Objective To analyze the epidemiological characteristics and risk factors of common viruses in children with respiratory tract infection in Yangling District, and to provide scientific basis for clinical formulation of effective prevention and control strategies. Methods The study subjects were 502 children with respiratory tract infection in Yangling Demonstration Zone Hospital from February 2022 to February 2024. 10 kinds of common respiratory infection viruses such as respiratory syncytial virus, parainfluenza virus, human rhinovirus, influenza B virus, influenza A virus, human adenovirus, enterovirus, coronavirus, human metapneumovirus and human Boca virus were detected by multiple real-time fluorescent polymerase chain reaction (PCR). According to the results of viral nucleic acid detection, 502 children were divided into positive detection group and negative detection group. Univariate and logistic multivariate regression analyses were adopted to analyze the risk factors of respiratory virus infection in children. Results Among the 502 children with respiratory tract infection, 112 cases were positive for viral nucleic acid detection, with a positive rate of 22.31%. Among the 95 cases were with single virus infection with a positive rate of 18.92%, mainly respiratory syncytial virus and parainfluenza virus, and 17 cases were with mixed virus infection, with the positive rate of 3.39%, mainly respiratory syncytial virus+parainfluenza virus mixed infection. After logistic multivariate analysis, it was found that age≤1 year old, onset in autumn and winter, monthly family income≤5000 yuan, concomitant congenital heart disease, maternal atopic disease history, maternal gestational diabetes mellitus, malnutrition and anemia were independent risk factors for respiratory virus infection in children (P<0.05). Conclusion Respiratory virus infection in acute hospitalized children in Yangling District is mainly a single virus, and is affected by many factors such as age of children, onset season, family monthly income and so on. Clinically, it is necessary to actively screen the above indicators of children and take active preventive measures to reduce viral infection.

Objective:To investigate the relationship between thyroid hormone sensitivity indicators and the risk of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM) who have normal thyroid function.Methods:A retrospective study design was used to gather data from 100 patients with T2DM who had normal thyroid function and were treated at Shangluo Central Hospital between June 2022 and January 2024. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used for evaluation. Patients with an MMSE score of ≤ 26 or a MoCA score of ≤ 26 were included in the MCI group ( n = 22), whereas those with an MMSE score of > 26 and a MoCA score of > 26 were included in the non-MCI group ( n = 78). Multivariate logistic regression analysis was performed to identify factors influencing MCI in patients with T2DM. Additionally, receiver operating characteristic curve analysis was conducted to assess the predictive value of thyroid hormone sensitivity indicators for MCI in this patient population. Results:In the MCI group, 68.18% of patients had an education level of high school or below. The level of glycosylated hemoglobin in this group was (8.45 ± 1.95)%, insulin resistance index was (3.34 ± 0.25), the level of triglycerides was (2.59 ± 0.19) mmol/L, the level of uric acid was (354.76 ± 46.16) μmol/L, thyroid-stimulating hormone index was (3.09 ± 0.26), and thyroid feedback quantile-based index was [0.2 (0.0, 0.5)]. All of these values were significantly higher than those in the non-MCI group: [43.59%, (7.63 ± 1.61)%, (3.05 ± 0.17), (2.09 ± 0.15) mmol/L, (311.74 ± 67.15) μmol/L, (2.87 ± 0.13), 0.2 (-0.1, 0.4), χ2 = 4.15, t = 2.01, 6.32, 12.99, 3.47, 5.47, Z = -2.54, all P < 0.05]. In the MCI group, the level of free triiodothyronine was (4.32 ± 0.21) pmol/L, and thyrotroph T4 resistance index (TT4RI) was (34.54 ± 4.30), both of which were significantly lower than those in the non-MCI group [(4.61 ± 0.36) pmol/L, (37.15 ± 5.55), t = 2.58, 2.04, both P < 0.05]. There were no significant differences in gender, age, body mass index, alcohol consumption, smoking, history of cerebral infarction, hypertension, duration of diabetes, use of only metformin, fasting blood glucose, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, alanine aminotransferase, aspartate aminotransferase, free thyroxine, and thyroid-stimulating hormone between the two groups (all P > 0.05). Logistic regression analysis indicated that education level, triglyceride, uric acid, free triiodothyronine, thyroid-stimulating hormone index, and TT4RI were risk factors for MCI (all P < 0.05). The predictive value of the combined thyroid hormone sensitivity indicators for MCI in patients with T2DM was high, with an area under the receiver operating characteristic curve of 0.778 [95% CI(0.676, 0.880), P < 0.001], a sensitivity of 0.538, a specificity of 0.909, and a maximum Youden index of 0.447. Conclusions:In patients with T2DM who have normal thyroid function, the thyroid hormone sensitivity indicators (TT4RI and thyroid feedback quantile-based index) exhibited a negative correlation with MCI, whereas TSHI demonstrated a positive correlation with MCI. The combined use of these thyroid hormone sensitivity indicators is valuable for predicting MCI and offers significant guidance for the early intervention of cognitive impairment in patients with T2DM.

