OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

ObjectiveBased on the clinical characteristics of chronic gouty arthritis （CGA） in both traditional Chinese and western medicine， this study aims to systematically evaluate the clinical concordance of existing CGA animal models， providing recommendations for establishing animal models that align with the pathological characteristics of CGA and the manifestations of traditional Chinese medicine syndromes. MethodsBy comprehensively retrieving Chinese and international databases such as China National Knowledge Infrastructure， Wanfang， VIP Chinese Science and Technology Periodical Database （VIP）， and PubMed， all relevant literature on CGA animal models was collected. Based on the guidelines， the diagnostic criteria of both traditional Chinese and western medicine were summarized and organized. The evaluation indicators for the CGA model were constructed with reference to existing evaluation modes， and the CGA animal models were analyzed to systematically evaluate the clinical concordance of existing models. ResultsThe current methods used to construct CGA animal models mainly include monosodium urate crystal induction， high-protein diet induction （poultry lack urate oxidase）， and high-fat diet combined with urate oxidase inhibitors and joint injection. Based on 11 pieces of included literature， the traditional Chinese and western medicine scoring data of each model were extracted， and the average scoring values of all models were ultimately calculated. The results show that the average clinical concordances of existing CGA animal models in both traditional Chinese and western medicine are 43.33% and 64.44%， respectively. Among them， the model with the highest clinical concordance rate is the one with a high-fat diet combined with potassium oxonate to induce hyperuricemia plus joint injection， achieving 83.33% clinical concordance in western medicine and 60% in traditional Chinese medicine. This model aligns well with the pathogenic characteristics and pathological changes of clinical CGA. ConclusionAlthough current CGA animal models can simulate some pathological characteristics of CGA， they struggle to comprehensively reflect the complex pathological processes of CGA and the characteristics of traditional Chinese medicine syndromes. Therefore， in the future， it is necessary to establish the CGA animal models that incorporate the clinical disease and syndrome characteristics of traditional Chinese and western medicine and formulate the uniform model evaluation criteria， providing more precise tools for CGA mechanism research and the development of traditional Chinese medicine.

OBJECTIVE: To observe the effect of electroacupuncture (EA) pretreatment of "biaoben acupoint combination" on cardiomyocyte mitochondrial fission in the rats with myocardial ischemia-reperfusion injury (MIRI) and explore its mechanism. METHODS: Fifty male SD rats were randomly divided into a sham-operation group, a model group, an EA pretreatment group, an EA pretreatment + Compound C group and an EA pretreatment+ML385 group, 10 rats in each group. In the EA pretreatment, the EA pretreatment + Compound C group and the EA pretreatment+ML385 group, EA was delivered at bilateral "Neiguan" (PC6), "Zusanli" (ST36) and "Guanyuan" (CV4) for 20 min, with continuous wave and 2 Hz of frequency, 1 mA of current, once daily for consecutive 7 days. On day 8, in the EA pretreatment + Compound C group and the EA pretreatment+ML385 group, 30 min before model preparation, the intraperitoneal injection with Compound C (0.3 mg/kg) and ML385 (30 mg/kg) was administered respectively. Except in the sham-operation group, the ligation of the left anterior descending coronary artery was performed to prepare MIRI rat model in the rest groups. In the sham-operation group, the thread was not ligated. After modeling, the content of reactive oxygen species (ROS) in the ischemic area was measured by flow cytometry, superoxide dismutase (SOD) was detected using xanthine oxidase method, and malondialdelyde (MDA) was detected using thiobarbituric acid (TBA) chromatometry. The morphology of myocardial tissue in the ischemic area was observed with HE staining, and the mitochondria ultrastructure of cardiomyocytes observed under transmission electron microscopy. Using immunofluorescence analysis, the positive expression of mitochondrial fission factor (MFF), mitochondrial fission 1 protein antibody (Fis1) and dynamin-related protein 1 (Drp1) was detected; and with immunohistochemical method used, the protein expression