Changing Trajectories of Alanine Aminotransferase and Risk of Antituberculosis Drug-Induced Liver Injury in Chinese Patients: A Cohort Study.

Antituberculosis drug-induced liver injury (ATLI) is a major adverse effect during antituberculosis treatment. Early detection or prediction is essential to prevent ATLI in antituberculosis treatment patients. The purpose of this work is to explore the relationship between alanine aminotransferase (ALT) trajectories within 15 days of initial treatment and the risk of ATLI. Based on a historical cohort of patients hospitalized for antituberculosis treatment and group-based trajectory modeling analysis, ALT trajectories within 15 days of initial treatment were determined. Conditional logistic regression model was used to estimate the association between different ALT trajectories and the risk of ATLI, and the corresponding odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated with covariates. Based on the ALT levels within 15 days of initial treatment, a total of 853 patients were divided into four ALT trajectories. The incidence of ATLI significantly increased with the increase of ALT trajectories (2.33%, 4.38%, 5.90%, and 2.44%, respectively). Compared with trajectory 1, the adjusted OR for ATLI in trajectory 2, trajectory 3, and trajectory 4 were 2.448 (95% CI: 0.302-19.856, P = 0.402), 5.373 (95% CI: 0.636-45.411, P = 0.123), 11.010 (95% CI: 0.720-168.330, P = 0.085), respectively, and there was an increasing trend of ATLI risk (Ptrend = 0.015). Different ALT trajectories within 15 days of initial treatment were associated with different risk of ATLI, and it is necessary to pay attention to the ALT trajectory within 15 days of initial treatment to predict the occurrence of ATLI.

Leritrelvir for the treatment of mild or moderate COVID-19 without co-administered ritonavir: a multicentre randomised, double-blind, placebo-controlled phase 3 trial.

Background: Leritrelvir is a novel α-ketoamide based peptidomimetic inhibitor of SARS-CoV-2 main protease. A preclinical study has demonstrated leritrelvir poses similar antiviral activities towards different SARS-CoV-2 variants compared with nirmatrelvir. A phase 2 clinical trial has shown a comparable antiviral efficacy and safety between leritrelvir with and without ritonavir co-administration. This trial aims to test efficacy and safety of leritrelvir monotherapy in adults with mild-to-moderate COVID-19. Methods: This was a randomised, double-blind, placebo-controlled, multicentre phase 3 trial at 29 clinical sites in China. Enrolled patients were from 18 to 75 years old, diagnosed with mild or moderate COVID-19 and not requiring hospitalization. Patients had a positive SARS-CoV-2 nucleic acid test (NAT) and at least one of the COVID-19 symptoms within 48 h before randomization, and the interval between the first positive SARS-CoV-2 NAT and randomization was ≤120 h (5 days). Patients were randomly assigned in a 1:1 ratio to receive a 5-day course of either oral leritrelvir 400 mg TID or placebo. The primary efficacy endpoint was the time from the first dose to sustained clinical recovery of all 11 symptoms (stuffy or runny nose, sore throat, shortness of breath or dyspnea, cough, muscle or body aches, headache, chills, fever ≥37 °C, nausea, vomiting, and diarrhea). The safety endpoint was the incidence of adverse events (AE). Primary and safety analyses were performed in the intention-to-treat (ITT) population. This study is registered with ClinicalTrials.gov, NCT05620160. Findings: Between Nov 12 and Dec 30, 2022 when the zero COVID policy was abolished nationwide, a total of 1359 patients underwent randomization, 680 were assigned to leritrelvir group and 679 to placebo group. The median time to sustained clinical recovery in leritrelvir group was significantly shorter (251.02 h [IQR 188.95-428.68 h]) than that of Placebo (271.33 h [IQR 219.00-529.63 h], P = 0.0022, hazard ratio [HR] 1.20, 95% confidence interval [CI], 1.07-1.35). Further analysis of subgroups for the median time to sustained clinical recovery revealed that (1) subgroup with positive viral nucleic acid tested ≤72 h had a 33.9 h difference in leritrelvir group than that of placebo; (2) the subgroup with baseline viral load >8 log 10 Copies/mL in leritrelvir group had 51.3 h difference than that of placebo. Leritrelvir reduced viral load by 0.82 log10 on day 4 compared to placebo. No participants in either group progressed to severe COVID-19 by day 29. Adverse events were reported in two groups: leritrelvir 315 (46.46%) compared with placebo 292 (43.52%). Treatment-relevant AEs were similar 218 (32.15%) in the leritrelvir group and 186 (27.72%) in placebo. Two cases of COVID-19 pneumonia were reported in placebo group, and one case in leritrelvir group, none of them were considered by the investigators to be leritrelvir related. The most frequently reported AEs (occurring in ≥5% of participants in at least one group) were laboratory finding: hypertriglyceridemia (leritrelvir 79 [11.7%] vs. placebo 70 [10.4%]) and hyperlipidemia (60 [8.8%] vs. 52 [7.7%]); all of them were nonserious. Interpretation: Leritrelvir monotherapy has good efficacy for mild-to-moderate COVID-19 and without serious safety concerns. Funding: This study was funded by the National Multidisciplinary Innovation Team Project of Traditional Chinese Medicine, Guangdong Science and Technology Foundation, Guangzhou Science and Technology Planning Project and R&D Program of Guangzhou Laboratory.

