PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

Purpose::In patients with heatstroke, disseminated intravascular coagulation (DIC) is associated with greater risk of in-hospital mortality. However, time-consuming assays or a complex diagnostic system may delay immediate treatment. Therefore, the present study proposes a new heatstroke-induced coagulopathy (HIC) score in patients with heat illness as an early warning indicator for DIC.Methods::This retrospective study enrolled patients with heat illness in 24 Chinese hospitals from March 2021 to May 2022. Patients under 18 years old, with a congenital clotting disorder or liver disease, or using anticoagulants were excluded. Data were collected on demographic characteristics, routine blood tests, conventional coagulation assays and biochemical indexes. The risk factors related to coagulation function in heatstroke were identified by regression analysis, and used to construct a scoring system for HIC. The data of patients who met the diagnostic criteria for HIC and International Society on Thrombosis and Haemostasis defined-DIC were analyzed. All statistical analyses were performed using SPSS 26.0.Results::The final analysis included 302 patients with heat illness, of whom 131 (43.4%) suffered from heatstroke, including 7 death (5.3%). Core temperature ( OR = 1.681, 95% CI 1.291 - 2.189, p < 0.001), prothrombin time ( OR = 1.427, 95% CI 1.175 - 1.733, p < 0.001) and D-dimer ( OR = 1.242, 95% CI 1.049 - 1.471, p = 0.012) were independent risk factors for heatstroke, and therefore used to construct an HIC scoring system because of their close relation with abnormal coagulation. A total score ≥ 3 indicated HIC, and HIC scores correlated with the score for International Society of Thrombosis and Hemostasis-DIC ( r = 0.8848, p < 0.001). The incidence of HIC (27.5%) was higher than that of DIC (11.2%) in all of 131 heatstroke patients. Meanwhile, the mortality rate of HIC (19.4%) was lower than that of DIC (46.7%). When HIC developed into DIC, parameters of coagulation dysfunction changed significantly: platelet count decreased, D-dimer level rose, and prothrombin time and activated partial thromboplastin time prolonged ( p < 0.05). Conclusions::The newly proposed HIC score may provide a valuable tool for early detection of HIC and prompt initiation of treatment.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

ObjectiveTo investigate the role and possible mechanism of action of rhubarb decoction （RD） retention enema in improving inflammatory damage of brain tissue in a rat model of mild hepatic encephalopathy （MHE）. MethodsA total of 60 male Sprague-Dawley rats were divided into blank group （CON group with 6 rats） and chronic liver cirrhosis modeling group with 54 rats using the complete randomization method. After 12 weeks， 40 rats with successful modeling which were confirmed to meet the requirements for MHE model by the Morris water maze test were randomly divided into model group （MOD group）， lactulose group （LT group）， low-dose RD group （RD1 group）， middle-dose RD group （RD2 group）， and high-dose RD group （RD3 group）， with 8 rats in each group. The rats in the CON group and the MOD group were given retention enema with 2 mL of normal saline once a day； the rats in the LT group were given retention enema with 2 mL of lactulose at a dose of 22.5% once a day； the rats in the RD1， RD2， and RD3 groups were given retention enema with 2 mL RD at a dose of 2.5， 5.0， and 7.5 g/kg， respectively， once a day. After 10 days of treatment， the Morris water maze test was performed to analyze the spatial learning and memory abilities of rats. The rats were analyzed from the following aspects： behavioral status； the serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） and the level of blood ammonia； pathological changes of liver tissue and brain tissue； the mRNA and protein expression levels of phosphatidylinositol 3-kinase （PI3K）， protein kinase B （AKT）， and mammalian target of rapamycin （mTOR） in brain tissue. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the MOD group， the RD1， RD2， and RD3 groups had a significantly shorter escape latency （all P<0.01）， significant reductions in the levels of ALT， AST， IL-1β， IL-6， TNF-α， and blood ammonia （all P<0.05）， significant alleviation of the degeneration， necrosis， and inflammation of hepatocytes and brain cells， and significant reductions in the mRNA and protein expression levels of PI3K， AKT， and mTOR in brain tissue （all P<0.05）， and the RD3 group had a better treatment outcome than the RD1 and RD2 groups. ConclusionRetention enema with RD can improve cognitive function and inflammatory damage of brain tissue in MHE rats， possibly by regulating the PI3K/AKT/mTOR signaling pathway.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Background/Aims: Steatotic liver disease (SLD) is a common manifestation in chronic hepatitis C (CHC). Metabolic alterations in CHC are associated with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to elucidate whether hepatitis C virus (HCV) eradication mitigates MASLD occurrence or resolution. Methods: We enrolled 5,840 CHC patients whose HCV was eradicated by direct-acting antivirals in a nationwide HCV registry. MASLD and the associated cardiometabolic risk factors (CMRFs) were evaluated at baseline and 6 months after HCV cure. Results: There were 2,147 (36.8%) patients with SLD, and 1,986 (34.0%) of them met the MASLD criteria before treatment. After treatment, HbA1c (6.0% vs. 5.9%, p<0.001) and BMI (24.8 kg/m2 vs. 24.7 kg/m2, p<0.001) decreased, whereas HDL-C (49.1 mg/dL vs. 51.9 mg/dL, p<0.001) and triglycerides (102.8 mg/dL vs. 111.9 mg/dL, p<0.001) increased significantly. The proportion of patients with SLD was 37.5% after HCV eradication, which did not change significantly compared with the pretreatment status. The percentage of the patients who had post-treatment MASLD was 34.8%, which did not differ significantly from the pretreatment status (p=0.17). Body mass index (BMI) (odds ratio [OR] 0.89; 95% confidence intervals [CI] 0.85–0.92; p<0.001) was the only factor associated with MASLD resolution. In contrast, unfavorable CMRFs, including BMI (OR 1.10; 95% CI 1.06–1.14; p<0.001) and HbA1c (OR 1.19; 95% CI 1.04–1.35; p=0.01), were independently associated with MASLD development after HCV cure. Conclusions HCV eradication mitigates MASLD in CHC patients. CMRF surveillance is mandatory for CHC patients with metabolic alterations, which are altered after HCV eradication and predict the evolution of MASLD.

