocardial infarction.

Background: Previous studies have shown that the frailty index based on laboratory tests (FI-Lab) can identify older adults at increased risk of adverse health outcomes. This study aimed to determine whether the FI-Lab is associated with mortality risk and can provide incremental improvements in risk stratification of patients with critical acute myocardial infarction (AMI). Materials and methods: We conducted a secondary analysis of data from the Medical Information Mart for Intensive Care (MIMIC)-IV database. A 33-item FI-Lab was constructed. Outcomes of interest were in-hospital and 1-year mortality. Logistic regression models were used to investigate the association between the FI-Lab and outcomes. For the assessment of the incremental predictive value, the FI-Lab was added to several risk stratification scoring systems for critically ill patients, and the following indices were calculated: Δ C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Results: Out of 2,159 patients, 477 died in hospital (22.1%), and 898 died during the 1-year follow-up period. After adjustment for confounders, the FI-Lab was associated with increased in-hospital mortality [odds ratio (OR) = 1.06, 95% confidence interval (CI): 1.05-1.07] and 1-year mortality (OR = 1.05, 95% CI: 1.04-1.06) when assessed as a continuous variable (per 0.01-score increase). When assessed as a categorical variable, the FI-Lab was associated with in-hospital mortality (2nd Quartile: OR = 1.89, 95% CI: 1.18-3.03; 3rd Quartile: OR = 3.46, 95% CI: 2.20-5.46; and 4th Quartile: OR = 5.79, 95% CI: 3.61-9.28 compared to 1st Quartile) as well as 1-year mortality (2nd Quartile: OR = 1.66, 95% CI: 1.23-2.24; 3rd Quartile: OR = 2.40, 95% CI: 1.76-3.26; and 4th Quartile: OR = 3.76, 95% CI: 2.66-5.30 compared to 1st Quartile) after adjustment for confounders. The addition of the FI-Lab to all disease severity scores improved discrimination and significantly reclassified in-hospital and 1-year mortality risk. Conclusion: The FI-Lab was a strong predictor of short- and long-term mortality in patients with critical AMI. The FI-Lab improved the ability to predict mortality in patients with critical AMI and therefore might be useful in the clinical decision-making process.

Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks.

Machine learning methods are a novel way to predict and rank donors' willingness to donate blood and to achieve precision recruitment, which can improve the recruitment efficiency and meet the challenge of blood shortage. We collected information about experienced blood donors via short message service (SMS) recruitment and developed 7 machine learning-based recruitment models using PyCharm-Python Environment and 13 features which were described as a method for ranking and predicting donors' intentions to donate blood with a floating number between 0 and 1. Performance of the prediction models was assessed by the Area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score in the full dataset, and by the accuracy in the four sub-datasets. The developed models were applied to prospective validations of recruiting experienced blood donors during two COVID-19 pandemics, while the routine method was used as a control. Overall, a total of 95,476 recruitments via SMS and their donation results were enrolled in our modelling study. The strongest predictor features for the donation of experienced donors were blood donation interval, age, and donation frequency. Among the seven baseline models, the eXtreme Gradient Boosting (XGBoost) and Support vector machine models (SVM) achieved the best performance: mean (95%CI) with the highest AUC: 0.809 (0.806-0.811), accuracy: 0.815 (0.812-0.818), precision: 0.840 (0.835-0.845), and F1 score of XGBoost: 0.843 (0.840-0.845) and recall of SVM: 0.991 (0.988-0.994). The hit rate of the XGBoost model alone and the combined XGBoost and SVM models were 1.25 and 1.80 times higher than that of the conventional method as a control in 2 recruitments respectively, and the hit rate of the high willingness to donate group was 1.96 times higher than that of the low willingness to donate group. Our results suggested that the machine learning models could predict and determine the experienced donors with a strong willingness to donate blood by a ranking score based on personalized donation data and demographical details, significantly improve the recruitment rate of blood donors and help blood agencies to maintain the blood supply in emergencies.

[Value of interleukin-6 and CD4+ T-lymphocytopenia in assessing the severity and prognosis of coronavirus disease 2019].