of adenosine monophosphate-activated protein kinase (AMPK), nuclear factor E2-associated factor2 (Nrf2) and Drp1 in the ischemic area was detected. RESULTS: Compared with the sham-operation group, the content of ROS and MDA in the myocardial tissue of the ischemic area, and the positive expression of MFF, Fis1 and Drp1 increased in the model group (P<0.01); the content of SOD and the protein expression of AMRK and Nrf2 decreased (P<0.01), and the protein expression of Drp1 elevated (P<0.01). Compared with the model group, the content of ROS and MDA in the myocardial tissue of the ischemic area, and the positive expression of MFF, Fis1 and Drp1 were dropped in the EA pretreatment group (P<0.01); the content of SOD and the protein expression of AMRK and Nrf2 rose (P<0.01), and the protein expression of Drp1 declined (P<0.01); and in the EA pretreatment+Compound C group and the EA pretreatment+ML385 group, the positive expression of MFF, Fis1 and Drp1, and the protein expression of Drp1 were all reduced (P<0.01). When compared with the EA pretreatment + Compound C group and the EA pretreatment+ML385 group, the content of ROS and MDA in the myocardial tissue of the ischemic area, and the positive expression of MFF, Fis1 and Drp1 were dropped in the EA pretreatment group (P<0.01); the content of SOD and the protein expression of AMRK and Nrf2 rose (P<0.01, P<0.05), and the protein expression of Drp1 decreased (P<0.05). In comparison with the model group, the EA pretreatment+Compound C group and the EA pretreatment+ML385 group, the cardiac muscle fiber rupture, cell swelling and mitochondrial disorders were obviously alleviated in the EA pretreatment group. The morphological changes were similar among the model group, the EA pretreatment+Compound C group and the EA pretreatment+ML385 group. CONCLUSION Electroacupuncture pretreatment of "biaoben acupoint combination" attenuates myocardial injury in MIRI rats, probably through promoting the phosphorylation of AMPK and Nrf2, inhibiting the excessive mitochondrial fission induced by Drp1, and reducing mitochondrial dysfunction caused by mitochondrial fragmentation and vacuolation.
Animals ; Electroacupuncture ; Male ; Rats, Sprague-Dawley ; Myocardial Reperfusion Injury/physiopathology* ; Myocytes, Cardiac/cytology* ; Rats ; Acupuncture Points ; Mitochondrial Dynamics ; Humans ; Reactive Oxygen Species/metabolism* ; NF-E2-Related Factor 2/genetics* ; Superoxide Dismutase/metabolism*

This study was aimed at analyzing the biotypes and genetic diversity characteristics of five non-major Brucella species,to provide a scientific basis for understanding the species diversity of Brucella and strengthening pathogen monitoring and control.According to the biotypes(species,hosts,isolation locations,and time)and MLVA-16 genotypes(MLVA-16 lo-cus data,MLVA-11 genotypes)of five non-major pathogenic Brucella in the international MLVA database,we used Bionu-merics 8.0 software and PHYLOVIZ2.0 online software to analyze the geographical origin and genetic diversity characteristics of strains.A total of 227 strains were studied,including 121 Brucella ceti,47 B.pinnipedialis,37 Brucella ovis,11 B.mi-croti,and Brucella neotomae.The greatest host diversity was observed for B.ceti,followed by B.pinnipedialis and B.mi-croti.B.ceti was distributed in European and South American countries;B.pinnipedialiswas distributed in Europe;and B.microti.was distributed in the Czech Republic,Austria,and Hungary in Central Europe.B.ovis was widely distributed in Af-rica,Argentina,Australia,Brazil,Greece,the United States,Spain,and France.The MLVA-11 genotypes of different types of Brucella showed high polymorphism and large differences,thus suggesting that the strains have different geographical ori-gins.MST analysis indicated that the studied strains were divided into four branches(BCⅠ-Ⅳ),among which B.ceti was di-vided into two different branches(BC-Ⅰ and BC-Ⅱ),the strains of other types formed different branches(or sub-branches),and the strains of different types showed clear regional and dominant host characteristics.Genetic correlation analysis of strains of the Brucella genus revealed that non-major pathogenic Brucella had clear genetic,distribution,and host spectrum differ-ences with respect to four classical pathogenic Brucella species.Five non-major pathogenic Brucella strains presented unique genetic evolutionary patterns,geographical distributions,and host tropism characteristics,thereby providing new insight for understanding the biological and genetic diversity of those Brucella strains.