Performance of the MeltPro TB assay as initial test for diagnosis of pulmonary tuberculosis with drug-resistance detection.

BACKGROUND: The MeltPro TB assay (MeltPro) is a molecular rapid diagnostic test designed for detecting resistance to antituberculosis drugs. However, the performance of MeltPro as an initial diagnostic test for simultaneously detecting the presence of Mycobacterium tuberculosis (MTB) and drug resistance has not been evaluated. This study aims to assess the performance of MeltPro as initial diagnostic test for simultaneous detection of MTB and drug resistance in clinical samples from patients with presumptive pulmonary tuberculosis (PTB). METHODS: A retrospective analysis was conducted on 1283 patients with presumptive PTB from two clinical centers, out of which 875 were diagnosed with PTB. The diagnostic accuracy of MeltPro, Xpert MTB/RIF (Xpert), and MGIT 960 for PTB detection was evaluated. Rifampicin (RIF), isoniazid (INH), ethambutol (EMB), streptomycin (STR), and fluoroquinolone (FQ) resistance were detected using MeltPro, with Xpert and/or the broth microdilution plate method (MYCOTB) results as references. RESULTS: For the diagnosis of PTB, MeltPro showed a sensitivity of 69.0%, which was similar to Xpert (72.7%; P > 0.05) and higher than MGIT (58.1%; P < 0.001). The specificity of MeltPro was 97.1%, similar to Xpert (98.0%; P > 0.05). In smear-negative patients, MeltPro's sensitivity was 50.9%, similar to Xpert (56.5%; P > 0.05), and higher than MGIT (33.1%; P < 0.001). Based on Xpert and/or MYCOTB results, MeltPro exhibited a sensitivity and specificity of 98.3% and 99.2%, respectively, for detecting RIF resistance. Based on MYCOTB results, MeltPro's sensitivity for detecting resistance to INH, EMB, STR, and FQ was 96.4%, 89.1%, 97.5%, and 90.3%, respectively, with specificities of 96.0%, 96.0%, 95.2%, and 99.4%, respectively. CONCLUSION: The MeltPro TB assay could potentially be an effective alternative as the initial test for rapid diagnosis of PTB with drug-resistance detection in clinical practice.

A prospective multicenter clinical research study validating the effectiveness and safety of a chest X-ray-based pulmonary tuberculosis screening software JF CXR-1 built on a convolutional neural network algorithm.

