In Uganda, 1 in 4 girls has been pregnant by 18 years. This was worse during the COVID 19 pandemic. We determined risk factors for pregnancy among rural and urban dwelling adolescents in Uganda.

We conducted a mixed-methods study among girls aged 13 to 19 years in a rural and urban district in Uganda. Quantitatively, we used an unmatched case control design involving 200 adolescents with pregnancy experience and 400 controls with no pregnancy experience. Quantitative data was analyzed using STATA version 14. Qualitative methods included 17 focus group discussions, 10 in-depth interviews and 20 key informant interviews with key stakeholders. Transcribed audio recordings were analyzed using a content thematic approach using Nvivo.

Of the 600 girls, mean age was 16.9 years (SD 3.84). Independent risk factors for pregnancy were age, out-of-school, a friend with teenage pregnancy, cigarette smoking, working for money and correct contraceptive knowledge. Protective factors included positive personal attitudes, father's education and larger household size. Qualitatively, inadequate information on sexual and reproductive health, early sexual debut, alcohol and drug abuse, absence of parental supervision, negative peer influence and poverty were reported.

Overall, individual characteristics, behaviors and inadequate information increased the risk of pregnancy.

Artemisia pollen is a major airborne allergen in northern China; however, the relative contributions of environmental pollen exposure and host susceptibility to allergic disease remain unclear in high-exposure regions.

A population-based cross-sectional study was conducted in Yulin City, China, involving 12,345 participants recruited through multistage stratified cluster sampling. Serum Artemisia-specific IgE was measured in 3,130 participants. Disease status was classified into healthy, sensitized, allergic rhinitis, and acute asthma exacerbation groups. Regional pollen exposure was categorized into low, medium, and high levels based on monitoring data. Inverse probability weighting was applied to reduce selection bias. Multivariable logistic regression models were used to assess associations.

The IPW-adjusted prevalence of Artemisia sensitization, allergic rhinitis, and acute asthma exacerbations was 13.0%, 10.7%, and 1.9%, respectively. Regional pollen concentration was not significantly associated with sensitization or disease outcomes in adjusted models (all P > 0.05). In contrast, host-related factors, including family history of allergy and Artemisia-specific IgE levels, showed consistent associations across disease stages. Family history of allergy was strongly associated with sensitization (OR = 4.57, 95% CI: 3.01-6.95). Increasing Artemisia-specific IgE levels were associated with higher odds of progression from sensitization to clinical disease and from rhinitis to acute asthma exacerbation.

In this high-exposure population, host susceptibility factors demonstrated stronger and more consistent statistical associations with Artemisia-related allergic disease than regional pollen concentration. These findings suggest that host heterogeneity may contribute importantly to disease variability in high-exposure environments; however, causal inference is limited by the cross-sectional design and exposure measurement constraints.

Asthma is one of the most prominent chronic diseases in children and one of the most challenging ailments to diagnose in infants and preschoolers in the United States. Predictive models can be instrumental in improving early diagnosis, personalized treatment strategies, and disease progression. By utilizing nationalized data, this study focuses on building and comparing high-performing analytical predictive models based on the relevant risk factors and identifying the most influential predictors.

We analyzed cross-sectional BRFSS Asthma Call-Back Survey data (2011-2020; N = 9,813) and randomly split participants into training and testing sets. An XGBoost model (hyperparameters tuned via grid search) was developed and compared with SVM, random forest, LASSO, and GBM using accuracy, AUC, precision, and recall. Calibration was evaluated with reliability plots and improved using Platt scaling and isotonic regression. Predictor contributions were examined using variable-importance (VIP) and Shapley Additive Explanations (SHAP) plot.

Of the five predictive models, the XGBoost was found to be the best performing model with AUC: 0.95, followed by random forest (AUC: 0.9345), GBM (AUC: 0.9341), SVM (AUC 0.9304), and LASSO (AUC 0.88); however, the random forest model was found to have the highest sensitivity (0.9786), and hence preferred for initial screening of asthma. On the independent test set, calibration (10-bin reliability curves; Brier/ECE/intercept-slope) improved most with isotonic regression, specifically for Random Forest (ECE 0.0158 to 0.0086; intercept -0.174 to -0.010), whereas Platt scaling often worsened calibration, with AUC remaining largely stable across models (AUC ≈ 0.92-0.95). The top two contributing predictors were overnight hospitalization visits and time since the last asthma medication, accounting for 24.62 and 20.92%, respectively, of the asthma status, from the VIP.