Objective To observe the value of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies.Methods Totally 118 fetuses with intracranial anomalies diagnosed through cranial MRI/induced labor specimen dissection who underwent prenatal ultrasound examination were retrospectively enrolled.Two-dimensional,three-dimensional ultrasound and microvascular flow imaging manifestations of fetal intracranial anomalies were observed,and the accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was analyzed.Results The accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was 93.22％(110/118),of isolated and non-isolated intracranial anomalies was 97.47％(77/79)and 84.62％(33/39),respectively.Six fetuses were missed diagnosis of malformations of cortical development(1 fetus of tuberous sclerosis,4 of abnormal morphology of the sulci gyrus and 1 of schizencephaly)and 1 fetus of intracranial softening lesion,while posterior fossa arachnoid cyst in 1 fetus was misdiagnosed as mega cisterna magna.Conclusion The accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was relatively high.

Objective:To evaluate the alveolar ridge preservation effect of immediate implantation at extraction site with the im-proved CBCT measuring method.Methods:Eighty patients with extraction site were divided into test group A,B,C and control group.The patients were treated by means of immediate implant placement combined with large flap surgery,guided bone regener-ation(GBR)using mass Bio-Oss bone particles in the group A(the thickness of facial bone wall＜1 mm);The patients were trea-ted by means of immediate implant placement combined without flap surgery and bone graft in the group B(the thickness of facial bone wall ≥1 mm and＜2 mm)and C(the thickness of facial bone wall ≥2 mm),the CGF was implanted in the jumping space only when the thickness of jumping space was＞2 mm.In the control group,the alveolar sockets healed naturally without any in-tervention or treatment.CBCT was taken before surgery,immediately after surgery,and 6 months after surgery to evaluate the height and width of alveolar bone,the thickness of facial bone wall and jumping space.Results:The reduction of alveolar ridge height in group A,B,C and control group was(0.41±0.13,0.94±0.18,0.59±0.12,1.31±0.19)mm,The reduction of alveolar ridge width in group A,B,C and control group was(0.93±0.10,1.48±0.21,1.12±0.17,1.66±0.16)mum.The re-sults of four groups were statistically different(F=177.0,P＜0.001;F=125.3,P＜0.001).The alveolar ridge thickness of facial bone wall in group A,B,C and con-trol group was(0.98±0.25,2.39±0.28)mm,(1.43±0.52,2.10±0.33)mm,(2.17±0.41,2.79±0.27)mm before surgery and six months after immediate implantation.The results of each group were statistically different between before surgery and six months after immediate implantation(t=16.45,P＜0.001;t=7.357,P＜0.001;t=5.488,P＜0.001).Patients in three test groups had the thickness of jumping space＞2 mm and ≤2 mm,and the reduction of alveolar ridge width was(0.78±0.18,0.88±0.17)mm.The results were statistically different(t=17.18,P=0.018).Conclusion:The alveolar ridge preservation was obtained by means of immediate implant placement combined with large flap surgery,guided bone regeneration(GBR)using mass Bio-Oss bone particles at extraction site with the thickness of facial bone wall＜1 mm;The alveolar ridge preservation was obtained without flap surgery and GBR at extraction site with the thickness of facial bone wall≥1 mm.The preservation of soft and hard tissue was better in the axial palatal side of immediate implantation with the thickness of jumping space＞2 mm than that with the thickness of jumping space≤2 mm.