Objective:To investigate the correlation between glycated hemoglobin (HbA1c) and 25-hydroxyvitamin D [25(OH)D] levels with peripheral vascular disease in patients with type 2 diabetes mellitus (T2DM).Methods:A total of 165 patients with T2DM who were treated at Shangluo Central Hospital from April 2021 to April 2023 were included in this retrospective study. Based on the presence or absence of peripheral vascular disease, the patients were divided into two groups: the positive group (115 patients with T2DM and peripheral vascular disease) and the negative group (50 patients with T2DM only). Data on general clinical characteristics including age, gender, duration of diabetes, family history of the disease, and the presence of hypertension were collected from both groups. Laboratory data, including 25(OH)D, serum calcium, phosphorus, apolipoprotein B, lipoprotein(a), uric acid, and apolipoprotein AⅠ, were also gathered. Logistic regression analysis was performed to identify high-risk factors for peripheral vascular disease, while Pearson or Spearman correlation analyses were used to evaluate the correlation between HbA1c, 25(OH)D, and peripheral vascular disease. The diagnostic efficiency of the high-risk factors for peripheral vascular disease was assessed using receiver operating characteristic analysis.Results:Long disease duration ( t = 2.74, P = 0.007), a history of hypertension ( χ2 = 6.60, P = 0.010), poor control of HbA1c ( χ2 = 12.14, P < 0.001), vitamin D deficiency ( χ2 = 10.20, P < 0.001), high levels of low-density lipoprotein cholesterol ( t = 2.58, P = 0.024), low levels of high-density lipoprotein cholesterol ( t = 3.65, P = 0.008), high HbA1c levels ( t = 6.68, P < 0.001), and low levels of 25(OH)D ( t = 6.60, P < 0.001) are the independent risk factors for peripheral vascular disease in patients with T2DM. Logistic regression analysis revealed that long disease duration ( OR = 2.327, P = 0.008), vitamin D deficiency ( OR = 1.255, P = 0.034), high HbA1c levels ( OR = 3.124, P < 0.001), and low 25(OH)D levels ( OR = 4.256, P = 0.002) are significant risk factors for peripheral vascular disease. Pearson correlation analysis indicated a negative correlation between HbA1c levels and 25(OH)D levels ( r = -0.810, P < 0.001). Spearman correlation analysis showed a positive correlation between HbA1c levels and peripheral vascular disease ( r = 0.472, P < 0.001), while 25(OH)D levels were negatively correlated with peripheral vascular disease ( r = -0.443, P < 0.001). Receiver operating characteristic curve analysis revealed that the area under the curve (AUC) for HbA1c predicting peripheral vascular disease was 0.797 (95% CI: 0.719, 0.874), with a sensitivity of 0.817 and specificity of 0.760 at a cutoff value of 8.27%. The AUC for 25(OH)D predicting peripheral vascular disease was 0.778 (95% CI: 0.695, 0.861), with a sensitivity of 0.748 and specificity of 0.780 at a cutoff value of 63.49 nmol/L. The prediction of peripheral vascular disease using both HbA1c and 25(OH)D yielded an AUC of 0.805 (95% CI: 0.730, 0.876), with a sensitivity of 0.815 and specificity of 0.800. Conclusions:The duration of the disease, HbA1c levels, and 25(OH)D levels are high risk factors for peripheral vascular disease in patients with T2DM. When patients with T2DM exhibit vitamin D deficiency and poor control of HbA1c levels, prompt intervention should be implemented to reduce the risk of developing peripheral vascular disease.