Background: Chest radiography (chest X-ray or CXR) plays an important role in the early detection of active pulmonary tuberculosis (TB). In areas with a high TB burden that require urgent screening, there is often a shortage of radiologists available to interpret the X-ray results. Computer-aided detection (CAD) software employed with artificial intelligence (AI) systems may have the potential to solve this problem. Objective: We validated the effectiveness and safety of pulmonary tuberculosis imaging screening software that is based on a convolutional neural network algorithm. Methods: We conducted prospective multicenter clinical research to validate the performance of pulmonary tuberculosis imaging screening software (JF CXR-1). Volunteers under the age of 15 years, both with or without suspicion of pulmonary tuberculosis, were recruited for CXR photography. The software reported a probability score of TB for each participant. The results were compared with those reported by radiologists. We measured sensitivity, specificity, consistency rate, and the area under the receiver operating characteristic curves (AUC) for the diagnosis of tuberculosis. Besides, adverse events (AE) and severe adverse events (SAE) were also evaluated. Results: The clinical research was conducted in six general infectious disease hospitals across China. A total of 1,165 participants were enrolled, and 1,161 were enrolled in the full analysis set (FAS). Men accounted for 60.0% (697/1,161). Compared to the results from radiologists on the board, the software showed a sensitivity of 94.2% (95% CI: 92.0-95.8%) and a specificity of 91.2% (95% CI: 88.5-93.2%). The consistency rate was 92.7% (91.1-94.1%), with a Kappa value of 0.854 (P = 0.000). The AUC was 0.98. In the safety set (SS), which consisted of 1,161 participants, 0.3% (3/1,161) had AEs that were not related to the software, and no severe AEs were observed. Conclusion: The software for tuberculosis screening based on a convolutional neural network algorithm is effective and safe. It is a potential candidate for solving tuberculosis screening problems in areas lacking radiologists with a high TB burden.

Relationship between common telomere length-related genetic variations, telomere length, and risk of antituberculosis drug-induced hepatotoxicity in Chinese Han population: As assessed for causality using the updated Roussel Uclaf Causality Assessment Method.

Antituberculosis drug-induced hepatotoxicity (ATDH) is a significant threat to tuberculosis control, and two recent studies indicated that leukocyte telomere length (LTL) might be a potential biomarker for ATDH. This study aimed to investigate the relationship between common telomere length-related genetic variations, LTL, and risk of ATDH in Eastern Chinese antituberculosis treatment patients. A 1:4 matched case-control study was conducted among 79 ATDH cases assessed for causality using the updated RUCAM and 316 controls. LTL was determined by quantitative real-time PCR, and nine SNPs involved in telomere biology reported by previous GWAS were assessed. Conditional logistic regression model was used to estimate the association between genotypes and risk of ATDH with odds ratios (ORs) and 95% confidence intervals (CIs). The average RUCAM score of cases was 7.1. The average LTL in cases was significantly shorter than that in controls (median = 1.239 vs. 1.481, P = 0.032). Differences in the distribution of LTL were statistically significant among three genotypes of SNP rs2736098 (CC vs. CT vs. TT, median = 1.544 vs. 1.356 vs. 1.337, P = 0.026) and rs2853677 (AA vs. AG vs. GG, median = 1.511 vs. 1.544 vs. 1.159, P = 0.005) in TERT. SNP rs7675998 in NAF1 was statistically associated with the risk of ATDH under the dominant model (adjusted OR = 1.725, 95% CI: 1.021-2.913, P = 0.042). This is the first study to investigate the relationship of LTL, common telomere length-related variations, and risk of ATDH. SNP rs2736098 and rs2853677 in TERT were significantly associated with LTL, and SNP rs7675998 in NAF1 may be associated with ATDH in Chinese population.

High accuracy of recombinant fusion protein early secretory antigenic target protein 6-culture filtrate protein 10 skin test for the detection of tuberculosis infection: a phase III, multi-centered, double-blind, hospital-based, randomized controlled trial.

OBJECTIVES: To verify the diagnostic utility of recombinant fusion protein ESAT6-CPF10 (EC), a novel skin test reagent to detect Mycobacterium tuberculosis infection. METHODS: A multi-centered, double-blind, randomized controlled trial was conducted from December 17, 2015, to March 2, 2018. Participants involved in this study included those with active tuberculosis (TB), suspected pulmonary TB, or non-TB pulmonary disease. Each participant received three tests simultaneously, TB-specific enzyme-linked immunospot assay (T-SPOT.TB), tuberculin skin test (TST), and EC skin test (ECST), and adverse events were reported. RESULTS: Diagnostic accuracy was analyzed using data from 1085 protocol-compliant participants. The sensitivities of the ECST, TST, and T-SPOT.TB were 91.2% (95% CI, 89.0-93.2%), 91.4% (95% CI, 89.1-93.3%), and 92.1% (95% CI, 89.9-93.9%), respectively. The specificities of the ECST (69.7%, 95% CI, 64.5-74.5%) and T-SPOT.TB (76.1%, 95% CI, 71.2-80.5%) were significantly higher than the TST (54.4%, 95% CI, 48.9-59.7%). The agreements between ECST and TST (kappa = 0.632) and between ECST and T-SPOT.TB (kappa = 0.780) were substantial. No severe adverse event was reported. CONCLUSION: The diagnostic performance of the ECST was close to the T-SPOT.TB assay in the detection of TB infection and indicated good potential for clinical application in common scenarios.