This study explored the growth-promoting effect and mechanism of the endophytic bacterium Kocuria rosea on Rehmannia glutinosa, aiming to provide a scientific basis for the development of green bacterial fertilizer. R. glutinosa 'Jinjiu' was treated with K. rosea, and the shoot parameters including leaf length, leaf width, plant width, and stem diameter were measured every 15 days. After 120 days, the shoots and roots were harvested. The root indicators(root number, root length, root diameter, root fresh weight, root dry weight, root volume, and root vitality) and secondary metabolites(catalpol, rehmannioside A, rehmannioside D, verbascoside, and leonuride) were determined. The R. glutinosa growth-promoting mechanism of K. rosea was discussed from the effect of K. rosea on the nutrient element content in R. glutinosa and rhizosphere soil and the genome information of this plant. After application of K. rosea, the maximum increases in leaf length, leaf width, plant width, and stem diameter were 35.67%(60 d), 25.39%(45 d), 40.17%(60 d), and 113.85%(45 d), respectively. The root number, root length, root diameter, root volume, root fresh weight, root dry weight, and root viability increased by 41.71%, 45.10%, 48.61%, 94.34%, 101.55%, 147.61%, and 42.08%, respectively. In addition, the content of rehmannioside A and verbascoside in the root of R. glutinosa increased by 76.67% and 69.54%, respectively. K. rosea promoted the transformation of nitrogen(N), phosphorus(P), and potassium(K) in the rhizosphere soil into the available state. Compared with that in the control, the content of available N(54.60 mg·kg~(-1)), available P(1.83 μmol·g~(-1)), and available K(83.75 mg·kg~(-1)) in the treatment with K. rosea increased by 138.78%, 44.89%, and 14.34%, respectively. The content of N, P, and K in the treatment group increased by 293.22%, 202.63%, and 23.80% in the roots and by 23.60%, 107.23%, and 134.53% in the leaves of R. glutinosa, respectively. K. rosea carried the genes related to colonization(rbsB, efp, bcsA, and gmhC), N, P, and K metabolism(narG, narH, narI, nasA, nasB, GDH2, pyk, aceB, ackA, CS, ppa, ppk, ppk2, pstS, pstA, pstB, and pstC), and indole-3-acetic acid and zeatin synthesis(iaaH and miaA). Further studies showed that K. rosea could colonize the roots of R. glutinosa and secrete indole-3-acetic acid(3.85 μg·mL~(-1)) and zeatin(0.10 μg·mL~(-1)). In summary, K. rosea promotes the growth of R.ehmannia glutinosa by enhancing the nutrient uptake, which provides a theoretical basis for the development of plant growth-promoting microbial products.
Rehmannia/metabolism* ; Endophytes/metabolism* ; Plant Roots/growth & development* ; Micrococcaceae/genetics* ; Data Mining ; Plant Leaves/metabolism* ; Genomics ; Rhizosphere

The chemical constituents in the ethanol extract of Hypericum wightianum(Hypericaceae) were purified by column chromatography and identified via magnetic resonance imaging(NMR), high-resolution mass spectrum, and circular dichroism. A total of 22 compounds were identified, including eight polyprenylated phloroglucinols(1-8), three chromones(9-11), and three terpenoids(14-16) and so on. Among them, compounds 16 and 17 were first reported in the genus Hypericum, and compounds 1-11, 14, 15, and 19 were first isolated from H. wightianum. Compounds 1-4 were previously reported as two pairs of enantiomers. This study reported the chiral resolutions and absolute configurations of compounds 1-4 for the first time.
Phloroglucinol ; Hypericum/chemistry* ; Molecular Structure ; Magnetic Resonance Spectroscopy ; Drugs, Chinese Herbal/chemistry*

Objective: To explore risk factors affecting treatment for deep neck space infections (DNSIs) so as to provide guidance for appropriate early managements. Methods: A retrospective cohort study was conducted on inpatients with DNSIs admitted to the Department of Otolaryngology, Head and Neck Surgery, Affiliated Hospital of Qingdao University from March 2013 to February 2021. Patients were divided into surgical and non-surgical groups based on whether they had surgery or not. Information collected included demographic data, disease-related signs and symptoms, treatment history, systemic comorbidities, imaging data and laboratory indicators. Hypothesis testing, univariate Logistic regression and multivariate Logistic regression were used for data processing. Resuts A total of 61 patients were included, including 37 males and 24 females, aged 6-96 years. There were 35 cases (57.4%) in the surgical group and 26 cases (42.6%) in the non-surgical group. Multivariate analysis showed that risk factors for surgery as followings: neck dyskinesia (OR=0.03, 95%CI: 0.00-0.24), dysphagia (OR=0.10, 95%CI: 0.02-0.72), serum white blood cell count≥16.74×10⁹/L (OR=1.18, 95%CI: 1.01-1.39) and interspace gas (OR=0.03, 95%CI: 0.00-0.30). Conclusion: Clinicians should be alert to these risk factors for surgery in the course of treatment and timely surgical treatment for patients who meet the conditions.
Male ; Female ; Humans ; Retrospective Studies ; Neck/surgery* ; Risk Factors ; Deglutition Disorders