The coupling coordination between health service supply and regional economy in China: spatio-temporal evolution and convergence.

Background: The coordination of health service supply and regional economy is an integral path to promote China's prosperity. Methods: Based on the coupling mechanism of health service supply and regional economy, we sampled the data from 30 provinces in China from 2009 to 2021 in this study and constructed the evaluation index system. Additionally, we calculated the coupling coordination degree (HED) of the two through the coupling coordination degree model. We further used the kernel density estimation, Moran's I index, and spatial ß convergence model to assess the dynamic evolution trends, spatial aggregation effect, and spatial convergence characteristics of coupling coordination. Conclusion: (1) HED in China showed a rising trend during the study period but with large regional differences, forming a gradient distribution pattern of "high in the east and low in the west." (2) The results of Kernel density estimation show that HED has formed a gradient differentiation phenomenon within each region in China. (3) HED has modeled spatial clustering characteristics during the study period, with high-value clusters mainly appearing in the eastern region and low-value clusters appearing in the northwestern region. (4) There are absolute ß-convergence and conditional ß-convergence trends in HED in China and the three major regions during the study period, but there is an obvious regional heterogeneity in the control factors. The research provides a reference for accurately implementing policies according to different levels of health service supply and economic development, in addition to narrowing the regional differences of the coupling coordination between the regional economy and health service supply.

Influence of intergenerational support on the mental health of older people in China.

Today, population aging is the main trend of population development. Home-based care is mainly adopted in Chinese society, and scholars have paid ample attention to the effect of intergenerational support on the mental health of older people. However, research conclusions differ. This study uses data from the 2018 China Health and Pension Tracking Survey (CHARLS), which we analyzed with STATA software to construct least squares regression and two-stage least squares regression models. The regression model included 6,647 respondents to investigate the mental health status of older people based on depression status. Intergenerational support was defined as economic support, emotional support, and daily care provided by the children of older people. We studied the impact of three aspects of intergenerational support on the mental health of the elderly. We performed a robustness test using the variable replacement and propensity score matching methods, and analyzed age, gender, and urban-rural heterogeneity. The results showed that economic support had no significant impact on the mental health of older people, while emotional support and daily care had a positive effect. The heterogeneity results indicated that the relationship between intergenerational support and mental health of older people differed significantly based on age, gender, and urban and rural areas. Therefore, children should raise their awareness of supporting their parents, pay attention to their parents' mental health, and provide emotional support and daily care. Furthermore, community work improves family relations, creates a good social environment, and encourages young people to respect and be filial to older people. The government should improve the medical security system and old-age service system, and provide policy support to help the mental health of older people.

Performance and Solution Structures of Side-Chain-Bridged Oligo (Ethylene Glycol) Polymer Photocatalysts for Enhanced Hydrogen Evolution under Natural Light Illumination.

Converting solar energy into hydrogen energy using conjugated polymers (CP) is a promising solution to the energy crisis. Improving water solubility plays one of the critical factors in enhancing the hydrogen evolution rate (HER) of CP photocatalysts. In this study, a novel concept of incorporating hydrophilic side chains to connect the backbones of CPs to improve their HER is proposed. This concept is realized through the polymerization of carbazole units bridged with octane, ethylene glycol, and penta-(ethylene glycol) to form three new side-chain-braided (SCB) CPs: PCz2S-OCt, PCz2S-EG, and PCz2S-PEG. Verified through transient absorption spectra, the enhanced capability of PCz2S-PEG for ultrafast electron transfer and reduced recombination effects has been demonstrated. Small- and wide-angle X-ray scattering (SAXS/WAXS) analyses reveal that these three SCB-CPs form cross-linking networks with different mass fractal dimensions (f) in aqueous solution. With the lowest f value of 2.64 and improved water/polymer interfaces, PCz2S-PEG demonstrates the best HER, reaching up to 126.9 µmol h-1 in pure water-based photocatalytic solution. Moreover, PCz2S-PEG exhibits comparable performance in seawater-based photocatalytic solution under natural sunlight. In situ SAXS analysis further reveals nucleation-dominated generation of hydrogen nanoclusters with a size of ≈1.5 nm in the HER of PCz2S-PEG under light illumination.

Short-Term Peg-IFN α-2b Re-Treatment Induced a High Functional Cure Rate in Patients with HBsAg Recurrence after Stopping Peg-IFN α-Based Regimens.

