To construct a preliminary quality evaluation index system for the centralized hospitalization treatment of infectious tuberculosis (TB), and to provide a reference basis for further promoting centralized hospitalization treatment of TB.

Based on Donabedian’s “structure-process-result” theoretical framework, the Delphi method and analytic hierarchy process were used toconstruct the content of the index system and determine the weights of the indicators.

The active coefficients of experts in both rounds are 100%, the authority index of experts is 0.918 and 0.922, and the Kendall harmony coefficients of first level, second level, and third level indicators are 0.168(χ²=8.400, P=0.015), 0.174(χ²=104.355, P<0.001), and 0.112(χ²=232.560, P<0.001) respectively, the difference was statistically significant. The final index system consists of 3 primary indicators, 25 secondary indicators, and 84 tertiary indicators.

The quality evaluation index system of centralized hospitalization treatment for infectious tuberculosis constructed in this study has a high degree of representativeness and authority, with a more standardized construction of indicators and a more reasonable distribution of weights, which lays the foundation for subsequent research.

To analyze the risk factors for phlebitis caused by scalp vein indwelling needle infusion in children, providing a basis for reducing the clinical incidence of phlebitis.

We analyzed the medical records of 3 618 patients aged 0-24 months who received scalp vein indwelling needle infusion therapy at our hospital from January 2019 to June 2024. A multivariate logistic regression model was used to analyze the risk factors for phlebitis and its severity associated with scalp vein indwelling needle infusion.

During scalp vein indwelling needle infusion therapy, 311 patients developed phlebitis, with an incidence rate of 8.60%. Among them, there were 175 cases in Grade 1, 89 cases in Grade 2, 39 cases in Grade 3, and 8 cases in Grade 4. Multivariate regression analysis showed that age≤12 months(OR=3.579, 95%CI: 1.055-12.135), indwelling needle retention time≥48 hours (OR=7.142, 95%CI: 2.426-21.030), unsuccessful venipuncture (OR=5.658, 95%CI: 1.278-25.044), junior nursing staff performing venipuncture (OR=3.747, 95%CI: 1.107-12.681), use of irritating drugs (OR=3.877, 95%CI: 1.719-8.744), daily infusion volume≥1L (OR=2.413, 95%CI: 1.066-5.465), infusion drug temperature<35℃ (OR=3.391, 95%CI: 1.044-11.012), infusion drug speed≥60 drops/min (OR=3.684, 95%CI: 1.675-8.100), and drug pH not between 5 and 9 (OR=6.527, 95%CI: 2.212-19.258) were independent risk factors for the occurrence of phlebitis due to scalp vein indwelling needle infusion (P<0.05). Multivariate ordinal logistic regression results for phlebitis grading showed that factors such as age, indwelling needle retention time, smoothness of the puncture process, seniority of medical staff, use of irritating drugs, daily infusion volume, and infusion drug temperature were positively correlated with the severity of phlebitis. The presence of these factors significantly increased the risk of children developing higher grades of phlebitis.

For younger patients undergoing scalp vein infusion therapy, it is recommended to promptly adjust drug pH and temperature, and appropriately assign experienced nursing staff to perform procedures to reduce the clinical risk of phlebitis.

To explore whether the number of somatic pain sites serves as a mediator between the number of chronic conditions and depressive symptoms in older adults.

Based on data from the 2020 wave of the China Health and Retirement Longitudinal Study (CHARLS), 8 363 participants aged 60 and above were analyzed. The mediating role between variables was examined using Model 4 of the PROCESS 4.0 macro, and the Bootstrap method was applied for validation.

The prevalence of depressive symptoms among older adults reached 41.02%. An increase in both chronic disease count and pain site number was significantly associated with higher levels of depressive symptoms. (r₁=0.284, r₂=0.350, both P<0.001). A positive correlation was also observed between the number of chronic diseases and the number of pain sites (r₃=0.381, P<0.001).The mediation analysis results indicate that the number of pain sites (effect size=0.15, Bootstrap 95%CI: 0.13-0.18) mediated the relationship between the number of chronic diseases and depressive symptoms.

Both the number of chronic diseases and the number of pain sites are important factors influencing depressive symptoms in the elderly, with the number of pain sites playing a partial mediating role between the two. It is recommended to strengthen pain management in the elderly, regularly assess pain status, provide personalized interventions, and incorporate psychological support to enhance the quality of life and promote mental health in elderly individuals.

