The World Health Organization predicts that by 2030, chronic obstructive pulmonary disease (COPD) will be the third leading cause of death and the seventh leading cause of morbidity worldwide. Pulmonary function tests (PFT) are the gold standard for COPD diagnosis. Since COPD is an incurable disease that takes a considerable amount of time to diagnose, even by an experienced specialist, it becomes important to provide an analysis of abnormalities in a simple manner. Although many deep learning (DL) methods based on computed tomography (CT) have been developed to identify COPD, the pathological changes of COPD based on CT are multi-dimensional and highly spatially heterogeneous, and their predictive performance still needs to be improved.

The purpose of this study was to develop a DL-based multimodal feature fusion model to accurately estimate PFT parameters from chest CT images and verify its performance.

In this retrospective study, participants underwent chest CT examination and PFT at the Fourth Clinical Medical College of Xinjiang Medical University between January 2018 and July 2024. In this study, the 1-s forced expiratory volume (FEV1), forced vital capacity (FVC), 1-s forced expiratory volume ratio forced vital capacity (FEV1/FVC), 1-s forced expiratory volume to predicted value (FEV1%), and forced vital capacity to predicted value (FVC%) of PFT parameters were used as predictors and the corresponding chest CT of 3108 participants. The data were randomly assigned to the training group and the validation group at a ratio of 9:1, and the model was cross-validated using 10-fold cross-validation. Each parameter was trained and evaluated separately on the DL network. The mean absolute error (MAE), mean squared error (MSE), and Pearson correlation coefficient (r) were used as evaluation indices, and the consistency between the predicted and actual values was analyzed using the Bland-Altman plot. The interpretability of the model's prediction process was analyzed using the Grad-CAM visualization technique.

A total of 2408 subjects were included (average age 66 ± 12 years; 1479 males). Among these, 822 cases were used for encoder training to extract image features, and 1,586 cases were used for the development and validation of a multimodal feature fusion model based on a multilayer perceptron (MLP). The MAE, MSE, and r predicted between PFT and model estimates for FEV1 were 0.34, 0.20, and 0.84, respectively. For FVC, the MAE, MSE, and r were 0.42, 0.31, and 0.81, respectively. For FEV1/FVC, the MAE, MSE, and r were 6.64, 0.73, and 0.77, respectively. For FEV1%, the MAE, MSE, and r were 13.42, 3.01, and 0.73, respectively. For FVC%, the MAE, MSE, and r were 13.33, 2.97, and 0.61, respectively. It was observed that there was a strong correlation between the measured and predicted indices of FEV1, FVC, FEV1/FVC, and FEV1%. The Bland-Altman plot analysis showed good consistency between the estimated values and the measured values of all PFT parameters.

The preliminary research results indicate that the MLP-based multimodal feature fusion model has the potential to predict PFT parameters in COPD patients in real time. However, it is worth noting that the study used indicators before the use of bronchodilators, which may affect the interpretation of the results. Future studies should use measurements taken after bronchodilator administration to better align with clinical standards.

Obstructive sleep apnea (OSA) has been linked to adverse cardiovascular outcomes, but its role as a risk factor for sudden cardiac death (SCD) remains uncertain. This systematic review and meta-analysis aimed to evaluate the association between OSA and SCD and assess the influence of disease severity and treatment.

A comprehensive search of PubMed, Scopus, Web of Science, and Google Scholar was conducted up to January 17, 2025. We included observational studies reporting the association between OSA and SCD. Data were pooled using a random-effects model. Subgroup analyses were performed based on apnea-hypopnea index (AHI) and CPAP treatment. A separate meta-analysis examined adjusted odds ratios (aORs). Heterogeneity was assessed using the I² statistic, and publication bias was evaluated via funnel and Galbraith plots.

Twelve studies (527,069 participants: 18,084 OSA, 508,985 non-OSA) were included. The pooled odds ratio for SCD in OSA patients was 1.41 (95% CI: 0.91-2.16; p = 0.12), with high heterogeneity (I² = 79.3%). Subgroup analysis showed increased risk in untreated OSA (OR = 3.87; 95% CI: 1.09-13.81; p = 0.04), but not in those receiving CPAP. Adjusted estimates showed no significant association (aOR = 0.90; 95% CI: 0.17-1.98; p = 0.10), with high heterogeneity (I² = 95.9%). Sensitivity analyses indicated moderate result stability; however, potential publication bias was observed.

Available evidence is insufficient to establish a definitive association between OSA and SCD. Some subgroup analyses suggest an elevated risk in untreated OSA, but overall findings are heterogeneous and limited by study design.

Not applicable.