The analytical methodology of model development was found to be instrumental in the discovery of behavioral health-risk knowledge and to visualize the significance of predictive modeling from a multidimensional behavioral health survey. These insights can be instrumental in predicting different types of chronic lung diseases affecting people of all ages and can be useful for clinicians to diagnose asthma at an early stage, allowing for early intervention and proactive management.

How to increase the diagnosis rate of pulmonary tuberculosis (PTB) has always been a major challenge in medicine. Compared with conventional microbiological tests (CMTs), nanopore targeted sequencing (NTS) is undoubtedly a faster and more effective diagnostic method. This study explores the feasibility of combining chest CT imaging screening with NTS to improve PTB diagnosis.

This retrospective observational study was conducted from March 2023 to December 2024, enrolling 380 patients from a single center who underwent bronchoalveolar lavage fluid (BALF) analysis and NTS testing. We compared the diagnostic accuracy of radiologists with varying experience levels to determine the most suitable preliminary screening protocol for PTB. Additionally, we compared NTS results with CMTs (including mycobacterial culture, acid-fast bacilli smear and Xpert MTB/RIF) to evaluate differences in diagnostic performance between NTS and CMTs.

We conducted a horizontal comparison of PTB diagnostic accuracy among three radiologists with different levels of experience. The most experienced radiologist had the lowest missed diagnosis rate. When combining cases suspected by all three radiologists (202 cases), the missed diagnosis rate dropped to as low as 9.09% (27.27% [95% CI: 16.77-40.70%] vs. 30.91% [95% CI: 19.73-44.51%] vs. 16.36% [95% CI: 8.38-29.82%] vs. 9.09% [95% CI: 3.80-19.84%], p = 0.019). Furthermore, we analyzed the diagnostic performance of NTS and CMTs in PTB patients and found that NTS had significantly higher sensitivity than Xpert MTB/RIF, mycobacterial culture, and acid-fast bacilli smear (89.09% [95% CI: 78.17-95.02%] vs. 78.18% [95% CI: 65.44-87.12%] vs. 23.64% [95% CI: 13.99-36.99%] vs. 16.36% [95% CI: 8.38-28.82%], p < 0.001). ROC analysis demonstrated that incorporating NTS into the testing of suspected PTB specimens significantly improved diagnostic capability (AUC = 0.990, 95% CI: 0.968-1.000).

Radiologists' experience in PTB imaging diagnosis can reduce missed diagnoses. Additionally, combining NTS with CMTs helps improve early diagnosis in suspected PTB patients. The combined use of NTS and Xpert MTB/RIF yielded the highest diagnostic accuracy (AUC 0.990).

Cardiometabolic disorders contribute significantly to global cardiovascular disease risk. COVID-19 can exacerbate underlying vascular and metabolic disturbances through immune and inflammatory pathways. Lipoprotein abnormalities may influence disease susceptibility and outcomes, as lipoproteins play key roles in viral entry, inflammation and immune regulation. These markers may therefore serve as potential biomarkers for predicting outcomes, yet data from African populations remain limited.

To determine the association between admission lipid profiles and adverse clinical outcomes in hospitalised COVID-19 patients within a resource-constrained setting, in a predominantly black African population.

This retrospective observational study was conducted at Charlotte Maxeke Johannesburg Academic Hospital between 6 March and 31 August 2020. Adults aged ≥18 years with confirmed SARS-CoV-2 infection who had admission lipid profiles were included. The association between lipid parameters and adverse clinical outcomes, including intensive care unit (ICU) admission, mechanical ventilation, and in-hospital mortality, were determined by multivariable logistic regression analysis. Correlation analyses examined associations between lipids and inflammatory markers.

Among 305 patients (mean (standard deviation) age 53 (13.8) years; 77% black ethnicity), non-survivors had significantly lower low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC), and higher fasting plasma glucose and inflammatory markers. Both LDL-C and TC were inversely correlated with procalcitonin (ρ=-0.44, 95% confidence interval (CI) -0.65 - -0.23, p=0.001; (ρ=-0.28, CI-0.52 - -0.05), p=0.03, respectively). Triglyceride (TG) levels were higher in ICU patients (p=0.01), and significantly correlated with an increasing white cell count (ρ=0.31, CI 0.09 - 0.53, p=0.01), neutrophil-to-lymphocyte ratio (ρ=0.27, CI 0.01 - 0.54, p=0.04) and fasting plasma glucose (ρ=0.39, CI 0.14 - 0.64, p=0.03), but were not independently predictive of mortality. High-density lipoprotein cholesterol was lower in ICU-admitted patients and inversely correlated with ferritin, but it was also not significantly associated with mortality. Lower LDL-C was an independent predictor of ICU admission (odds ratio (OR) 0.69, CI 0.50 - 0.96, p=0.03 ), mechanical ventilation (OR 0.55, CI 0.35 - 0.86, p=0.009 ) and mortality (OR 0.66, CI 0.48 - 0.91, p=0.01), with an LDL-C <2.2 mmol/L associated with increased mortality(area under curve 0.62, CI 0.55 - 0.69), as shown in receiver operating characteristic analysis.