Little is known about the treatment of patients with hepatitis B surface antigen (HBsAg) recurrence after being clinically cured by peginterferon alpha(peg-IFN-α)-based regimens. This study aimed to investigate the efficacy and safety of peg-IFNα-2b in re-treating patients with HBsAg recurrence after stopping peg-IFN α-based regimens. In this two-center, prospective observational study, 33 patients with HBsAg recurrence after stopping peg-IFN α-based regimens were enrolled and re-treated with an individualized course of peg-IFN α-2b. The hepatitis B virus (HBV) vaccine could be injected immediately after HBsAg clearance, according to patients' willingness. All patients were monitored and followed-up for 48 weeks after peg-IFN α-2b re-treatment stop. The primary endpoint was HBsAg clearance at the end of follow-up. At baseline, all patients had HBsAg levels of <10 IU/mL and undetectable HBV DNA, with the median HBsAg level of 1.66 (0.56−2.87) IU/mL. After a median of 24 (24−30) weeks of peg-IFN α-2b re-treatment, 87.9% (29/33) of the patients achieved HBsAg clearance again and 66.7% (22/33) of the patients achieved HBsAg seroconversion. At the end of follow-up, the HBsAg clearance and HBsAg seroconversion rates decreased to 78.8% (26/33) and 51.5% (17/33), respectively. Furthermore, 88.9% (16/18) of the patients with HBsAg clearance benefited from receiving the HBV vaccine therapy. Generally, both peg-IFN α-2b and HBV vaccine therapy were well tolerated. A high functional cure rate can be achieved by a short-course of peg-IFN α-2b re-treatment in patients with HBsAg recurrence after stopping peg-IFN α-based regimens. Furthermore, injecting HBV vaccine is beneficial after HBsAg clearance.

Development and validation of a machine learning-based model for varices screening in compensated cirrhosis (CHESS2001): an international multicenter study.

BACKGROUND AND AIMS: The prevalence of high-risk varices (HRV) is low among compensated cirrhotic patients undergoing EGD. Our study aimed to identify a novel machine learning (ML)-based model, named ML EGD, for ruling out HRV and avoiding unnecessary EGDs in patients with compensated cirrhosis. METHODS: An international cohort from 17 institutions from China, Singapore, and India were enrolled (CHESS2001). The variables with the top 3 importance scores (liver stiffness, platelet count, and total bilirubin) were selected by the Shapley additive explanation and input into a light gradient-boosting machine algorithm to develop ML EGD for identification of HRV. Furthermore, we built a web-based calculator for ML EGD, which is free with open access (http://www.pan-chess.cn/calculator/MLEGD_score). Unnecessary EGDs that were not performed and the rates of missed HRV were used to assess the efficacy and safety for varices screening. RESULTS: Of 2794 enrolled patients, 1283 patients formed a real-world cohort from 1 university hospital in China used to develop and internally validate the performance of ML EGD for varices screening. They were randomly assigned into the training (n = 1154) and validation (n = 129) cohorts with a ratio of 9:1. In the training cohort, ML EGD spared 607 (52.6%) unnecessary EGDs with a missed HRV rate of 3.6%. In the validation cohort, ML EGD spared 75 (58.1%) EGDs with a missed HRV rate of 1.4%. To externally test the performance of ML EGD, 966 patients from 14 university hospitals in China (test cohort 1) and 545 from 2 hospitals in Singapore and India (test cohort 2) comprised the 2 test cohorts. In test cohort 1, ML EGD spared 506 (52.4%) EGDs with a missed HRV rate of 2.8%. In test cohort 2, ML EGD spared 224 (41.1%) EGDs with a missed HRV rate of 3.1%. When compared with the Baveno VI criteria, ML EGD spared more screening EGDs in all cohorts (training cohort, 52.6% vs 29.4%; validation cohort, 58.1% vs 44.2%; test cohort 1, 52.4% vs 26.5%; test cohort 2, 41.1% vs 21.1%, respectively; P < .001). CONCLUSIONS: We identified a novel model based on liver stiffness, platelet count, and total bilirubin, named ML EGD, as a free web-based calculator. ML EGD could efficiently help rule out HRV and avoid unnecessary EGDs in patients with compensated cirrhosis. (Clinical trial registration number: NCT04307264.).

A Review on Enhancing Cupriavidus necator Fermentation for Poly(3-hydroxybutyrate) (PHB) Production From Low-Cost Carbon Sources.