To promptly identify common respiratory viruses causing infections and facilitate effective therapeutic interventions in resource-limited settings such as grassroots, clinics, border areas, and border defense, this study established a visual detection method based on recombinase polymerase amplification (RPA) technology and CRISPR/Cas12a (clustered regularly interspaced short palindromic repeats/CRISPR-associated 12a) system.

Initially, conservative sequences of each virus target were designed, and RPA primers along with single-strand guide RNAs (sgRNAs) were selected. Subsequently, the RPA technology was integrated with the CRISPR/Cas12a detection method for visual detection of influenza A virus, influenza B virus, respiratory syncytial virus, Severe Acute Respiratory Syndrome Coronavirus 2, and human rhinovirus.

The detection method yielded results within 1.5 hours, with a sensitivity of 3.5 copies/μl plasmid, and exhibited no cross-reactivity between each virus target. In terms of detection accuracy, this method demonstrated higher consistency compared to the control Quantitative Reverse Transcription Polymerase Chain Reaction, (qRT-PCR) method.

The visual detection method established in this study possesses good specificity and high sensitivity for the common five respiratory virus infections. It is suitable for on-site detection of common respiratory virus infections, especially in resource-limited environments, and holds promising clinical application prospects.

To investigate the prevalence of physical-psychological-cognitive multimorbidity patterns and their impact on the risk of falls among older adults in China.

Data were drawn from the CHARLS 2018-2020. A total of 6 431 participants aged 60 years and older were included. Physical-psychological-cognitive multimorbidity patterns were assessed in 2018 using self-reported physician-diagnosed diseases, the Center for Epidemiologic Studies Depression Scale, and the Mini-Mental State Examination. Falls were assessed in 2020 by self-reported fall events in the past two years. Poisson regression models with robust standard errors were used to analyse the association between multimorbidity patterns and the risk of falls.

1 228(19.1%) out of 6 431 participants aged 60 years and older had experienced a fall in the past two years. In terms of the physical-psychological-cognitive multimorbidity pattern, the highest proportion of older adults had only physical illnesses (33.9%), followed by physical illnesses plus cognitive impairment (17.8%) and physical-psychological-cognitive multimorbidity (16.9%). The lowest proportions were observed for older adults with psychological illnesses plus cognitive impairment (2.2%) and those with only psychological illnesses (1.6%). Compared with older adults without any illnesses, the risk of falling increased by 73%(aRRs: 1.73, 95%CI: 1.33-2.26), 83%(aRRs: 1.83, 95%CI: 1.11-3.03), 70%(aRRs: 1.70, 95%CI: 1.29-2.23), 164%(aRRs: 2.64, 95%CI: 2.02-3.43), and 182%(aRRs: 2.82, 95%CI: 2.17-3.67) for those with only physical illnesses, only psychological illnesses, physical illnesses plus cognitive impairment, physical plus psychological illnesses, and physical-psychological-cognitive multimorbidity, respectively.

Most combinations of physical, psychological, and cognitive disorders increase the risk of falls in older adults. Compared with older adults without any illness, the risk of falling was significantly elevated for those with comorbid physical and psychological illnesses, and the risk was highest for those with physical-psychological-cognitive multimorbidity. Interventions are needed to reduce the risk of falls in older adults with physical-psychological-cognitive multimorbidity.

Understand the current situation of palliative care services in Chengdu, analyze existing problems, and provide policy recommendations for further promoting the development of palliative care.

Relying on the Chengdu Municipal Palliative Care Quality Control Center to conduct a cross-sectional survey and collect city-wide data related to palliative care.

Thirty-three medical institutions provide palliative care services, offering a total of 512 beds, with 188 physicians, 325 nurses, 179 nursing aides, 59 social workers, and 145 volunteers. Medical staff with a master’s degree or higher and those with an associate senior title or higher account for 8.96% and 10.92%, respectively. The establishment rates of psychology and nutrition departments are 24.24% and 51.52%, respectively. Outpatient palliative care services include four items such as condition assessment and medication consultation, while inpatient services cover eight items including symptom control and comfort care. Home-based palliative care services consist of four items such as communication guidance and condition assessment. In 2022, a total of 2 295 palliative care patients were admitted, with an average length of stay of 18.02 days and an average cost per admission of 9 840 yuan.

There is a relative shortage of highly qualified health professionals in palliative care, a severe insufficiency in psychological and nutritional support services, and underutilization of palliative care resources. It is imperative to improve the palliative care service system, strengthen the training of specialized personnel, place greater emphasis on nutritional and psychological support services, and enhance the efficiency of palliative care resource utilization.