Objective:To investigate the relationship between thyroid hormone sensitivity indicators and the risk of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM) who have normal thyroid function.Methods:A retrospective study design was used to gather data from 100 patients with T2DM who had normal thyroid function and were treated at Shangluo Central Hospital between June 2022 and January 2024. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used for evaluation. Patients with an MMSE score of ≤ 26 or a MoCA score of ≤ 26 were included in the MCI group ( n = 22), whereas those with an MMSE score of > 26 and a MoCA score of > 26 were included in the non-MCI group ( n = 78). Multivariate logistic regression analysis was performed to identify factors influencing MCI in patients with T2DM. Additionally, receiver operating characteristic curve analysis was conducted to assess the predictive value of thyroid hormone sensitivity indicators for MCI in this patient population. Results:In the MCI group, 68.18% of patients had an education level of high school or below. The level of glycosylated hemoglobin in this group was (8.45 ± 1.95)%, insulin resistance index was (3.34 ± 0.25), the level of triglycerides was (2.59 ± 0.19) mmol/L, the level of uric acid was (354.76 ± 46.16) μmol/L, thyroid-stimulating hormone index was (3.09 ± 0.26), and thyroid feedback quantile-based index was [0.2 (0.0, 0.5)]. All of these values were significantly higher than those in the non-MCI group: [43.59%, (7.63 ± 1.61)%, (3.05 ± 0.17), (2.09 ± 0.15) mmol/L, (311.74 ± 67.15) μmol/L, (2.87 ± 0.13), 0.2 (-0.1, 0.4), χ2 = 4.15, t = 2.01, 6.32, 12.99, 3.47, 5.47, Z = -2.54, all P < 0.05]. In the MCI group, the level of free triiodothyronine was (4.32 ± 0.21) pmol/L, and thyrotroph T4 resistance index (TT4RI) was (34.54 ± 4.30), both of which were significantly lower than those in the non-MCI group [(4.61 ± 0.36) pmol/L, (37.15 ± 5.55), t = 2.58, 2.04, both P < 0.05]. There were no significant differences in gender, age, body mass index, alcohol consumption, smoking, history of cerebral infarction, hypertension, duration of diabetes, use of only metformin, fasting blood glucose, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, alanine aminotransferase, aspartate aminotransferase, free thyroxine, and thyroid-stimulating hormone between the two groups (all P > 0.05). Logistic regression analysis indicated that education level, triglyceride, uric acid, free triiodothyronine, thyroid-stimulating hormone index, and TT4RI were risk factors for MCI (all P < 0.05). The predictive value of the combined thyroid hormone sensitivity indicators for MCI in patients with T2DM was high, with an area under the receiver operating characteristic curve of 0.778 [95% CI(0.676, 0.880), P < 0.001], a sensitivity of 0.538, a specificity of 0.909, and a maximum Youden index of 0.447. Conclusions:In patients with T2DM who have normal thyroid function, the thyroid hormone sensitivity indicators (TT4RI and thyroid feedback quantile-based index) exhibited a negative correlation with MCI, whereas TSHI demonstrated a positive correlation with MCI. The combined use of these thyroid hormone sensitivity indicators is valuable for predicting MCI and offers significant guidance for the early intervention of cognitive impairment in patients with T2DM.