In the context of a circular economy, bioplastic production using biodegradable materials such as poly(3-hydroxybutyrate) (PHB) has been proposed as a promising solution to fundamentally solve the disposal issue of plastic waste. PHB production techniques through fermentation of PHB-accumulating microbes such as Cupriavidus necator have been revolutionized over the past several years with the development of new strategies such as metabolic engineering. This review comprehensively summarizes the latest PHB production technologies via Cupriavidus necator fermentation. The mechanism of the biosynthesis pathway for PHB production was first assessed. PHB production efficiencies of common carbon sources, including food waste, lignocellulosic materials, glycerol, and carbon dioxide, were then summarized and critically analyzed. The key findings in enhancing strategies for PHB production in recent years, including pre-treatment methods, nutrient limitations, feeding optimization strategies, and metabolism engineering strategies, were summarized. Furthermore, technical challenges and future prospects of strategies for enhanced production efficiencies of PHB were also highlighted. Based on the overview of the current enhancing technologies, more pilot-scale and larger-scale tests are essential for future implementation of enhancing strategies in full-scale biogas plants. Critical analyses of various enhancing strategies would facilitate the establishment of more sustainable microbial fermentation systems for better waste management and greater efficiency of PHB production.

Deep Learning-Based Automatic CT Quantification of Coronavirus Disease 2019 Pneumonia: An International Collaborative Study.

OBJECTIVE: We aimed to develop and validate the automatic quantification of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) images. METHODS: This retrospective study included 176 chest CT scans of 131 COVID-19 patients from 14 Korean and Chinese institutions from January 23 to March 15, 2020. Two experienced radiologists semiautomatically drew pneumonia masks on CT images to develop the 2D U-Net for segmenting pneumonia. External validation was performed using Japanese (n = 101), Italian (n = 99), Radiopaedia (n = 9), and Chinese data sets (n = 10). The primary measures for the system's performance were correlation coefficients for extent (%) and weight (g) of pneumonia in comparison with visual CT scores or human-derived segmentation. Multivariable logistic regression analyses were performed to evaluate the association of the extent and weight with symptoms in the Japanese data set and composite outcome (respiratory failure and death) in the Spanish data set (n = 115). RESULTS: In the internal test data set, the intraclass correlation coefficients between U-Net outputs and references for the extent and weight were 0.990 and 0.993. In the Japanese data set, the Pearson correlation coefficients between U-Net outputs and visual CT scores were 0.908 and 0.899. In the other external data sets, intraclass correlation coefficients were between 0.949-0.965 (extent) and between 0.978-0.993 (weight). Extent and weight in the top quartile were independently associated with symptoms (odds ratio, 5.523 and 10.561; P = 0.041 and 0.016) and the composite outcome (odds ratio, 9.365 and 7.085; P = 0.021 and P = 0.035). CONCLUSIONS: Automatically quantified CT extent and weight of COVID-19 pneumonia were well correlated with human-derived references and independently associated with symptoms and prognosis in multinational external data sets.

Caffeine-induced neurotoxicity mediated by Nrf2 pathway in PC12 cells and zebrafish larvae.

Caffeine is one of the most widely used psychostimulants in the world and possesses central excitative, anti-depressive, and neuroprotective properties. However, excessive ingestion or abuse of caffeine can lead to intoxication. Many toxic effects are attributed to oxidative damage, and nuclear factor erythroid 2-related factor 2 (Nrf2) is a critical intracellular regulator of the oxidative stress response. Here, we investigated the neurotoxicity of caffeine in rat pheochromocytoma PC12 cells and zebrafish larvae. It was found that caffeine inhibited the viability of PC12 cells in a dose- and time-dependent manner. Furthermore, it induced PC12 cell apoptosis and elevated reactive oxygen species (ROS) production. Quantitative polymerase chain reaction (qPCR) and western blotting revealed that caffeine also inhibited the expression levels of Nrf2 mRNA and protein and its target genes (e.g., NADPH quinone oxidoreductase 1 [NQO1]). Furthermore, Nrf2 silencing attenuated the toxic effects of caffeine. In addition, zebrafish larvae were treated with different doses of caffeine. Behavioral experiments showed that a low dose of caffeine (0.05 to 0.3 mM) increased the average distance of movement and promoted excitation. Survivorship curves showed that caffeine (0.2 to 1.5 mM) caused lethality. Finally, qPCR revealed that a higher dose of caffeine inhibited mRNA levels in the Nrf2 pathway. Based on these results, this study identified for the first time that overuse of caffeine can induce neurotoxicity by inhibiting the Nrf2 pathway. These results will provide a new perspective for studies on caffeine toxicity.