The COVID-19 pandemic has yielded substantial evidence indicating that SARS-CoV-2 may impair reproductive function, particularly by adversely affecting sperm quality. Given the potential implications for male reproductive health, it is crucial to assess the reversibility of such damage, determine the precise recovery timeline, and evaluate post-infection health parameters. Male patients who had undergone sperm analysis prior to SARS-CoV-2 infection were enrolled to evaluate longitudinal changes in sperm quality during a 6-month recovery period. Sperm parameters were collected at five consecutive time points: before infection and at 1, 2, 3, 6 months post-infection. Additionally, quality of life (QoL), psychological status, and sexual function were evaluated via standardized questionnaires within the first month after infection. The primary outcomes were sperm concentration and progressive motility. Generalized Estimating Equations (GEE) were applied for statistical analysis of repeated measures, while Kaplan-Meier survival analysis was used to assess temporal trends in sperm recovery. 1009 subjects underwent sperm analysis during widespread COVID-19 transmission, from April 2022 to January 2023. Among them, 139 eligible patients completed sperm analysis in the first month post-infection, with 92 (66%) patients were tested in the second month, 72 (52%) patients in the third month, and 64 (46%) patients completed the sperm analysis in the sixth month. The final analytical cohort comprised 74 participants with complete pre-infection baselines and ≥ 3 post-COVID-19 semen analyses at specified intervals (1, 2, 3, 6 months). Sperm concentration [39.22 (95% CI 32.02-46.41)] and progressive motility [36.41 (95% CI 32.29-40.53)] showed a significant decline at 1-month post-infection compared to pre-infection levels. Partial recovery occurred during the second and third months, though values remained significantly lower than baseline pre-infection levels at 6-month follow-up (p < 0.05). Kaplan-Meier analysis estimated median recovery times of 5 months (95% CI 4.57-5.43) for sperm concentration and 3 months (95% CI 2.08-3.82) for progressive motility, with no age-dependent differences observed (log-rank p > 0.05). Comprehensive assessments showed preserved psychological status, quality of life, and urogenital function at 1-month post-infection. Sperm quality was negatively impacted by COVID-19 infection, but temporary, with a recovery period of 3-5 months. Furthermore, no abnormalities were observed in men's psychological, urinary symptoms, or sexual function during the initial month following recovery from infection.

This study aimed to analyze the epidemiological characteristics of severe Mycoplasma pneumoniae in the pediatric intensive care unit (PICU) of Hunan Children's Hospital from 2020 to 2023. This study investigated the epidemiological patterns related to different years, seasons, ages, and sexes, as well as the correlations of PM_2.5, PM₁₀, and NO₂ concentrations, temperature, and humidity with severe Mycoplasma pneumoniae. The goal is to increase awareness of the prevention and control of severe Mycoplasma pneumoniae in the Changsha region, thereby improving clinical outcomes, reducing mortality rates among patients with severe cases, and providing evidence-based guidance for clinical practice. A retrospective analysis was conducted on children diagnosed with severe Mycoplasma pneumoniae in the PICU of Hunan Children's Hospital from January 2020 to December 2023. The study compared the positivity rates of Mycoplasma infections across different years, seasons, age groups, and sexes. The correlations between PM_2.5 (µg/m³), PM₁₀ (µg/m³), NO₂ (µg/m³), average temperature (°C), and average relative humidity (%) and the number of cases of severe Mycoplasma pneumoniae were also analyzed. Among 2,047 children with severe pneumonia, the overall MP-IgM positivity rate was 9.5%. Annual positivity rates increased from 6.3% in 2020 to 15.7% in 2023. Rates were highest in summer (15.8%), and preschool children (3-7 years) showed the greatest positivity (30.0%). At pollutant concentrations above thresholds (PM_2.5 ≥35 µg/m³, PM₁₀ ≥ 50 µg/m³, NO₂ ≥ 25 µg/m³), moderate positive correlations with severe cases were found, with risk ratios of 1.28, 1.31, and 2.04 per 10 µg/m³ increase, respectively. The positivity rate and number of cases of severe Mycoplasma pneumoniae in the PICU tended to increase from 2020 to 2023. The condition was most prevalent in summer and among preschool-aged children. When the PM_2.5 concentration was ≥ 35 µg/m³ or the PM₁₀ concentration was ≥ 50 µg/m³, moderate positive correlations were observed between the PM_2.5 and PM₁₀ concentrations and the number of severe Mycoplasma pneumoniae cases.