BACKGROUND:Hemivertebra deformity should be treated surgically at an early age,but the risk factors for progression of deformity after hemivertebral resection have not been established.OBJECTIVE:To investigate the curative effect of one-stage posterior hemivertebrae resection and pedicle screw fixation in the treatment of congenital scoliosis,and to further explore the risk factors causing the progression of postoperative deformity.METHODS:The medical records of patients who underwent pedicle screw-rod fixation for unilateral hemivertebral deformity from January 2012 to February 2020 and were followed up for at least 2 years were retrospectively analyzed,and a total of 116 patients met the inclusion criteria.All patients were treated with standing anterior and lateral spinal radiographs taken before,after and at each follow-up time point.The segment Cobb angle,the total scoliosis Cobb angle,the proximal complementary Cobb angle,the distal complementary Cobb angle,and the coronal balance distance,apical vertebra distance,upper instrumented vertebra tilt,upper instrumented vertebra disc angle,lower instrumented vertebra tilt,lower instrumented vertebra disc angle,segmental kyphosis/lordosis,thoracic kyphosis,lumbar lordosis and sagittal vertical axis were measured.The progression of deformity and complications were also recorded.RESULTS AND CONCLUSION:(1)Segment Cobb,total scoliosis Cobb,segmental kyphosis,proximal complementary Cobb,and distal complementary Cobb were significantly corrected after operation(P＜0.05),and remained corrected at the last follow-up.Thoracic kyphosis,lumbar lordosis,coronal balance distance,and sagittal vertical axis were all in the normal range pre-operation,after operation and at the last follow-up.(2)During follow-up,10 patients developed coronary decompensation,which was characterized by abnormal progression.(3)Independent sample t-test showed that preoperative total scoliosis Cobb,preoperative apical vertebra distance,age,Risser sign,postoperative upper instrument vertebra tilt and postoperative lowest instrumented vertebra tilt were correlated with postoperative malformation progression(P＜0.05).(4)Multivariate Logistic regression analysis showed that postoperative lowest instrumented vertebra tilt was an independent risk factor for postoperative malformation progression(P=0.002,OR=1.526).(5)Receiver operating characteristic curve analysis showed that a postoperative lowest instrumented vertebra tilt of 8.14° was the optimal threshold for deformity progression after hemivertebrae resection and pedicle rod fixation(sensitivity 0.900,specificity 0.906,area under curve:0.926).(6)It is indicated that the treatment of congenital scoliosis with one-stage posterior hemivertebrae resection and pedicle nail fixation can achieve satisfactory orthopedic effect.Postoperative lowest instrumented vertebra tilt greater than 8.14° was an independent risk factor for postoperative coronal decompensation.