Coronavirus Disease 2019: Hysteresis Effect of Chest CT and the Correlation with its Severity.

PURPOSE: The purpose of this study was to investigate the influencing factors for chest CT hysteresis and severity of coronavirus disease 2019 (COVID-19). METHODS: The chest CT data of patients with confirmed COVID-19 in 4 hospitals were retrospectively analyzed. An independent assessment was performed by one clinician using the DEXIN FACT Workstation Analysis System, and the assessment results were reviewed by another clinician. Furthermore, the mean hysteresis time was calculated according to the median time from progression to the most serious situation to improve chest CT in patients after fever relief. The optimal scaling regression analysis was performed by including variables with statistical significance in univariate analysis. In addition, a multivariate regression model was established to investigate the relationship of the percentage of lesion/total lung volume with lymphocyte and other variables. RESULTS: In the included 166 patients with COVID-19, the average value of the most serious percentage of lesion/total lung volume was 6.62, of which 90 patients with fever had an average hysteresis time of 4.5 days after symptom relief, with a similar trend observed in those without fever. Multivariate analysis revealed that lymphocyte count in peripheral blood and transcutaneous oxygen saturation decreased with the increase of the percentage of lesion/total lung volume. CONCLUSION: There is a hysteresis effect in the improvement of chest CT image relative to fever relief in patients with COVID-19. The pulmonary lesions may be related to the severity as well as decreased lymphocyte count or percutaneous oxygen saturation.

Platelet count/spleen volume ratio has a good predictive value for esophageal varices in patients with hepatitis B liver cirrhosis.

BACKGROUND & AIMS: Platelet count/spleen longest diameter ratio (PSDR) is widely used in clinical practice due to its good performance in predicting esophageal varices (EV). We obtained spleen volume (SV) by magnetic resonance examination, the purpose of this study was to evaluate the clinical value of platelet count/spleen volume ratio (PSVR) and spleen volume in predicting EV in patients with hepatitis B cirrhosis. Methods: This study was a diagnostic accuracy experiment and retrospective, 199 patients with hepatitis B cirrhosis who met the criteria were selected as the research subjects. All patients were collected blood samples in the morning on an empty stomach within 2 days, and related indicators were tested. Within 10 days, they received electronic gastroscopy and abdominal magnetic resonance examination. According to the Child-Pugh score, the patients were divided into groups with or without EV and with or without high-risk esophageal varices (HRV), then statistical analysis of the two groups was performed. RESULTS: The area under the curve (AUC) of PSVR in predicting EV or HRV in each group (85.5%-92.6%) was higher than PSDR, SV, spleen diameter, and platelet count. The AUC of PSDR in diagnosing HRV was higher than SV, and the AUC of SV in diagnosing EV was higher than PSDR, but the difference was not significant (P>0.05). In Child-Pugh A patients, Multivariate logistic regression analysis showed PSVR could be a predictor of HRV (P<0.05), SV was a reliable predictor of EV (P<0.05). CONCLUSION: PSVR is better than PSDR, spleen diameter, platelet count in predicting EV; in the absence of serological results, SV could be used instead of PSDR. Both can predict EV or HRV of patients with hepatitis B cirrhosis.

CANPT Score: A Tool to Predict Severe COVID-19 on Admission.

Background and Aims: Patients with critical coronavirus disease 2019 (COVID-19) have a mortality rate higher than 50%. The purpose of this study was to establish a model for the prediction of the risk of severe disease and/or death in patients with COVID-19 on admission. Materials and Methods: Patients diagnosed with COVID-19 in four hospitals in China from January 22, 2020 to April 15, 2020 were retrospectively enrolled. The demographic, laboratory, and clinical data of the patients with COVID-19 were collected. The independent risk factors related to the severity of and death due to COVID-19 were identified with a multivariate logistic regression; a nomogram and prediction model were established. The area under the receiver operating characteristic curve (AUROC) and predictive accuracy were used to evaluate the model's effectiveness. Results: In total, 582 patients with COVID-19, including 116 patients with severe disease, were enrolled. Their comorbidities, body temperature, neutrophil-to-lymphocyte ratio (NLR), platelet (PLT) count, and levels of total bilirubin (Tbil), creatinine (Cr), creatine kinase (CK), and albumin (Alb) were independent risk factors for severe disease. A nomogram was generated based on these eight variables with a predictive accuracy of 85.9% and an AUROC of 0.858 (95% CI, 0.823-0.893). Based on the nomogram, the CANPT score was established with cut-off values of 12 and 16. The percentages of patients with severe disease in the groups with CANPT scores <12, ≥12, and <16, and ≥16 were 4.15, 27.43, and 69.64%, respectively. Seventeen patients died. NLR, Cr, CK, and Alb were independent risk factors for mortality, and the CAN score was established to predict mortality. With a cut-off value of 15, the predictive accuracy was 97.4%, and the AUROC was 0.903 (95% CI 0.832, 0.974). Conclusions: The CANPT and CAN scores can predict the risk of severe disease and mortality in COVID-19 patients on admission.