The relationship between relative telomere length and anti-tuberculosis drug-induced hepatitis : A case-control study.

AIM: Anti-tuberculosis drug-induced hepatitis (AT-DIH) is a common and serious adverse drug reaction of tuberculosis treatment. Evidence demonstrated that many factors could affect the occurrence of AT-DIH, such as ageing, smoking, alcohol, oxidative stress, etc., while these factors could also promote telomere shortening. Therefore, relative telomere length (RTL) is indirectly related to the occurrence of AT-DIH. The present study aimed to explore and validate this relationship in Chinese tuberculosis patients. METHODS: A 1:4 matched case-control study was undertaken using 202 AT-DIH cases and 808 controls. Logistic regression models were used to estimate the association between RTL and AT-DIH with odds ratios (ORs) and 95% confidence intervals (CIs). The area under receiver operating characteristic curve (AUC) was calculated to estimate the discriminative performance for distinguishing AT-DIH cases from controls. RESULTS: The average RTL in AT-DIH cases was significantly shorter than that in controls (1.24 vs. 1.46, P=0.002). Patients with longer RTL were at a reduced risk of AT-DIH (OR=0.79, 95% CI: 0.66-0.94, P=0.009), and a dose-response relationship also existed between RTL and lower AT-DIH risk (P for trend=0.012). Under the optimal RTL cut-off value of 1.22, the corresponding AUCs were 0.57 (95% CI: 0.53-0.62, P=0.001) in the univariate model and 0.62 (95% CI: 0.57-0.66, P<0.001) in the multivariate model. CONCLUSION: This study showed that the shorter the RTL, the higher the risk of AT-DIH during an anti-tuberculosis treatment. The short RTL could potentially serve as a risk factor or a predictive test of the hepatotoxic risk associated with anti-tuberculosis treatments.

The role of the genetic variant FECH rs11660001 in the occurrence of anti-tuberculosis drug-induced liver injury.

WHAT IS KNOWN AND OBJECTIVE: The pathogenic mechanism of anti-tuberculosis drug-induced liver injury (AT-DILI) is still largely unknown. Recent studies have indicated that rifampicin and isoniazid cotreatment causes the accumulation of endogenous protoporphyrin IX in the liver through the haem biosynthesis pathway. Alanine synthase 1 (ALAS1) and ferrochelatase (FECH) are the rate-limiting enzymes in the production of haem. The present study aimed to investigate the genetic contribution of the ALAS1 and FECH genes to the risk of AT-DILI in an Eastern Chinese Han population. METHODS: A 1:4 matched case-control study was conducted, and eight SNPs in the ALAS1 and FECH genes were detected and assessed. A multivariate conditional logistic regression model was used to estimate the association between genotypes and the risk of AT-DILI by the odds ratios (ORs) with 95% confidence intervals (CIs), with liver disease history, hepatoprotectant use, smoking and drinking history as covariates. RESULTS AND DISCUSSION: Overall, 202 AT-DILI cases and 808 controls were included in this study. The female patients carrying polymorphisms of rs11660001 in FECH had an increased risk of AT-DILI under the dominant and additive models (OR = 1.831, 95% CI: 1.014-3.307, p = 0.045; OR = 1.673, 95% CI: 1.015-2.760, p = 0.044, respectively). The peak aspartate transaminase level was significantly higher in female patients carrying the GA+AA genotype of rs11660001 than in those with the GG genotype during anti-TB treatment (p = 0.032). WHAT IS NEW AND CONCLUSION: Based on this 1:4 individual matched case-control study, SNP rs11660001 in the FECH gene may be associated with susceptibility to AT-DILI in Chinese female anti-TB treatment patients. Further studies in larger varied populations are needed to validate our findings.

Heme oxygenase-1 and hemopexin gene polymorphisms and the risk of anti-tuberculosis drug-induced hepatotoxicity in China.