To analyze the trends in the disease burden of schizophrenia among Chinese adolescents aged 10-24 years from 1990 to 2021, reveal age, period, and cohort effects, and predict the disease burden trend from 2022 to 2030, providing a basis for formulating targeted prevention and control strategies.

Based on data from the Global Burden of Disease study, Joinpoint regression was used to analyze trends in age-standardized rates, an age-period-cohort model was applied to interpret age, period, and cohort effects on incidence and prevalence.

From 1990 to 2021, the incidence rate, prevalence rate, and disability-adjusted life year (DALY) rate of schizophrenia among Chinese adolescents showed a downward trend, decreasing from 33.64/100 000, 145.77/100 000, and 98.69/100 000 to 31.51/100 000, 133.55/100 000, and 90.80/100 000, with decline rates of 6.33%, 8.38%, and 8.00%, respectively. In contrast, the age-standardized incidence rate, prevalence rate, and DALY rate increased slowly at average annual growth rates of 0.05%, 0.13%, and 0.14%, respectively. The trend of age-standardized incidence rate could be divided into three periods: 1990-2008 (APC=-0.02%), 2005-2016 (APC=-0.28%), and 2016-2021 (APC=0.77%). The trend of age-standardized prevalence rate was divided into four periods: 1990-2004 (APC=-0.01%), 2004-2010 (APC=0.13%), 2010-2016 (APC=-0.14%), and 2016-2021 (APC=0.84%). The trend of age-standardized DALY rate was divided into four periods: 1990-2005 (APC=0.02%), 2005-2010 (APC=0.20%), 2010-2016 (APC=-0.16%), and 2016-2021 (APC=0.81%). The age-period-cohort model revealed that the risks of incidence and prevalence increased significantly with age (RR values for the 20-24-year-old group were 2.37 and 4.41, respectively, significantly higher than 0.30 and 0.17 in the 10-14-year-old group), showed a mild upward trend over time (RR values increased from 0.94 and 0.91 in 1990-1994 to 1.08 and 1.11 in 2020—2021), and decreased with later birth cohorts (RR values for the 1970-1974 birth cohort were 1.07 and 1.11, dropping to 0.96 and 0.92 in the 2010-2014 cohort).

From 1990 to 2021, the incidence, prevalence, and DALY rates of schizophrenia among Chinese adolescents showed a downward trend, while the standardized rates exhibited a slow upward trend. Age growth and temporal trends were key factors in risk elevation, while younger birth cohorts exhibited lower risks. Dynamic intervention strategies targeting adolescents are needed in the future, with particular attention to the rising age-standardized burden.

To investigate the independent and joint effects of long-term exposure to air pollutants on the metabolic syndrome risk in adults.

Data were obtained from the surveillance and investigation of chronic diseases and risk factors in Hubei Province from 2018 to 2020. The daily average concentrations of PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO at 1-kilometre spatial resolution were matched according to participants’ residential addresses, and the average levels of these air pollutants over the 1-year period before the survey conducted were calculated to assign individual-level exposure. Multilevel logistic regression and weighted quantile sum regression models were applied to evaluate the independent and joint effects of air pollutant exposure on the risk for metabolic syndrome, respectively.

A total of 24 322 adults were included in the final analysis, with a metabolic syndrome prevalence of 39.8%. Higher exposure to PM_2.5(OR=1.011, 95%CI:1.001-1.020) and O₃ (OR=1.012, 95%CI: 1.005-1.018) were associated with an increased risk for metabolic syndrome. Subgroup analyses showed that exposure to PM_2.5 was positively associated with risk for metabolic syndrome among rural residents (OR=1.018, 95%CI: 1.006-1.030), and the positive association between exposure to O₃ and metabolic syndrome were found in adults beyond 60 years (OR=1.015, 95%CI: 1.008-1.023) and those physically active (OR=1.015, 95%CI: 1.008-1.022). The WQS regression revealed a positive association between long-term exposure to air pollutant mixtures and the metabolic syndrome risk (OR=1.188, 95%CI: 1.129-1.251), with O₃, CO, and PM_2.5 contributing 44.3%, 34.8%, and 20.8% to the joint effect, respectively.

Both long-term individual and joint exposures to air pollutants are positively associated with metabolic syndrome risk in adults, with the joint exposure showing a stronger adverse effect primarily driven by O₃, CO, and PM_2.5. To mitigate metabolic syndrome risk in adults, comprehensive prevention and control strategies should be implemented to reduce exposure to air pollutants.