Machine learning-based CT radiomics method for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: a multicenter study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a global challenge since the December 2019. The hospital stay is one of the prognostic indicators, and its predicting model based on CT radiomics features is important for assessing the patients' clinical outcome. The study aimed to develop and test machine learning-based CT radiomics models for predicting hospital stay in patients with COVID-19 pneumonia. METHODS: This retrospective, multicenter study enrolled patients with laboratory-confirmed SARS-CoV-2 infection and their initial CT images from 5 designated hospitals in Ankang, Lishui, Lanzhou, Linxia, and Zhenjiang between January 23, 2020 and February 8, 2020. Patients were classified into short-term (≤10 days) and long-term hospital stay (>10 days). CT radiomics models based on logistic regression (LR) and random forest (RF) were developed on features from pneumonia lesions in first four centers. The predictive performance was evaluated in fifth center (test dataset) on lung lobe- and patients-level. RESULTS: A total of 52 patients were enrolled from designated hospitals. As of February 20, 21 patients remained in hospital or with non-findings in CT were excluded. Therefore, 31 patients with 72 lesion segments were included in analysis. The CT radiomics models based on 6 second-order features were effective in discriminating short- and long-term hospital stay in patients with COVID-19 pneumonia, with areas under the curves of 0.97 (95% CI, 0.83-1.0) and 0.92 (95% CI, 0.67-1.0) by LR and RF, respectively, in test. The LR and RF model showed a sensitivity and specificity of 1.0 and 0.89, 0.75 and 1.0 in test respectively. As of February 28, a prospective cohort of six discharged patients were all correctly recognized as long-term stay using RF and LR models. CONCLUSIONS: The machine learning-based CT radiomics features and models showed feasibility and accuracy for predicting hospital stay in patients with COVID-19 pneumonia.

Clinical course of COVID-19 in patients with pre-existing decompensated cirrhosis: initial report from China.

BACKGROUND: The clinical characteristics and disease course in COVID-19 patients with pre-existing decompensated cirrhosis has not been described so far. METHODS: In this case series, we report three patients with confirmed COVID-19 and pre-existing decompensated cirrhosis from three hospitals in Hubei, the epicenter of the outbreak in China. RESULT: Patient 1 was a 53-year-old man with hepatitis B virus-related cirrhosis, portal hypertension, and ascites. Though receiving intensive support, he died of irreversible multiple organ dysfunction syndrome 48 days after the onset of the illness. Patient 2 was a 75-year-old woman with a history of schistosomiasis-related cirrhosis, portal hypertension, and ascites. Her family members requested that invasive rescue measures not be undertaken, and she died of acute respiratory distress syndrome 40 days after presenting with COVID-19 infection. Patient 3 was an 87-year-old man with alcohol-related cirrhosis, portal hypertension, and esophageal variceal hemorrhage. He was discharged from the hospital 29 days after illness onset. CONCLUSION: The case series raise the possibility that decompensated cirrhosis may be a risk factor for a poor outcome in patients with COVID-19.

Changes in T-lymphocyte subsets and risk factors in human immunodeficiency virus-negative patients with active tuberculosis.