Objective: To assess whether the risk of anti-tuberculosis drug-induced hepatotoxicity (ATDH) might be influenced by heme oxygenase-1 (HMOX1) and hemopexin (HPX) gene polymorphisms. Methods: A dynamic anti-tuberculosis treatment cohort was constructed, and the 1:4 matched nested case-control study was analysed. Eight single-nucleotide polymorphisms (SNPs) of the two genes were selected for genotyping and Bonferroni correction was performed to correct for multiple comparison. Results: Overall, 7.8% of patients developed ATDH. SNP rs1807714 in the HMOX1 gene had decreased effects on the risk of moderate and severe hepatotoxicity under the dominant and additive models, and hepatocellular injury under the additive model. SNP rs2682099 in the HPX gene had increased effects on the risk of moderate and severe hepatotoxicity under the recessive model. However, these associations disappeared after Bonferroni correction. Conclusion:HMOX1 and HPX gene polymorphisms might not be associated with susceptibility to ATDH in the Chinese population.

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.

A validation study of the UGT1A4 rs2011404 variant and the risk of anti-tuberculosis drug-induced hepatotoxicity in an Eastern Chinese Han population.

WHAT IS KNOWN AND OBJECTIVE: Anti-tuberculosis (anti-TB) drug-induced hepatotoxicity (ATDH) is a serious adverse drug reaction. A recent study found that the rs2011404 variant of uridine 5'-diphospho-glucuronosyl-transferase 1A4 (UGT1A4) is a marker of susceptibility to ATDH. The present study aimed to validate this relationship in an Eastern Chinese Han anti-TB treatment population. METHODS: A 1:4 matched case-control study was conducted among anti-TB treatment patients in four regions of Jiangsu. ATDH was diagnosed based on the criteria from the Chinese Society of Hepatology and the updated Roussel Uclaf Causality Assessment Method. A conditional logistic regression model was used to estimate the association between rs2011404 genotypes and the risk of ATDH using odds ratios (ORs) with 95% confidence intervals (95% CIs) and smoking, drinking, hepatoprotectant use and liver diseases as covariates. RESULTS AND DISCUSSION: A total of 202 ATDH cases and 808 controls were matched according to age, sex and treatment history. After correcting for potential confounding factors, conditional logistic regression analysis indicated no significant differences in genotypes between the two groups (CC vs. TC: OR = 0.933, 95% CI: 0.457-1.905, p = 0.849). Subgroup analysis suggested that patients carrying the CC genotype at rs2011404 in UGT1A4 were at a reduced risk of moderate or severe liver injury (OR = 0.293, 95% CI: 0.093-0.921, p = 0.036). WHAT IS NEW AND CONCLUSION: Based on a 1:4 individual matched case-control study, possessing the CC genotype at rs2011404 of the UGT1A4 gene reduces the risk of moderate or severe liver injury in Eastern Chinese Han patients receiving anti-TB treatment. Further research is warranted to explain the role of the UGT1A4 gene and its contribution to individual differences in susceptibility to ATDH.

A risk score for prediction of poor treatment outcomes among tuberculosis patients with diagnosed diabetes mellitus from eastern China.

Persons living with diabetes (PLWD) with newly diagnosed tuberculosis are at greater risk of poor treatment outcomes. Identifying and prioritizing high-risk subgroups of PLWD and tuberculosis for tuberculosis programs to target has been rarely performed. We investigated risk factors for poor tuberculosis treatment outcomes among PLWD and developed a predictive risk score for tuberculosis control prioritization. Among PLWD diagnosed with tuberculosis, demographic, clinical, and tuberculosis treatment outcome data were collected. Poor treatment outcomes included treatment failure, death, default, and transfer. Multivariable logistic regression modeling was used to analyze risk factors of poor treatment outcomes. Risk scores were derived based on regression coefficients to classify participants at low-, intermediate-, and high-risk of poor treatment outcomes. Among 335 PLWD newly diagnosed with tuberculosis, 109 were cured and 172 completed treatment. Multivariable logistic regression found that risk factors of poor treatment outcomes included bacteriologically-positivity, low body mass index, no physical activity, and pulmonary cavitation. Rates of poor treatment outcomes in low- (0-2), intermediate- (3-4), and high-risk (5-8) groups were 4.2%, 10.5%, and 55.4% (Ptrend < 0.0001), respectively. The risk score accurately discriminated poor and successful treatment outcomes (C-statistic, 0.85, 95% CI 0.78-0.91). We derived a simple predictive risk score that accurately distinguished those at high- and low-risk of treatment failure. This score provides a potentially useful tool for tuberculosis control programs in settings with a double burden of both tuberculosis and diabetes.