Objective:To investigate the correlation between glycated hemoglobin (HbA1c) and 25-hydroxyvitamin D [25(OH)D] levels with peripheral vascular disease in patients with type 2 diabetes mellitus (T2DM).Methods:A total of 165 patients with T2DM who were treated at Shangluo Central Hospital from April 2021 to April 2023 were included in this retrospective study. Based on the presence or absence of peripheral vascular disease, the patients were divided into two groups: the positive group (115 patients with T2DM and peripheral vascular disease) and the negative group (50 patients with T2DM only). Data on general clinical characteristics including age, gender, duration of diabetes, family history of the disease, and the presence of hypertension were collected from both groups. Laboratory data, including 25(OH)D, serum calcium, phosphorus, apolipoprotein B, lipoprotein(a), uric acid, and apolipoprotein AⅠ, were also gathered. Logistic regression analysis was performed to identify high-risk factors for peripheral vascular disease, while Pearson or Spearman correlation analyses were used to evaluate the correlation between HbA1c, 25(OH)D, and peripheral vascular disease. The diagnostic efficiency of the high-risk factors for peripheral vascular disease was assessed using receiver operating characteristic analysis.Results:Long disease duration ( t = 2.74, P = 0.007), a history of hypertension ( χ2 = 6.60, P = 0.010), poor control of HbA1c ( χ2 = 12.14, P < 0.001), vitamin D deficiency ( χ2 = 10.20, P < 0.001), high levels of low-density lipoprotein cholesterol ( t = 2.58, P = 0.024), low levels of high-density lipoprotein cholesterol ( t = 3.65, P = 0.008), high HbA1c levels ( t = 6.68, P < 0.001), and low levels of 25(OH)D ( t = 6.60, P < 0.001) are the independent risk factors for peripheral vascular disease in patients with T2DM. Logistic regression analysis revealed that long disease duration ( OR = 2.327, P = 0.008), vitamin D deficiency ( OR = 1.255, P = 0.034), high HbA1c levels ( OR = 3.124, P < 0.001), and low 25(OH)D levels ( OR = 4.256, P = 0.002) are significant risk factors for peripheral vascular disease. Pearson correlation analysis indicated a negative correlation between HbA1c levels and 25(OH)D levels ( r = -0.810, P < 0.001). Spearman correlation analysis showed a positive correlation between HbA1c levels and peripheral vascular disease ( r = 0.472, P < 0.001), while 25(OH)D levels were negatively correlated with peripheral vascular disease ( r = -0.443, P < 0.001). Receiver operating characteristic curve analysis revealed that the area under the curve (AUC) for HbA1c predicting peripheral vascular disease was 0.797 (95% CI: 0.719, 0.874), with a sensitivity of 0.817 and specificity of 0.760 at a cutoff value of 8.27%. The AUC for 25(OH)D predicting peripheral vascular disease was 0.778 (95% CI: 0.695, 0.861), with a sensitivity of 0.748 and specificity of 0.780 at a cutoff value of 63.49 nmol/L. The prediction of peripheral vascular disease using both HbA1c and 25(OH)D yielded an AUC of 0.805 (95% CI: 0.730, 0.876), with a sensitivity of 0.815 and specificity of 0.800. Conclusions:The duration of the disease, HbA1c levels, and 25(OH)D levels are high risk factors for peripheral vascular disease in patients with T2DM. When patients with T2DM exhibit vitamin D deficiency and poor control of HbA1c levels, prompt intervention should be implemented to reduce the risk of developing peripheral vascular disease.