To analyze the dynamic trends in incidence and prevalence of periodontal disease in China from 1992-2021, quantify age, period, and cohort effects, and project future trends over the next two decades, thereby informing targeted prevention strategies.

Data were extracted from the 2021 Global Burden of Disease Study. Joinpoint Regression (JPR5.0.2) was employed to assess temporal trends in periodontal disease incidence and prevalence. Age-Period-Cohort (APC) modeling was applied to disentangle independent age, period, and cohort effects. Bayesian Age-Period-Cohort (BAPC) analysis was utilized to project incidence and prevalence from 2022 to 2041.

Between 1992 and 2021, the incidence and prevalence of periodontal diseases in China exhibited an overall upward trend, with an annual increase of 0.18% in incidence and 0.30% in prevalence, and higher rates observed in males than females. The APC model revealed that net age effects were positive across all age groups, with net changes of 0.61%(95%CI: 0.43-0.80) for incidence and 0.98%(95%CI: 0.81-1.15) for prevalence, showing an initial increase followed by a decline and subsequent rise. The highest incidence occurred in the 50-54 age group, while the highest prevalence was observed in the 60-64 age group. Using 2002-2006 as the reference period (RR=1), the risk of incidence and prevalence began to rise continuously around 2007, peaking at RR=1.04 (95%CI: 0.99-1.09) and RR=1.09 (95%CI: 1.05-1.13), respectively. For the birth cohort, using 1953—1957 as the reference (RR=1), the 1998-2002 birth cohort exhibited the highest risks for both incidence (RR=1.80, 95%CI: 1.14-2.84) and prevalence (RR=1.87, 95%CI: 1.01-3.46). Predictions indicated that the incidence and prevalence of periodontal diseases in China will continue to rise over the next 20 years.

China has experienced escalating periodontal disease burden since 1992, with marked age-dependent heterogeneity. Without effective interventions, incidence and prevalence are expected to rise rapidly through 2041, highlighting the need for heightened attention to its disease burden in public health planning.

To construct a machine learning model based on Insulin-like Growth Factor-1 (IGF-1) and Growth Differentiation Factor-8 (GDF-8, Myostatin) for predicting sarcopenia in lung cancer patients, with the aim of improving early detection and diagnostic capabilities, providing personalized nutrition and treatment recommendations, and enhancing patients’ health status and prognosis.

A total of 263 primary lung cancer patients hospitalized at Karamay Central Hospital between October 2023 and July 2024 were selected as research subjects. Data on gender, age, BMI, IGF-1, GDF-8, interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and other variables were collected. Patients were divided into a sarcopenia group and a non-sarcopenia group according to the criteria established by the Asian Working Group for Sarcopenia (AWGSOP). Univariate analysis and LASSO regression analysis were used to identify risk factors for sarcopenia in primary lung cancer patients. The selected risk factors were incorporated into the K-nearest neighbors (KNN) algorithm model, Gaussian Naive Bayes (GNB), and binary logistic regression models, using the R software. Internal validation was performed using the Bootstrap method.

A total of 263 patients were investigated, with 137 in the sarcopenia group and 126 in the non-sarcopenia group. The sarcopenia group had significantly higher proportions of alcohol consumption, IL-4, IL-6, IL-17, TNF-α, GDF-8, blood urea nitrogen, and low-density lipoprotein, while BMI, smoking, PSQI score, IGF-1, and platelet count were significantly lower than those in the non-sarcopenia group (all P<0.05). The ROC curve showed that the C-index of the KNN model was 0.936, the C-index of the GNB model was 0.935, both significantly better than the binary logistic regression model’s C-index of 0.926. The Hosmer-Lemeshow goodness-of-fit test showed that the average prediction error between the predicted and actual values of the KNN model, GNB model, and binary logistic regression model were 0.026 9, 0.018 8, and 0.028 7, respectively, with the GNB model significantly outperforming the KNN model and the binary logistic regression model. The prediction results of the GNB model were highly consistent with the observed outcomes. DCA curves demonstrated that the GNB model outperformed both the KNN model and the binary logistic regression model in predicting sarcopenia risk in lung cancer patients.

High levels of IL-6, TNF-α, and GDF-8, low levels of IGF-1 and albumin, poor sleep quality, and low BMI are independent risk factors for sarcopenia in lung cancer patients. The GNB prediction model constructed in this study significantly outperforms both the KNN model and the binary logistic regression model, providing precise and individualized predictions for sarcopenia risk in lung cancer patients. This model can offer personalized nutrition and treatment recommendations for clinical practice, improving patients’ health status and prognosis.