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 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 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 establish an early prediction model for the diagnosis of severe acute pancreatitis based on the improved machine learning models,and to analyze its clinical value.Methods A case-control study was conducted on 352 patients with acute pancreatitis admitted to the Gastroenterology and Hepatobiliary Surgery Departments of the Army Medical Center of PLA and Emergency and Critical Care Medicine Department of No.945 Hospital of Joint Logistics Support Force of PLA from January 2014 to August 2023.According to the severity of the disease,the patients were divided into the severe group(n=88)and the non-severe group(n=264).The RUSBoost model and improved Archimead optimization algorithm was used to analyze 39 routine laboratory biochemical indicators within 48 h after admission to construct an early diagnosis and prediction model for severe acute pancreatitis.The task of feature screening and hyperparameter optimization was completed simultaneously.The ReliefF algorithm feature importance rank and multivariate logistic analysis were used to analyze the value of the selected features.Results In the training set,the area under curve(AUC)of the improved machine learning model was 0.922.In the testing set,the AUC of the improved machine learning model reached 0.888.The 4 key features of predicting severe acute pancreatitis based on the improved Archimedes optimization algorithm were C-reactive protein,blood chlorine,blood magnesium and fibrinogen level,which were consistent with the results of ReliefF algorithm feature importance ranking and multivariate logistic analysis.Conclusion The application of improved machine learning model analyzing the laboratory examination results can help to early predict the occurrence of severe acute pancreatitis.

Objective To explore the clinical characteristics and treatment scheme of patients with spinal infection caused by Prevotella intermedia(P.intermedia).Methods Clinical diagnosis and treatment processes of a patient with spinal infection caused by P.intermedia admitted to the spinal surgery department of a hospital were summa-rized,and relevant literature was retrieved from database for reviewing.Results The patient,a 50 year old male,was admitted to the hospital due to"lumbago pain complicated with pain in double lower extremities for 2 months".The lesion tissue was taken for metagenomic next-generation sequencing(mNGS)detection,which detected P.in-termedia,and the patient was diagnosed with P.intermedia spondylitis.After treatments with open lesion clea-rance,tube rinsing+autologous bone transplantation fusion internal fixation,intravenous drip of ceftriaxone sodium and metronidazole,as well as metronidazole rinsing,infection was under control.A total of 16 available papers were retrieved,together with this case,a total of 17 patients were included,with 7 males and 10 females.The main risk factors were diabetes and history of corticosteroid use(35.3％).The most common invasion sites were lumbar ver-tebra(n=12)and thoracic vertebra(n=6).13 cases were positive for pathogen culture,3 cases were positive for molecular detection,and 1 case was positive for staining microscopy.17 patients received anti-anaerobic bacteria treatment,with 14 cases receiving combined surgical treatment.One case died,with a mortality of 5.9％;5 cases had partial neurological impairment,with a disability rate of 29.4％.The survival rate of patients who received treatment of anti-anaerobic bacteria combined with surgery was 92.8％,3 patients only with anti-anaerobic bacteria treatment but without surgery were all cured.Conclusion P.intermedia is an opportunistic pathogeanic bacteria which often causes infection in immunocomprised individuals and is prone to be misdiagnosed.It is recommended to perform mNGS detection to identify the pathogen as early as possible and seize the opportunity for treatment to reduce mortality.