SARS-CoV-2 Omicron variant evolved into multiple sub-lineages, some showing increased transmissibility and immune evasion. Despite decreased risk of severe disease, paediatric hospitalization rose. However, factors influencing clinical outcomes remain unclear. A total of 458 whole-genome Omicron sequences from patients 0-17 years, diagnosed with SARS-CoV-2 at Bambino Gesù Children's Hospital (January-December 2023) were analysed. Clinical features, disease severity and circulating variants were assessed. Phylogenetic analysis was performed, and logistic regression identified factors associated with hospitalization. Among patients, 249 (54.4%) were male, with median age 0.6 years. Comorbidities were present in 105 (22.9%) patients, mainly immunocompromised (21.0%). Infections were predominantly from XBB (75.0%), JN.1 (12.4%), BA.5 (7.4%) and BA.2 (5.2%) clades. Upper respiratory infections predominated (73.8%), followed by asymptomatic (17.2%) and lower respiratory infections (4.6%), with nine patients having ≥ 1 co-infection. Comorbidities and lower respiratory infections were positively associated with hospitalization, while upper respiratory infections showed a negative association. Given the recent shift to RGN integrin-binding motif in Omicron sub-lineages, leading to altered pathogenesis, its presence was evaluated, revealing a predominance of RGN (N = 378, 84.6%). In conclusion, COVID-19 severity in paediatric patients was primarily driven by comorbidities and co-infections, while milder cases in healthy children may be associated with RGN integrin-binding motif.

Childhood obesity is a growing public health concern globally and in China, with long-term health and economic consequences. Evidence suggests that early life, particularly the first 1000 days, is a critical window for obesity prevention. This study aimed to assess the prevalence, temporal trends, and associated risk factors of obesity among children under three years of age in Shaanxi province from 2012 to 2024. Data were obtained from the national children's nutrition and health surveillance system (NCNHSS), a population-based registry covering urban and rural sites in Shaanxi. A total of 8201 children aged 0-3 years were included. Anthropometric and sociodemographic data were collected through standardized physical examinations and caregiver interviews. Temporal trends were analyzed using Joinpoint regression. Multivariable logistic regression was used to identify risk factors for obesity at 36 months. The overall obesity prevalence at 36 months was 1.91%, with a fluctuating trend between 2012 and 2024. A significant decline was observed in rural areas, followed by a temporary increase in 2021, coinciding with the COVID-19 pandemic, and a subsequent reduction. In contrast, urban children exhibited a modest upward trend. Most children classified as obese at 36 months had already become overweight or obese by 18 months. Low socioeconomic status was strongly associated with increased obesity risk in both rural (AOR = 2.15; 95% CI 1.54-2.99) and urban settings (AOR = 1.83; 95% CI 1.29-2.60). In rural areas, children whose mothers worked in agriculture had significantly higher odds of obesity (AOR = 2.30; 95% CI 1.23-4.30), as did those born small for gestational age (AOR = 1.63; 95% CI 1.02-2.60). Among urban children, prolonged breastfeeding without appropriate complementary feeding was associated with increased obesity risk (AOR = 1.41; 95% CI 1.01-1.99). Although obesity prevalence among children in Shaanxi remains relatively low, early onset and socioeconomic disparities persist. Targeted interventions during the first 1000 days, particularly for low-income and high-risk families, are essential. Policies should focus on nutrition education, support for appropriate infant feeding, and early growth monitoring to prevent obesity in early childhood and reduce long-term health risks.

Postoperative pneumonia (POP) is a prevalent, severe complication in elderly noncardiac surgical patients, linked to extended hospital stays, increased healthcare costs, and higher mortality. Existing predictive models are often limited by single-center data, small cohorts, or restricted variables, highlighting the need for a comprehensive tool integrating multi-phase perioperative factors. This retrospective study analyzed 44,740 patients aged ≥ 65 years who underwent noncardiac surgery (November 2014-April 2022) at Henan Provincial People's Hospital, with 3187 (7.1%) developing POP. Patients were stratified into development (n = 31,320) and validation (n = 13,420) cohorts via 70:30 random split. Key predictors were identified using LASSO logistic regression (from 44 candidates), followed by multivariate logistic regression with forward stepwise selection. Model performance was evaluated via AUC (discrimination), calibration (Hosmer-Lemeshow test, Brier score), clinical utility (decision curve analysis [DCA]), and interpretability (SHAP analysis). The final model included 9 predictors: anesthesia duration, anesthesia type, smoking status, pulmonary disease history, intraoperative colloid volume, preoperative anticoagulant/antihypertensive/steroid use, and intraoperative sufentanil dose. It demonstrated strong discrimination (validation AUC = 0.804, 95% CI 0.790-0.818) and good calibration (development: Hosmer-Lemeshow χ² = 5.45, P = 0.79; validation: χ² = 7.81, P = 0.55; Brier score = 0.058 for both). A derived nomogram (optimal cutoff = 190) showed high sensitivity (76.3%) and specificity (69.6%). DCA confirmed net benefit across 0-89% (development) and 0-88% (validation) thresholds. SHAP analysis identified prolonged anesthesia and pulmonary disease history as top predictors. This multifactorial model reliably predicts postoperative pneumonia in elderly noncardiac surgical patients using routinely collected perioperative data, with good discrimination and calibration. By integrating a wider range of variables than prior models, it enhances predictive accuracy and clinical applicability. External validation in multicenter prospective cohorts is needed to confirm its generalizability and support clinical integration.