Non-survivors had significantly higher inflammatory markers compared with survivors, and low LDL-C and TC were independently associated with adverse outcomes. LDL-C also predicted ICU admission, mechanical ventilation and mortality, highlighting the link between lipid metabolism and immune response. These findings emphasise the need for further prospective studies to evaluate the utility of these markers as accessible prognostic tools in low- and middle-income countries.

Primary ciliary dyskinesia (PCD) is a genetically heterogeneous disorder, and despite advances in next-generation sequencing, a substantial proportion of clinically suspected pediatric cases remain without a molecular diagnosis. This persistent diagnostic gap reflects limitations of earlier analysis pipelines and incomplete knowledge of PCD-related genes. Reanalysis of existing whole-exome sequencing (WES) data using updated resources has become a practical strategy to improve diagnostic yield in pediatric populations.

We retrospectively reanalyzed WES data from 34 Turkish pediatric patients with clinical suspicion of PCD evaluated at a tertiary center between 2019 and 2023, all of whom had previously nondiagnostic genetic results. Reanalysis incorporated updated population and disease databases, curated ciliary gene resources, phenotype-driven variant interpretation, and copy number variant (CNV) assessment.

Molecular diagnoses were established in 3 of 34 patients (8.8%) through variants in known PCD genes, demonstrating the incremental value of systematic reanalysis enabled by detection of previously missed CNVs and updated literature evidence. In addition, rare variants in biologically plausible candidate genes were prioritized in 8 cases (23.5%), including genes involved in ciliary structure (RIBC1, NINL, DNAH14, SPMIP2), host defense pathways (USHBP1, CRYBG1, TRIM34), and laterality determination (WDR90).

Systematic WES reanalysis can identify missed molecular diagnoses and prioritize biologically relevant candidate genes in unresolved pediatric PCD cases, supporting future gene discovery and refinement of the genetic architecture of PCD, particularly in populations with high rates of consanguinity.

Bronchospasm requiring continuous inhaled albuterol is a common reason for pediatric intensive care unit (PICU) admission. Albuterol's racemic composition may contribute to adverse effects; therefore, levalbuterol [(R)-albuterol] may be used. This study aimed to determine if continuous inhaled levalbuterol is associated with a shorter duration of continuous inhaled bronchodilator therapy and less tachycardia compared to albuterol in PICU patients.

This study utilized two periods of exclusive continuous inhaled levalbuterol use due to an albuterol shortage. PICU encounters receiving ≥ 12 h of continuous inhaled levalbuterol during those periods were compared to encounters receiving albuterol in the interim. Therapy duration and % change in median heart rate (HR) at 6-h epochs were compared between groups, and multilevel mixed effects models were created.

In 686 encounters, there was no difference in therapy duration between levalbuterol and albuterol groups (31.3 vs. 28.7 h, p = 0.22). There was no difference in % change in median HR at 6 (-1.0% vs. -1.3%, p = 0.54), 12 (-1.6% vs. -2.7%, p = 0.28), or 18 h (-2.5% vs. -4.1%, p = 0.38) from therapy initiation. Levalbuterol was not associated with therapy duration adjusting for age, technology dependence, respiratory rate category, and number of continuous intravenous bronchodilators (p = 0.13). Levalbuterol was not associated with % change in median HR at 12 h following therapy initiation after adjusting for age and respiratory rate category (p = 0.99).

Continuous inhaled levalbuterol was not associated with shorter therapy duration or lower HR compared to albuterol in PICU patients.

To develop and validate a predictive model for post-COVID-19 pulmonary fibrosis (PCPF) by integrating CT radiomics features with clinical characteristics to facilitate early identification and intervention.

An observational study. Place and Duration of the Study: Department of Radiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China, from December 2022 to January 2023.