Glycemic Trajectories and Treatment Outcomes of Patients with Newly Diagnosed Tuberculosis: A Prospective Study in Eastern China.

Rationale: Patients with newly diagnosed tuberculosis often have inconsistent glycemic measurements during and after treatment. Distinct glycemic trajectories after the diagnosis of tuberculosis are not well characterized, and whether patients with stress hyperglycemia have poor treatment outcomes is not known.Objectives: To identify distinct glycemic trajectories from the point of tuberculosis diagnosis to the posttreatment period and to assess the relationship between glycemic trajectories and tuberculosis treatment outcomes.Methods: Patients with newly diagnosed, drug-susceptible tuberculosis and with at least three fasting plasma glucose tests at tuberculosis diagnosis and during the third and sixth month of treatment were identified and included from Jiangsu Province, China. Patients were also given an additional fasting plasma glucose test at 2 and 4 months after treatment.Measurements and Main Results: Several distinct glycemic trajectories from the point of tuberculosis diagnosis to the posttreatment period were found, including consistently normal glycemic testing results (43%), transient hyperglycemia (24%), erratic glycemic instability (12%), diabetes (16%), and consistent hyperglycemia without diabetes (6%). Compared with participants with a consistently normal glycemic trajectory, patients with transient hyperglycemia were more likely to experience treatment failure (adjusted odds ratio [AOR], 4.20; 95% confidence interval [CI], 1.57-11.25; P = 0.004) or erratic glycemic instability (AOR, 5.98; 95% CI, 2.00-17.87; P = 0.001). Patients living with diabetes also had a higher risk of experiencing treatment failure (AOR, 6.56; 95% CI, 2.22-19.35; P = 0.001), and this was modified by glycemic control and metformin use.Conclusions: Among patients with tuberculosis without diabetes, glycemic changes were common and may represent an important marker for patient response to tuberculosis treatment.

Comparing the performance of time series models with or without meteorological factors in predicting incident pulmonary tuberculosis in eastern China.

BACKGROUND: Many studies have compared the performance of time series models in predicting pulmonary tuberculosis (PTB), but few have considered the role of meteorological factors in their prediction models. This study aims to explore whether incorporating meteorological factors can improve the performance of time series models in predicting PTB. METHODS: We collected the monthly reported number of PTB cases and records of six meteorological factors in three cities of China from 2005 to 2018. Based on this data, we constructed three time series models, including an autoregressive integrated moving average (ARIMA) model, the ARIMA with exogenous variables (ARIMAX) model, and a recurrent neural network (RNN) model. The ARIMAX and RNN models incorporated meteorological factors, while the ARIMA model did not. The mean absolute percentage error (MAPE) and root mean square error (RMSE) were used to evaluate the performance of the models in predicting PTB cases in 2018. RESULTS: Both the cross-correlation analysis and Spearman rank correlation test showed that PTB cases reported in the study areas were related to meteorological factors. The predictive performance of both the ARIMA and RNN models was improved after incorporating meteorological factors. The MAPEs of the ARIMA, ARIMAX, and RNN models were 12.54%, 11.96%, and 12.36% in Xuzhou, 15.57%, 11.16%, and 14.09% in Nantong, and 9.70%, 9.66%, and 12.50% in Wuxi, respectively. The RMSEs of the three models were 36.194, 33.956, and 34.785 in Xuzhou, 34.073, 25.884, and 31.828 in Nantong, and 19.545, 19.026, and 26.019 in Wuxi, respectively. CONCLUSIONS: Our study revealed a possible link between PTB and meteorological factors. Taking meteorological factors into consideration increased the accuracy of time series models in predicting PTB, and the ARIMAX model was superior to the ARIMA and RNN models in study settings.

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.

Association between NR1I2 polymorphisms and susceptibility to anti-tuberculosis drug-induced hepatotoxicity in an Eastern Chinese Han population: A case-control study.

