Objective To explore the effects of air pressure, humidity, wind, and sunshine on the incidence of cardiovascular and cerebrovascular diseases (CVD) in Guiyang, and to provide reference for the prevention of CVD. Methods Using CVD incidence data from September 2021 to August 2022 in Guiyang City and meteorological data including average air pressure, average humidity, wind, and sunshine during the same period, the effects of meteorological factors on CVD incidence were explored and the importance of each factor was analyzed. Results When air pressure was below 868 hPa, above 887 hPa, or between 877 and 883 hPa, and when air pressure dropped less than 5.3 hPa within 24 hours, there was a higher risk of CVD. When the humidity was above 81%, the wind speed was small (<1.2 m/s) or high (>4m/s), and there was less sunlight (less than 3 hours), the risk of CVD was higher. Low humidity (<60%) was not conducive to the onset of CVD. There were highest risks at lag 5~10 days and 4-25 days for high pressure and low sunlight, respectively. When the relative humidity was saturated, there was an immediate effect. When the wind speed was low and high, the immediate effect and hysteresis effects were significant. Among the above meteorological factors, the impact of 24-hour variation of pressure and high or low atmospheric pressure on the incidence of CVD was the most significant, while the impact of sunlight and humidity was the weakest. The impact of diurnal variations in wind and atmospheric pressure was not clear. Conclusion The impact of air pressure on the incidence of CVD does not exhibit a simple linear relationship. The risk of CVD is high in high humidity, low light, and moderate or strong winds. It is necessary to fully consider changes in meteorological factors for CVD prevention and control.

Objective To establish autoverification rules for six routine coagulation assays(PT,APTT,TT,Fib,DD,and FDP)based on the stratification of outpatients and inpatients,in accordance with CLSI AUTO-10A,AUTO-15,and WS/T 616-2018 guide-lines,and to validate the feasibility of this stratified strategy with clinical data while optimizing verification efficiency.Methods A to-tal of 323 451 coagulation test results from Zhongshan Hospital,Fudan University in 2022 were retrospectively analyzed to define auto-verification rules involving critical values,instrument flags,logical rules,historical comparison,and numerical ranges.A stratified au-toverification system was established by applying distinct rules for outpatient and inpatient populations.Subsequently,the rules were op-timized using 87 830 coagulation test results from January to March 2024,and the consistency between autoverification and manual veri-fication was prospectively evaluated using 33 968 consecutive coagulation specimens collected in April 2024.Results A stratified au-toverification system was successfully developed,comprising a total of 53 rules.The pass rate of overall verification was 77.16％(26 210/33 968),with a true-positive rate of 19.64％(6 672/33 968),a false-positive rate of 3.20％(1 086/33 968),a true-nega-tive rate of 77.16％(26 210/33 968),and no false negatives were detected.Conclusion The proposed autoverification system signifi-cantly improved verification efficiency.The stratified design based on outpatient and inpatient populations effectively minimized the risk of false negatives,and may provide a novel approach for the further development and optimization of coagulation test autoverification.

Objective:To compare the differences in specimen results between the intelligent robotic phlebotomy group and the manual venipuncture group, and to evaluate the clinical applicability of the autonomous blood collection system.Methods:From January 20 to October 28, 2022, 154 volunteers at Zhongshan Hospital, Fudan University underwent paired blood collections (robotic and manual) within 5 minutes. The collected samples were analyzed for: hemolysis index (HI), alanine transaminase (ALT), aspartate transaminase (AST), L-γ-glutamyltransferase (γ-GT), lactate dehydrogenase (LDH), urea nitrogen (UREA), creatinine (CRE), uric acid (UA), glucose (GLU), total cholesterol (TC), triglyceride (TG), natrium (Na), kalium (K), chlorine (Cl), creatine kinase (CK), CK-MB, CK-MM, and neuron-specific enolase (NSE). Statistical analyses used t-tests and Wilcoxon signed-rank tests.Results:The results of two different blood collection methods revealed that the HI values of 154 specimens in the intelligent robot blood collection group were all less than 20SI, while 7 specimens (4.54%) in the manual blood collection group had HI values exceeding 20SI; In the comparison of 17 biochemical and immunological markers, there were statistically significant differences between groups in 8 items including γ-GT[20.00(15.00, 37.75)U/L vs. 19.00 (14.00, 36.25)U/L, Z=2.497, P<0.05], LDH[165.5 (147.0, 183.0)U/L vs. 173.0 (155.0, 193.0)U/L, Z=8.629, P<0.05], TC[(5.002±0.856)mmol/L vs.(5.031±0.870) mmol/L, t=-3.006, P<0.05], K[4.1 (4.0, 4.3)mmol/L vs. 4.3 (4.1, 4.4)mmol/L, Z=5.592, P<0.05], CK[97.00 (73.00, 133.00)U/L vs. 99.00 (74.75, 136.25)U/L, Z=3.490, P<0.05], CK-MB[13 (11, 15)U/L vs. 14 (12, 16)U/L, Z=6.581, P<0.05], CK-MM[84.00 (60.00, 119.00)U/L vs. 83.50 (58.75, 118.00)U/L, Z=3.790, P<0.05], and NSE[10.600 (9.500, 11.700)ng/ml vs. 11.950 (10.475, 13.725)ng/ml, Z=8.151, P<0.05]. Conclusions:In the collection of serum samples, intelligent blood collection robots can achieve standardization and normalization of specimen collection volume and mixing in the pre-analysis stage. The hemolysis related indicators of the collected specimens are lower than those of the manual collection group, and can be used for the collection of clinical serological specimens.