Colorectal cancer （CRC） is a malignant tumor of the intestinal tract with changes in bowel habits， blood in the stool， and pain as the main clinical manifestations. With the change in lifestyle and diet structure in recent years， the incidence of CRC has been increasing year by year. The pathogenesis of CRC is closely related to abnormal immune response and chronic inflammation， intestinal microbial dysbiosis， and the production of oncogenic metabolites. There is a two-way communication between the intestinal microbiota and the body's immunity， which not only plays a key role in maintaining the body's health but also has a close relationship with the development of diseases. An increasing number of studies have shown that abnormal immune responses accelerate the disease process by producing inflammatory factors， causing chronic inflammation in the body， disrupting the intestinal mucosal barrier， and increasing mucosal permeability， thus resulting in dysbiosis of the intestinal microbial ecology and a large number of pathogenic microorganisms and their metabolites. In addition， dysbiosis of intestinal microbes， by suppressing the normal immune response， leads to the disruption of multiple metabolic pathways in the body， affecting the internal and external stress response of the intestine， inducing inflammation， and thus producing disease. Therefore， the complex crosstalk mechanism between the immune response and intestinal microbial axis is closely related to the development of CRC. Based on traditional Chinese medicine theory and clinical research， it was found that dietary factors are an important causative factor in the development of CRC. The deficiency of positive energy is the root cause of the disease， and damp-heat accumulation is the key pathogenesis. Through modern medical and biological research， it is believed that abnormal immune response is the microscopic manifestation of damp-heat entrapment， while intestinal microbial dysbiosis is the biological basis of toxic injection into the large intestine， and in the pathogenesis of CRC， the imbalance of immune response-intestinal microbial axis is compatible with damp-heat accumulation in traditional Chinese medicine. This study aims to explore the biological connotation of CRC due to damp-heat accumulation from the immune response-intestinal microbial axis， so as to interpret the pathogenesis of CRC due to damp-heat accumulation with objective data and provide new ideas and theoretical basis for the pathogenesis and treatment strategies of CRC due to damp-heat accumulation.

Objective:To explore the predictive value of peripheral blood neutrophil to lymphocyte ratio (NLR) and serum trimethylamine oxide (TMAO) on in-hospital mortality events in patients with acute myocardial infarction complicated by cardiogenic shock (AMICS) upon admission.Methods:A retrospective collection of medical records of 103 AMICS patients admitted to the Shanxi Yingkang Life General Hospital from January 2018 to June 2023 was conducted. The patients were divided into a survival group ( n=78) and a death group ( n=25) based on whether they experienced in-hospital mortality events. Two groups of peripheral blood NLR, serum TMAO, baseline data, and other laboratory indicators were compared. A logistic regression model was used to analyze the risk factors for in-hospital mortality in AMICS patients and a prediction model was constructed. We established receiver operating characteristic (ROC) curves to evaluate the predictive efficacy of peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and predictive model indicators for in-hospital mortality events in AMICS patients. Results:The peripheral blood NLR and serum TMAO levels in the death group were significantly higher than those in the survival group (all P<0.05). The age of the death group was higher than that of the survival group, and the proportion of hypertension, alanine aminotransferase, creatinine, random blood glucose, proportion of patients who did not receive emergency percutaneous coronary intervention (PCI) treatment, peak cardiac troponin I, B-type natriuretic peptide, Gensini score of coronary artery disease, and C-reactive protein were all higher than those of the survival group. Systolic blood pressure and platelet count were lower than those of the survival group, heart rate and erythrocyte sedimentation rate were faster than those of the survival group, and the pre hospital time was longer than that of the survival group. The differences were statistically significant (all P<0.05). The results of binary logistic regression analysis showed that after adjusting for confounding factors such as age, male proportion, body mass index, proportion of old myocardial infarction, proportion of hypertension, and proportion of PCI history, advanced age, long pre hospital time, failure to receive emergency PCI, elevated peripheral blood NLR, and elevated serum TMAO were independent risk factors for in-hospital mortality in AMICS patients ( P<0.05). The predictive model was obtained as 0.734×age+ 0.277×pre hospital time+ 2.263×failure to receive emergency PCI+ 0.549×peripheral blood NLR+ 0.608×serum TMAO-26.923. The ROC curve results showed that the area under the curve (AUC) values of peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and predictive model indicators for predicting in-hospital mortality events in AMICS patients were 0.744, 0.781, 0.825, and 0.921, respectively. When the optimal cutoff value was taken, the sensitivities were 0.880, 0.520, 0.680, and 0.880, and the specificities were 0.526, 0.923, 0.872, and 0.821, respectively. Conclusions:Advanced age, long pre hospital duration, failure to undergo emergency PCI, elevated peripheral blood NLR, and elevated serum TMAO are independent risk factors for in-hospital mortality in AMICS patients. Peripheral blood NLR, serum TMAO, peripheral blood NLR+ serum TMAO, and prediction models all have certain predictive value for in-hospital mortality events in AMICS patients. Among them, the sensitivity and specificity of the prediction models are high, and the efficacy is good.