This study enrolled 223 patients with COVID-19. Chest CT images and clinical data of the participants during their hospitalisation were collected. Follow-up chest CT scans were performed 3-12 months post-discharge to assess for PCPF. Participants were randomly divided into a training set (n = 156) and a testing set (n = 67). Using the least absolute shrinkage and selection operator (LASSO) regression, six optimised radiomic features were identified, and radiomic scores were calculated (Rad-scores). Univariate and multivariate logistic regression analyses screened clinical features, identifying age, lesion location, length of hospital stay, and lactate dehydrogenase (LDH) as independent predictors. Subsequently, a radiomic model, a clinical model, and a combined nomogram model incorporating Rad-scores and clinical predictors were constructed.

The combined nomogram demonstrated superior prediction. In the testing set, the areas under the curve (AUC) were 0.833, outperforming the clinical (AUC = 0.687) and radiomic (AUC = 0.811) models. The DeLong test confirmed that the nomogram significantly outperformed the clinical model (p < 0.05). Calibration and decision curve analyses verified the nomogram's excellent fit and provided substantial clinical net benefit.

The nomogram model based on CT radiomics and clinical features is promising for predicting PCPF.

Computed tomography, COVID-19, Post COVID-19 pulmonary fibrosis, Radiomics, Nomogram.

To investigate the clinical characteristics of patients with saddle pulmonary embolism (SPE) among those with intermediate- to high-risk acute pulmonary embolism (APE).

A comparative study. Place and Duration of the Study: Department of Interventional Vascular Surgery, the First Hospital of Putian City, Putian, China, from May 2017 to October 2024.

Combined anticoagulation and interventional therapy was administered to all enrolled intermediate- to high-risk APE patients (with right ventricular dysfunction and/or elevated cardiac biomarkers, or haemodynamic instability) per the study protocol. Based on whether SPE was identified on computed tomography pulmonary angiography, patients were divided into the SPE group and the non-SPE group. Clinical characteristics, cardiac biomarkers, imaging features, and clinical outcomes were compared between the two groups.

When comparing the groups, no significant differences were observed in N-terminal pro-B-type natriuretic peptide, right ventricular diameter/left ventricular diameter, and peripheral pulmonary artery obstruction index before and after treatment (p >0.05). However, the SPE group had higher levels of cardiac troponin I than the non-SPE group before and after treatment (p <0.05). There was no significant difference in in-hospital mortality between the two groups (p = 0.653). In the SPE group, the saddle embolism resolved completely in 94.74% of patients after treatment.

Patients with SPE may experience more severe myocardial injury. The short-term resolution of the saddle embolism after treatment appears not to be a critical factor affecting treatment response.

Intermediate- to high-risk, Acute pulmonary embolism, Computed tomography pulmonary angiography, Saddle pulmonary embolism, Clinical characteristics.

The Nijmegen Questionnaire (NQ) is used to identify Dysfunctional Breathing (DB) in individuals with asthma. However, it has not been validated for use in children and adolescents.

This study aimed to validate a Swedish NQ for this population.

Participants aged 10-17 years with asthma were included (n = 124). In Cohort I (n = 22), audiotaped semi-structured interviews were conducted to adapt and refine the questionnaire analyzed by qualitative content analysis, resulting in NQ version 1. Forty-eight participants (11 from Cohort I, 37 new) then completed version 1 to assess internal redundancy, consistency (Spearman's Rho, Cronbach's alpha) and item clarity, leading to version 2. Cohort II (n = 60 new) completed NQ version 2 alongside the Paediatric Asthma Quality of Life Questionnaire (PAQLQ) and Childhood/Adult Asthma Control Test (cACT/ACT) to assess construct validity. Cohort III (n = 54, 48 from Cohort II, 6 new) completed NQ version 2 again after 2 weeks for test-retest reliability.

Content analysis prompted revisions for clarity and relevance. Internal redundancy ranged from r_s = 0.00-0.69 and internal consistency was 0.85 (Cronbach's alpha). The NQ correlated moderately with cACT/ACT (r_s = -0.54) and PAQLQ subscales Symptoms, Activity limitation and Emotional function, r_s -0.52, -0.48, -0.39 (CI 0.32;0.70, 0.24;0.66, 0.14;0.60) respectively. Test-retest reliability was 0.86 (Kw) (p < 0.0001).

The Swedish Paediatric NQ seems to be a valid and reliable tool for identifying DB in children and adolescents with asthma.