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

OBJECTIVE: This study aimed to reexplore minimum iodine excretion and to build a dietary iodine recommendation for Chinese adults using the obligatory iodine loss hypothesis. METHODS: Data from 171 Chinese adults (19-21 years old) were collected and analyzed based on three balance studies in Shenzhen, Yinchuan, and Changzhi. The single exponential equation was accordingly used to simulate the trajectory of 24 h urinary iodine excretion as the low iodine experimental diets offered (iodine intake: 11-26 μg/day) and to further deduce the dietary reference intakes (DRIs) for iodine, including estimated average requirement (EAR) and recommended nutrient intake (RNI). RESULTS: The minimum iodine excretion was estimated as 57, 58, and 51 μg/day in three balance studies, respectively. Moreover, it was further suggested as 57, 58, and 51 μg/day for iodine EAR, and 80, 81, and 71 μg/day for iodine RNI or expressed as 1.42, 1.41, and 1.20 μg/(day·kg) of body weight. CONCLUSION The iodine DRIs for Chinese adults were established based on the obligatory iodine loss hypothesis, which provides scientific support for the amendment of nutrient requirements.
Humans ; Iodine/administration & dosage* ; Male ; Female ; China ; Young Adult ; Diet ; Adult ; Nutritional Requirements ; East Asian People

Objective To establish autoverification rules for six routine coagulation assays(PT,APTT,TT,Fib,DD,and FDP)based on the stratification of outpatients and inpatients,in accordance with CLSI AUTO-10A,AUTO-15,and WS/T 616-2018 guide-lines,and to validate the feasibility of this stratified strategy with clinical data while optimizing verification efficiency.Methods A to-tal of 323 451 coagulation test results from Zhongshan Hospital,Fudan University in 2022 were retrospectively analyzed to define auto-verification rules involving critical values,instrument flags,logical rules,historical comparison,and numerical ranges.A stratified au-toverification system was established by applying distinct rules for outpatient and inpatient populations.Subsequently,the rules were op-timized using 87 830 coagulation test results from January to March 2024,and the consistency between autoverification and manual veri-fication was prospectively evaluated using 33 968 consecutive coagulation specimens collected in April 2024.Results A stratified au-toverification system was successfully developed,comprising a total of 53 rules.The pass rate of overall verification was 77.16％(26 210/33 968),with a true-positive rate of 19.64％(6 672/33 968),a false-positive rate of 3.20％(1 086/33 968),a true-nega-tive rate of 77.16％(26 210/33 968),and no false negatives were detected.Conclusion The proposed autoverification system signifi-cantly improved verification efficiency.The stratified design based on outpatient and inpatient populations effectively minimized the risk of false negatives,and may provide a novel approach for the further development and optimization of coagulation test autoverification.

Objective:To compare the differences in specimen results between the intelligent robotic phlebotomy group and the manual venipuncture group, and to evaluate the clinical applicability of the autonomous blood collection system.Methods:From January 20 to October 28, 2022, 154 volunteers at Zhongshan Hospital, Fudan University underwent paired blood collections (robotic and manual) within 5 minutes. The collected samples were analyzed for: hemolysis index (HI), alanine transaminase (ALT), aspartate transaminase (AST), L-γ-glutamyltransferase (γ-GT), lactate dehydrogenase (LDH), urea nitrogen (UREA), creatinine (CRE), uric acid (UA), glucose (GLU), total cholesterol (TC), triglyceride (TG), natrium (Na), kalium (K), chlorine (Cl), creatine kinase (CK), CK-MB, CK-MM, and neuron-specific enolase (NSE). Statistical analyses used t-tests and Wilcoxon signed-rank tests.Results:The results of two different blood collection methods revealed that the HI values of 154 specimens in the intelligent robot blood collection group were all less than 20SI, while 7 specimens (4.54%) in the manual blood collection group had HI values exceeding 20SI; In the comparison of 17 biochemical and immunological markers, there were statistically significant differences between groups in 8 items including γ-GT[20.00(15.00, 37.75)U/L vs. 19.00 (14.00, 36.25)U/L, Z=2.497, P<0.05], LDH[165.5 (147.0, 183.0)U/L vs. 173.0 (155.0, 193.0)U/L, Z=8.629, P<0.05], TC[(5.002±0.856)mmol/L vs.(5.031±0.870) mmol/L, t=-3.006, P<0.05], K[4.1 (4.0, 4.3)mmol/L vs. 4.3 (4.1, 4.4)mmol/L, Z=5.592, P<0.05], CK[97.00 (73.00, 133.00)U/L vs. 99.00 (74.75, 136.25)U/L, Z=3.490, P<0.05], CK-MB[13 (11, 15)U/L vs. 14 (12, 16)U/L, Z=6.581, P<0.05], CK-MM[84.00 (60.00, 119.00)U/L vs. 83.50 (58.75, 118.00)U/L, Z=3.790, P<0.05], and NSE[10.600 (9.500, 11.700)ng/ml vs. 11.950 (10.475, 13.725)ng/ml, Z=8.151, P<0.05]. Conclusions:In the collection of serum samples, intelligent blood collection robots can achieve standardization and normalization of specimen collection volume and mixing in the pre-analysis stage. The hemolysis related indicators of the collected specimens are lower than those of the manual collection group, and can be used for the collection of clinical serological specimens.