Objective:To construct a diabetic foot classification prediction model based on radiomics features of fundus photographs.Methods:A total of 2 035 fundus photographs of patients with type 2 diabetes diagnosed at Nanfang Hospital between December 2011 and December 2018 were retrospectively collected [282 photographs from patients with diabetic foot(DF), and 1 753 from patients with diabetes mellitus(DM)]. All fundus photographs were randomly divided into a training set(1 424 photos) and a test set(611 photos) using a computer generated random number at 7∶3. After pre-processing the fundus photographs, a total of 4 128 texture features based on the gray matrix were extracted by the Radiomic toolkit, and 11 339 other features were extracted using the ToolboxDESC toolkit. The LASSO algorithm was used to select the 30 features most relevant to DF, and then the Bootstrap + 0.632 self-sampling method was used to further select the 7 best combinations. Logistic regression analysis was used to obtain the regression coefficients and establish the final diabetic foot classification prediction model. ROC curve was drawn, and AUC, sensitivity, specificity, and accuracy of the training and test sets were calculated to verify its prediction performance. Results:We screened 7 fundus radiomics markers for diabetic foot patients, and based on this established a DF/DM classification prediction model. The AUC, sensitivity, specificity, and accuracy of the model were 0.958 6, 0.984 0, 0.920 0, and 0.928 0 in the training set, and 0.927 1, 0.988 9, 0.881 0, and 0.896 9 in the test set, respectively.Conclusion:In this study, seven DF fundus markers were screened using radiomics technology. Based on this, a highly accurate and easy-to-use DF/DM classification model was constructed. This technology has the potential to increase the efficiency of DF screening programs.

Objective:To investigate the clinical outcomes of using the levofloxacin combined with intrauterine infusion of metronidazole for the treatment of the infertility patients with chronic endometritis (CE).Methods:Using a case-control study method. 82 infertility patients with CE admitted to Xuzhou Central Hospital from March 2018 to March 2021 were selected and randomly divided into an observation group and a control group using a random number table method, with 41 cases in each group. The control group was treated with oral levofloxacin hydrochloride, while the observation group was treated with metronidazole sodium chloride injection intrauterine infusion on the basis of the control group. Both groups were treated for 14 days. Compare the serum C-reactive protein (CRP) and tumor necrosis factor between two groups before and after treatment α(tumor necrosis factor-α, TNF-α) The levels of monocyte chemotactic protein 1 (MCP-1), natural pregnancy rate within six months, total effective rate, and incidence of adverse reactions during treatment were measured. The measurement data with normal distribution is expressed as: independent sample t-test is used for comparison between the two groups, and paired t-test is used for comparison before and after treatment within the group; The measurement data of non normal distribution is represented by M( Q1, Q3), and the comparison between groups is made by Wilcoxon Rank sum test. The counting data is represented by examples (%), and the comparison between groups is conducted using the χ 2 test. Results:Before treatment, two groups of serum CRP and TNF-α There was no statistically significant difference compared to the levels of MCP-1 (all P>0.05); After 14 days of treatment, both groups had serum CRP and TNF-α、MCP-1 were all lower than before treatment, and the observation group was lower than the control group [(4.12±1.9) ng/L vs (6.36±1.63) ng/L, (47.28±9.10) ng/L vs (62.79±9.34) ng/L, (212.04±24.82) ng/L vs (326.15±27.38) ng/L], with