Asthma is associated with both airway and systemic inflammation as well as non-respiratory adverse outcomes. However, data regarding its impact on long-term renal outcomes is lacking. We classified all asthma patients who were followed at Queen Mary Hospital in 2017 into eosinophilic or non-eosinophilic phenotypes based on their highest blood eosinophil counts (BEC) during stable state in the year (≥ 300 or < 300 cells/mm³ respectively) and prospectively evaluated their clinical outcomes in the subsequent 5 years. The relationship between patient phenotypes and the long-term renal outcomes were assessed. Five hundred and four asthma patients with baseline Stage 1 to 3 chronic kidney disease were included [296 (58.7%) and 208 (41.3%) in eosinophilic and non-eosinophilic groups respectively]. Among patients with baseline renal function at CKD stage 1 to 3, one hundred and four patients (20.6%) had renal progression in this cohort (56 patients (26.9%) vs. 48 patients (16.2%) in the non-eosinophilic and eosinophilic groups respectively). Patients with non-eosinophilic asthma showed increased risks of renal progression over 5 years of follow-up [adjusted odds ratio (aOR) 2.615, 95% CI 1.151-5.942 p = 0.022] and more rapid eGFR decline (-4.29 ± 3.48 mL/min/1.73m²/year vs. -3.48 ± 3.07 mL/min/1.73m²/year, p = 0.007) than those with eosinophilic phenotype. Patients who developed renal progression had higher risk of death [adjusted hazard ratio (aHR) 1.614 (95% CI 1.041-2.502); p = 0.032]. Progressive renal function deterioration is prevalent amongst asthma patients, and those with non-eosinophilic phenotype are at risk of renal progression.

Bronchiolitis is associated with asthma persisting until adulthood. While bronchial hyper-reactivity (BHR) is a hallmark of asthma, its occurrence and characteristics after bronchiolitis have been less studied. We aimed to study if BHR differed between young adults hospitalised for bronchiolitis in infancy and control subjects with no such history. Further, we sought to study whether any association between asthma and BHR differed between these two groups.

This Norwegian historical cohort study included 186 young adults hospitalised for respiratory syncytial virus positive or negative bronchiolitis in infancy during 1996-2001 and 139 matched control subjects. BHR was assessed at 17-20 years by methacholine provocation tests and recorded as dose-response slopes (DRS). Outcomes were analysed by mixed effects regression models.

DRS was higher in the post-bronchiolitis group than in the control group (regression coefficient (β) 0.37; 95% CI 0.01 to 0.73; p=0.045). In both groups combined, current asthma was positively associated with DRS (β 0.98; 95% CI 0.50 to 1.45; p<0.001). Stratified analyses showed that the effect (β) of asthma on BHR was 0.80 (95% CI 0.21 to 1.38; p=0.008) in the post-bronchiolitis group and 1.40 (95% CI 0.58 to 2.23; p=0.001) in the control group. The difference in the association between asthma and BHR across the two groups was not statistically significant (p=0.191 for interaction).

BHR at age 17-20 years was higher in subjects hospitalised for bronchiolitis in infancy than in control subjects. The association between asthma and BHR was not found to differ between the post-bronchiolitis group and the control group, although a possible stronger association in the control group may warrant further study.

Antibiotics are widely used to manage acute asthma exacerbations, despite little evidence for their effectiveness. This study assesses the added value of antibiotics alongside oral corticosteroids (OCSs) in treating asthma exacerbations.

This retrospective cohort study included individuals from the Netherlands between 1994 and 2022 from the IADB.nl pharmacy dispensing database. Individuals had to be 16-45 years old, use inhaled asthma medication and have a first recorded prednisone/prednisolone (OCS) dispense of ≥30 mg/day for 3-14 days. Patients were compared regarding treatment failure (a new dispense of OCS or antibiotics, 15-30 days after initial dispense), based on whether or not they were dispensed antibiotics (AB) alongside their first recorded OCS dispense. Regression analyses with inverse probability of treatment weighting were used to adjust for various confounders.

Of the 5401 individuals included, 38% received antibiotics alongside the first-recorded OCS dispense, with a decreasing trend from 47% in 2009 to 24% in 2020. The OR for treatment failure was 1.36 (95% CI 0.81 to 2.16) for AB+OCS versus OCS-only. The HR for a new exacerbation within 31-365 days of follow-up was 1.20 (95% CI 0.92 to 1.56) for AB+OCS versus OCS-only. The lack of beneficial effect of AB was consistent across subcohorts.

This study found no reduction in treatment failure, nor in risk of subsequent exacerbation, from adding AB to OCS for treating acute asthma exacerbations. We suggest that antibiotics should not be used in primary care settings to treat acute asthma exacerbation unless there are clear signs of bacterial infection.