PURPOSE: Immune function imbalance is closely associated with the occurrence and development of infectious diseases. We studied the characteristics of changes in T-lymphocyte subsets and their risk factors in HIV-negative patients with active tuberculosis (ATB). METHODS: T-lymphocyte subsets in 275 HIV-negative ATB patients were quantitatively analyzed and compared with an Mycobacteriumtuberculosis-free control group. Single-factor and multifactor analyses of clinical and laboratory characteristics of patients were also conducted. RESULTS: In ATB patients, CD4 and CD8 T-cell counts decreased, and the levels were positively interrelated (r = 0.655, P < 0.0001). After 4 weeks of antituberculosis treatment, CD4 and CD8 T-cell counts increased significantly but remained lower than in the control group. CD4 and CD8 cell counts were negatively associated with the extent of lesions detected in the chest by computed tomography (all P < 0.05). Although not reflected in the CD4/CD8 ratio, CD4 and CD8 cell counts differed between drug-resistant TB patients and drug-susceptible TB patients (P = 0.030). The multivariate analysis showed prealbumin, alpha-1 globulin, body mass index, and platelet count were independent risk factors for decreased CD4 cell count (all P < 0.05), while age and platelet count were independent risk factors for decreased CD8 cell count (all P < 0.05). CONCLUSION: CD4 and CD8 T-cell counts showed the evident value in predicting ATB severity. An increase in the CD4/CD8 ratio may be a critical clue of drug resistance in ATB. Although the factors influencing CD4 and CD8 are not identical, our results indicated the importance of serum protein and platelets to ATB patients' immune function.

A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors.

The objective of the present investigation was to explore the influencing factors and value of computed tomography (CT) for diagnosing severe chest lesions in active pulmonary tuberculosis (APTB). This retrospective investigation included 463 patients diagnosed with APTB. Relevant clinical features were collected. Patients were assigned to mild/moderate group or advanced group depending on the lesion severity on chest CT, severe chest CT lesion refers to the moderately dense or less diffuse lesion that exceeds the total volume of one lung, or the dense fusion lesion greater than one third of the volume of one lung, or the lesion with cavity diameter ≥4 cm. Independent risk factors for severe lesions were determined by univariate and multivariate logistic regression analyses, and the diagnostic efficiency of the risk factors was assessed by receiver operating characteristic curve (ROC). Chest CT demonstrated that there were 285 (61.56%) cases with severe lesions; multivariate Logistic regression analysis showed dust exposure [odds ratio (OR) = 4.108, 95% confidence interval (CI) 2.416-6.986], patient classification (OR = 1.792, 95% CI 1.067-3.012), age (OR = 1.018, 95% CI 1.005-1.030), and albumin-globulin ratio (OR = 0.179, 95% CI 0.084-0.383) to be independently correlated with severe lesions on chest CT. ROC curve analysis showed the cutoff values of age, albumin-globulin ratio and combined score to be 39 years, 0.918 and -0.085, respectively. The predictive value of combined score area under the curve 0.753 (95% CI 0.708-0.798) was higher than that of any single factor. The combined score of these four factors further improved the predictive efficacy.

Quantitative investigation of factors relevant to the T cell spot test for tuberculosis infection in active tuberculosis.

BACKGROUND: Previous qualitative studies suggested that the false negative rate of the T cell spot test for tuberculosis infection (T-SPOT.TB) is associated with many risk factors in tuberculosis patients. However, more precise quantitative studies are lacking. The purpose of this study was to investigate the factors affecting quantified spot-forming cells (SFCs) to early secreted antigenic target 6 kDa (ESAT-6) or culture filtrate protein 10 kDa (CFP-10) in patients with active tuberculosis. METHODS: We retrospectively analyzed the data of 360 patients who met the inclusion criteria. Using the SFCs to ESAT-6 or CFP-10 levels as dependent variables, variables with statistical significance in the univariate analysis were subjected to optimal scaling regression analysis. The combination of ESAT-6 and CFP-10 (i.e., T-SPOT.TB) was analyzed by the exact logistic regression model. RESULTS: The results showed that the SFCs to ESAT-6 regression model had statistical significance (P < 0.001) and that previous treatment and CD4+ and platelet counts were its independent risk factors (all P < 0.05). Their importance levels were 0.095, 0.596 and 0.100, respectively, with a total of 0.791. The SFCs to CFP-10 regression model also had statistical significance (P < 0.001); platelet distribution width and alpha-2 globulin were its independent risk factors (all P < 0.05). Their importance levels were 0.287 and 0.247, respectively, with a total of 0.534. The quantification graph showed that quantified SFCs to ESAT-6 or CFP-10 grading had a linear correlation with risk factors. Albumin-globulin ratio, CD4+ and CD8+ were independent risk factors for false negative T-SPOT.TB (all P < 0.05). CONCLUSIONS: In T-SPOT.TB-assisted diagnosis of patients with active tuberculosis, previous treatment, decreased CD4+ and platelet count might lead to the decreased SFCs to ESAT-6, decreased alpha-2 globulin and high platelet distribution width might lead to the decreased SFCs to CFP-10, decreased albumin-globulin ratio, CD4+ and CD8+ might lead to an increase in the false negative rate of the T-SPOT.TB.