statistically significant differences ( t-values of 5.61, 7.62, and 19.77, all P<0.001). After 14 days of treatment, the total effective rate of the observation group was higher than that of the control group [95.12% (39/41) vs 78.05% (32/41)], with a statistically significant difference (χ 2=5.14, P=0.023). After 6 months of treatment, the natural pregnancy rate in the observation group was higher than that in the control group [53.66% (22/41) vs 31.71% (13/41)], with a statistically significant difference (χ 2=5.96, P=0.044). There was no statistically significant difference in the incidence of adverse reactions between the two groups during the treatment period (χ 2=0.55, P=0.457). Conclusions:The combination of levofloxacin and intrauterine infusion of metronidazole has a good clinical effect in treating infertility patients with CE. It can significantly improve the inflammatory state of the body, reduce serum inflammatory factor levels, increase the natural pregnancy rate within 6 months, and do not increase the incidence of adverse reactions.

Objective:To explore the different metabolites in the follicular fluids (FFs) of polycystic ovary syndrome (PCOS) patients and non-PCOS patients and their effects on the maturation of mouse oocytes and the developmental potential of in vitro fertilization (IVF) embryos. Methods:The clinical data were collected for the retrospective cohort study. Animal experiments were conducted in a randomized controlled trial. This study included PCOS ( n=71) and non-PCOS ( n=70) patients who underwent the first IVF or intracytoplasmic sperm injection (ICSI) cycle in Shanghai JIAI Genetics & IVF institute from June 2019 to June 2020. The patients' FFs were collected and the clinical data from these patients were analyzed. Raman spectroscopy analysis technology was used to detect differences in the metabolic spectra of FFs between the two groups. Mouse GV phase oocytes were placed in FFs from PCOS patients and non-PCOS patients for in vitro maturation (IVM) culture respectively, then the matured mouse oocytes were collected for IVF. The effects of differential metabolites in FFs on mouse oocyte maturation and embryonic development were further explored. The Raman spectrum was also applied to identify the differences of the IVM spent culture media. Results:The MⅡ rate [82.19% (886/1 078)] and day 3 available embryo rate [51.30% (553/1 078)] from PCOS group were significantly lower than those of the non-PCOS group [85.85% (625/728), P=0.038; 53.30% (388/728), P=0.042]. However, there were no significant differences between the two groups in the cumulative clinical pregnancy rate and the cumulative live birth rate (all P>0.05). Raman was capable of distinguishing PCOS from non-PCOS FFs. The characteristic Raman displacement difference between the two groups is mainly concentrated in the 600-1 000 cm -1, as well as 1 168 cm -1, 1 344 cm -1, 1 440 cm -1, 1 504 cm -1, 1 632 cm -1 and 1 664 cm -1. The Raman characteristic shift database showed that the different metabolites of the two sets of FFs samples were mainly concentrated in protein, lipids, free nucleic acis, glucose, cholesterol, carotenoids, and amino acids. Mouse oocyte IVM results showed that the PCOS-FF group had a lower MⅡ rate [49.04% (77/157)] than that of non-PCOS group [65.07% (95/146), P=0.005). IVF results showed the PCOS-FF group had a significantly lower cleavage rate [46.75% (36/77)] than that of non-PCOS group [63.16% (60/95), P=0.031], but there was no significant difference in the blastocyst rate between the two groups ( P>0.05). Conclusion:Differential metabolites detected by Raman spectrum in the PCOS FFs may cause defected maturation of the oocytes, leading to infertility, and Raman spectroscopy is an effective approach towards PCOS diagnosis and the identification of metabolomics differences.