OBJECTIVE: To evaluate the role of interleukin-6 (IL-6) and CD4+ T-lymphocytopenia in assessing the severity and prognosis of coronavirus disease 2019 (COVID-19). METHODS: A prospective observational study was conducted. Forty-five patients with COVID-19 admitted to Henan Provincial People's Hospital from January 13 to March 13, 2020 were enrolled and divided into normal group (13 cases), severe group (20 cases), critically severe group (12 cases) according to the severity of the disease. A total of 15 healthy subjects receiving physical examinations during the same period were collected as the healthy control group. Clinical data were collected to compare the clinical characteristics, general test results, IL-6 and CD4+ T-lymphocytopenia levels of patients in different disease severity groups and healthy control group. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of each indicator for the severity of COVID-19. Multivariate Cox regression analysis was used to analyze the risk factors affecting the prognosis of COVID-19 patients, and Kaplan-Meier survival curve analysis was performed. RESULTS: The age of the critically severe group was significantly higher than that of the severe and normal groups (years old: 66.91±17.01 vs. 59.35±18.07, 40.23±12.61, both P < 0.05), and the negative conversion time of the 2019 novel coronavirus (2019-nCoV) was significantly longer than that of the severe and normal groups (days: 19.00±10.66 vs. 18.00±7.18, 9.31±3.49, both P < 0.05). With the increase of the severity of disease, white blood cell count (WBC), C-reactive protein (CRP), calcitonin (PCT), total bilirubin (TBil), troponin I (TnI), IL-6, D-dimer and other indicators were significantly increased, while lymphocyte count (LYM), platelet count (PLT), CD4+, CD8+, oxygenation index (PaO2/FiO2) were significantly decreased (all P < 0.01). ROC curve showed that PaO2/FiO2, IL-6 and CD4+ had certain predictive value for disease severity of COVID-19, the area under the ROC curve (AUC) of them were 0.903, 0.871, 0.689, and the 95% confidence interval (95%CI) were 0.806-0.949, 0.769-0.974, 0.542-0.853; the best cut-off values were 196.00 mmHg (1 mmHg = 0.133 kPa), 6.02 ng/L, 355 cells/µL, respectively; the sensitivity were 73.3%, 99.3%, 73.3%, and the specificity were 96.6%, 62.1%, 65.5%, respectively. Multivariate Cox regression analysis showed that age, PaO2/FiO2, high IL-6 and low CD4+ (IL-6 ≥ 6.02 ng/L and CD4+ < 355 cells/µL) were independent risk factors affecting the prognosis of COVID-19 [hazard ratio (HR) was 1.077, 0.053 and 3.490, respectively, all P < 0.05]. Kaplan-Meier survival analysis showed that when both high IL-6 and low CD4+ (IL-6 ≥ 6.02 ng/L and CD4+ < 355 cells/µL) were present, the mean time of adverse prognosis was (20.53±5.71) days; when increased IL-6 and decreased CD4+ were inconsistent, the mean time of adverse prognosis was (53.21±3.16) days. CONCLUSIONS: The levels of IL-6 and CD4+ T-lymphocytopenia are closely related to the severity of COVID-19 disease. When IL-6 ≥ 6.02 ng/L and CD4+ < 355 cells/µL occur simultaneously, the prognosis is poor.

Diffusivities and Atomic Mobilities in bcc Ti-Mo-Zr Alloys.

ß-type (with bcc structure) titanium alloys have been widely used as artificial implants in the medical field due to their favorable properties. Among them, Ti-Mo alloy attracted numerous interests as metallic biomaterials. Understanding of kinetic characteristics of Ti alloys is critical to understand and manipulate the phase transformation and microstructure evolution during homogenization and precipitation. In this work, diffusion couple technique was employed to investigate the diffusion behaviors in bcc Ti-Mo-Zr alloys. The diffusion couples were prepared and annealed at 1373 K for 72 h and 1473 K for 48 h, respectively. The composition-distance profiles were obtained via electron probe micro-analysis (EPMA). The chemical diffusion coefficients and impurity diffusion coefficients were extracted via the Whittle-Green method and Hall method. The obtained diffusion coefficients were assessed to develop a self-consistent atomic mobility database of bcc phase in Ti-Mo-Zr system. The calculated diffusion coefficients were compared with the experimental results. They showed good agreement. Simulations were implemented by Dictra Module in Thermo-Calc software. The predicted composition-distance profiles, inter-diffusion flux, and diffusion paths are consistent with experimental data, confirming the accuracy of the database.