Objective To study the factors influencing the blood concentration of caspofungin(CPFG),construct a prediction model,and validate the predictive effect of the model,so as to provide reference for the individualised dosing of patients with fungal infections in haematology.Methods Seventy-five patients admitted to the Department of Haematology,General Hospital of Tianjin Medical University,who were treated with CPFG for antifungal therapy during the period of March 2021 to June 2022 were selected as the study subjects,and CPFG blood concentration monitoring was carried out to explore the influencing factors of CPFG blood concentration and to construct a prediction model accordingly.Hosmer-Lemeshow(H-L)was used to test the goodness-of-fit of the model,and another 30 patients were selected as the verification group,and the predictive effect of the model was verified by the receiver's operating characteristics(ROC)curve.Results The mean blood concentrations of the patients at 0.5,9 and 24 h were(12.54±4.38),(6.80±2.76),(4.13±2.16)μg·mL-1,and the mean AUC0-24h were(152.05±57.60)μg·mL-1·h.AUC0-24h was lower than the reference value(98 μg·mL-1·h)in two patients.The results of correlation analysis showed that gender showed a correlation with 0.5 h blood concentration(P＜0.05),and there was no correlation with the rest of the two time points blood concentration and AUC0-24h(P＞0.05).Body weight and albumin(Alb)concentration showed correlation with 0.5,9,24 h blood drug concentration and AUC0-24 h(P＜0.05),and the rest of the indicators showed no correlation with blood drug concentration and AUC0_24h at each time point(P＞0.05).The results of multifactorial analysis showed that the factors influencing the patients'0.5 h blood concentration were gender,Alb concentration and body weight,and the factors influencing the 9 and 24 h blood concentration and AUC0-24h were Alb concentration and body weight(P＜0.05).Correlation analysis showed that the daily dose was positively correlated with the plasma concentration of CPFG at 0.5,9 and 24 h and AUC0-24h(P＜0.05).The results of multivariate analysis showed that the daily dose was also one of the influencing factors of the plasma concentration of CPFG(P＜0.05).ROC curve shows that the model has good prediction ability.Conclusion Body weight and Alb are significantly associated with CPFG blood concentrations and area under the drug-time curve,which can be used as a basis for preventive risk avoidance.

To investigate the associations of serum gamma-glutamyl transferase (GGT) levels with the risk of cardiovascular disease (CVD) and its subtypes in patients with type 2 diabetes mellitus (T2DM) in Jiangsu Province.Methods:The participants were enrolled in the Comprehensive Research project regarding 'Prevention and Control of Diabetes' in Jiangsu Province. The baseline survey was conducted from 2013 to 2014, and follow-up until December 31, 2021. After excluding the participants who self-reported with chronic liver disease/stroke/coronary heart disease at baseline survey and those with incomplete information on GGT, a total of 16 147 T2DM patients were included in the final analysis. Cox proportional hazard regression models were used to calculate the hazard ratio ( HR) and their 95% CI of GGT for CVD, myocardial infarction, and stroke. Restricted cubic spline models were applied to analyze the dose-response relationship between GGT and the risk of CVD and its subtypes. Results:During the median follow-up time of 8.02 years, 2 860 CVD cases were registered, including 196 cases of myocardial infarction and 2 730 cases of stroke. Multivariate Cox proportional risk regression model indicated that compared to the lowest serum GGT level group, the highest GGT level group had a 24% increased risk of CVD ( HR=1.24, 95% CI: 1.09-1.41) and a 23% increased risk of stroke ( HR=1.23, 95% CI: 1.08-1.40). The restricted cubic spline model showed a nonlinear dose-response relationship between GGT and the risk of CVD, myocardial infarction, and stroke in T2DM patients. Conclusions:High levels of GGT may be associated with an increased risk of cardiovascular disease in T2DM patients, which needs further exploration and validation in future clinical practice.