OBJECTIVE: Anti-tuberculosis drug-induced hepatotoxicity (ATDH) is a serious adverse drug reaction, and its pathogenic mechanism is still largely unknown. Pregnane X receptor (PXR, encoded by the NR1I2 gene) is a ligand-dependent transcription factor, and rifampicin is a human PXR-specific activator. Rifampicin and isoniazid co-therapy targets porphyrin biosynthesis via PXR and results in hepatic protoporphyrin IX accumulation and subsequent liver injury. The present study aimed to investigate the associations between genetic polymorphisms in NR1I2 and ATDH in an Eastern Chinese Han population. METHODS: A 1:4 matched case-control study was conducted using 146 ATDH cases and 584 controls. Seven single nucleotide polymorphisms (SNPs) were detected and analysed. Multivariate conditional logistic regression analysis was used to estimate the association between genotypes and risk of ATDH by the odds ratios (ORs) with 95% confidence intervals (CIs), with liver disease history, hepatoprotectant use, smoking history and drinking history as covariates. RESULTS: Patients carrying the GG genotype of rs7643645 were at a higher risk of ATDH than those carrying the AA genotype (OR = 1.864, 95% CI: 1.106-3.141, P = .020), and significant differences were also found under the recessive model (P = .029) and additive model (P = .021). Patients with a polymorphism at rs2276707 were at a reduced risk of ATDH under the recessive model (OR = 0.600, 95% CI: 0.364-0.988, P = .045). Subgroup analysis confirmed the relationship in mild hepatotoxicity cases under the additive model (rs7643645, OR = 1.429, 95% CI: 1.027-1.988, P = .034) and recessive model (rs2276707, OR = 0.478, 95% CI: 0.253-0.902, P = .023). Functional annotation using ENCODE data also indicated that rs2276707 and rs7643645 were located in the histone modification regions targeting enhancers or promoter (H3K4Me1, H3K4Me3 and H3K27Ac). CONCLUSIONS: Based on this case-control study, SNPs rs7643645 and rs2276707 in NR1I2 may contribute to susceptibility to ATDH in Eastern Chinese Han anti-TB treatment patients. Further studies in larger varied populations are needed to validate our findings.

Association of ABO blood group and antituberculosis drug-induced liver injury: A case-control study from a Chinese Han population.

WHAT IS KNOWN AND OBJECTIVE: Antituberculosis drug-induced liver injury (ATLI) is a serious adverse drug reaction, and its pathogenic mechanism is still largely unknown. Rifampin (RIF) has been reported to cause haemolysis due to the production of drug-dependent antibodies, and haemolysis results in an increased level of free haem, which affects the function of hepatocytes. Blood group determinants can act as specific receptor sites for drug-antibody complexes, causing erythrocyte destruction in the presence of RIF. RIF-induced immune haemolysis may be a potential mechanism for ATLI. Thus, the study aimed to explore the role of ABO blood group systems in Chinese ATLI patients. METHODS: A 1:4 matched case-control study was conducted among 146 ATLI cases and 584 controls. Multivariable conditional logistic regression and Cox proportional regression were used to estimate the association between ABO blood group and risk of ATLI by odds ratio (OR), hazards ratio (HR) and 95% confidence intervals (CIs), and liver disease history and taking hepatoprotectant were used as covariates. RESULTS AND DISCUSSION: Patients in the A, B, AB and non-O blood groups had a significantly higher risk of ATLI than those in the O blood group (OR = 1.832, 95% CI: 1.126-2.983, P = .015; OR = 1.751, 95% CI: 1.044-2.937, P = .034; OR = 2.059, 95% CI: 1.077-3.938, P = .029; OR = 1.822, 95% CI: 1.173-2.831, P = .007, respectively). After considering the time of ALTI occurrence, similar results were found in the A, B, AB and non-O blood groups (HR = 1.676, 95% CI: 1.072-2.620, P = .024; HR = 1.620, 95% CI: 1.016-2.584, P = .043; HR = 2.010, 95% CI: 1.130-3.576, P = .018; HR = 1.701, 95% CI: 1.138-2.542, P = .010, respectively). Furthermore, subgroup analysis also detected a significant association between ABO blood group and ATLI in patients taking RIF (P < .05). However, no significant difference was observed in patients not taking RIF (P > .05). WHAT IS NEW AND CONCLUSION: The present study is the first to evaluate the role of ABO blood group systems in Chinese ATLI cases. Based on the present matched case-control study, the ABO blood group may be associated with susceptibility to ATLI in the Chinese antituberculosis population, especially in patients with blood groups A, B and AB who are taking RIF.