Aberrant expression of Colgalt1 is closely associated with tumorigenesis and tumor progres-sion;however,the mechanism by which it regulates macrophages to influence tumor development remains poorly understood.This study aimed to establish a macrophage-specific Colgalt1 gene knockout mouse model to delve into the mechanisms through which Colgalt1 modulates macrophage function and subse-quently affects the occurrence and progression of tumor-related diseases.Initially,Colgalt1flox+mice were generated using gene editing techniques,followed by crossing with Lyz2-Cre+mice,which exhibit tissue-specific expression in the myeloid lineage(including monocytes and mature macrophages).Through this strategy,mice with the genotype Colgalt1-/-Lyz2-Cre+were successfully obtained,achieving conditional knockout of the Colgalt1 gene in macrophages.Colgalt1flox/flox Lyz2-Cre-mice were used as control.PCR and agarose gel electrophoresis were employed to identify the Flox and Cre genotypes of the knockout mice.RT-qPCR and Western Blot techniques were utilized to detect the expression levels of Colgalt1 in BMDMs from knockout mice at both the mRNA and protein levels,respectively.Western Blot results re-vealed a significant downregulation of Colgaltl expression in BMDMs from knockout mice compared to controls(P＜0.01).RT-qPCR results demonstrated a significant reduction in Colgalt1 mRNA levels in BMDMs from knockout mice compared to contro1s(P＜0.001),while no significant differences in Col-galt1 mRNA expression were observed in liver,lung,or spleen tissues between the two groups.Addition-ally,immunohistochemistry was employed to detect Colgalt1 expression in liver-specific macrophages,re-vealing an absence of Colgalt l-positive staining in liver macrophages from knockout mice.HE staining was used to observe cellular morphology in liver tissues from both groups of mice,showing no significant differences in cellular morphology or obvious pathological changes in tissues and organs.Moreover,the o-verall survival of the mice was not affected.Finally,RT-qPCR was used to assess the expression of mac-rophage-related inflammatory factors in BMDMs from both groups of mice.The results indicated that com-pared to controls,knockout mice exhibited downregulated expression of TNF-α(P＜0.05)and signifi-cantly upregulated expression of IL-10(P＜0.01),Arginase1(P＜0.001),and CD206(P＜0.001)in BMDMs,suggesting an anti-inflammatory trend and M2 polarization of macrophages following Colgalt 1 knockout.In summary,this study successfully established a macrophage-specific Colgalt1 gene knockout mouse model,providing a more reliable experimental animal model for in-depth exploration of the specific roles of Colgalt1 in macrophage functional regulation and the pathogenesis of tumor-related diseases.This model holds promise for identifying novel therapeutic targets and strategies for tumors and other diseases.

Objective:To investigate the iodine nutrition level and the prevalence of thyroid nodules in pregnant women in Hubei Province, and to provide a basis for prevention and treatment of iodine deficiency disorders.Methods:According to the requirements of the National Iodine Deficiency Disorders Monitoring Program (2016 Edition), a cross-sectional survey of iodine nutrition status of pregnant women ( n = 321) was conducted from July to October 2020 in two mountainous counties (Tongcheng County and Xingshan County) and two plain counties (Liangzihu District and Xinzhou District) in Hubei Province. Among them, there were 43, 114, and 164 pregnant women in the early, middle, and late stages of pregnancy, respectively. Edible salt samples and once random urine samples were collected to detect salt iodine and urinary iodine, and thyroid ultrasound was performed to calculate the detection rate of thyroid nodules. Results:The coverage rate of iodized salt, qualified rate of iodized salt, and consumption rate of qualified iodized salt in Hubei Province were 99.69% (320/321), 95.94% (307/320) and 95.64% (307/321), respectively. The median urinary iodine level for pregnant women was 164.80 μg/L. Among them, the median urinary iodine levels in Liangzihu District, Tongcheng County, Xinzhou District, and Xingshan County were 175.90, 178.25, 155.80 and 143.00 μg/L, respectively. There was a statistically significant difference in urinary iodine levels among different regions ( H = 8.51, P = 0.037). The median urinary iodine levels of pregnant women in the early, middle, and late stages of pregnancy were 187.20, 144.45, and 172.05 μg/L, respectively. There was no statistically significant difference in urinary iodine levels among pregnant women in different stages of pregnancy ( H = 2.94, P = 0.230). Urinary iodine < 150, 150 - < 250, 250 - < 500, ≥500 μg/L accounted for 45.48% (146/321), 33.33% (107/321), 19.63% (63/321), 1.56% (5/321), respectively. The detection rate of thyroid nodules was 16.82% (54/321), and the goiter rate was 0.93% (3/321). Conclusions:In 2020, Hubei Province is in an appropriate state of iodine, and there are still a considerable proportion of pregnant women in a state of iodine deficiency. The detection rate of thyroid nodules is relatively low. It is necessary to continuously monitor the iodine nutrition of pregnant women, strengthen health promotion on the hazards of iodine deficiency during pregnancy, and minimize maternal and infant health damage caused by iodine deficiency.