Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease associated with high morbidity and mortality despite specific anti-fibrotic therapies. Management of IPF is complex and relies on pulmonary function tests (PFT) to evaluate severity and monitor progression. CT provides non-invasive morphologic assessment and emerging software techniques enable quantitative analysis.

We included 319 individuals with IPF from the OSIC dataset. A cross-sectional analysis was made for all patients, with a longitudinal evaluation for 143 of them. We used LungQ software (Thirona, The Netherlands) to quantify lung and pulmonary vessel volumes, as well as the extent of interstitial lung disease and to assess correlation with PFT and mortality.

Quantitative extent of fibrotic abnormalities was correlated with baseline FVC and DLCO (r -0.47, p < 0.0001 and r -0.55, p < 0.0001 respectively) and longitudinal modifications over time (r -0.48, p < 0.0001 and r-0.43 p < 0.0001, respectively). Median baseline extent of ILD, expressed as a percentage of lung volume, was 16.5% (10.8-25.5) and increased to 17.3% (11.6-29) on follow-up (p < 0.001). The median ILD progression was of 9.8% (-9.5-40.0). Vascular enlargement quantification as well as ILD quantification were predictive marker of death (p < 0.0001). However, vascular abnormalities' independent predictive value could not be assessed in multivariate models due to multicollinearity with other variables.

LungQ allows to quantify interstitial and vascular lung features and their changes over time in a large cohort of patients with IPF. Imaging markers were negatively correlated with PFT at baseline and follow-ups were predictive of mortality confirming their potential as disease quantifiers. Further clinical validation is needed to specify the potential clinical use.

Obstructive respiratory conditions, including asthma, bronchiectasis, and chronic obstructive pulmonary disease (COPD), are increasingly recognised as heterogeneous syndromes with significant overlap. Multiple disease pathways contribute to phenotypes that do not always align with textbook definitions, limiting the effectiveness of a one-size-fits-all approach. This study aims to identify, validate, and characterise clinically meaningful airway disease subtypes using electronic healthcare records (EHR) and unsupervised machine learning clustering techniques.

We applied k-means clustering to 626,651 patients with a diagnosis of asthma, bronchiectasis, or COPD, using linked national structured EHRs in England. Twenty-one clinical features, including risk factors and comorbidities, were analysed, with dimensionality reduction via principal component and multiple correspondence analyses. Associations between cluster membership and exacerbations, as well as respiratory and cardiovascular mortality, were assessed. Over 3,696,962 person-years of follow-up, 102,522 deaths were recorded. Cluster stability was evaluated after five years, and genome-wide association studies (GWAS) were conducted to explore genetic associations with cluster membership.

Seven clusters were identified, each encompassing patients across traditional diagnostic labels. Distinct clinical patterns emerged as follows: (1) High BMI female predominant, (2) Older male-predominant with diabetes and cardiovascular disease, (3) Eosinophilic atopic, (4) Older non-comorbid, (5) Non-comorbid low BMI, (6) Neutrophilic smoker, (7) Anxious/depressed female-predominant.The cluster with cardiovascular comorbidities showed the highest rates of hospital admissions for exacerbations. Neutrophilic cluster 6 is a potential novel subtype marked by persistent neutrophilia and poor outcomes. Cluster stability over five years ranged from 38% to 78%. GWAS revealed significant genetic loci in a cluster enriched for allergic disease and eosinophilia, suggesting shared genetic mechanisms.

This study provides a data-driven dissection of the heterogeneity underlying obstructive airway diseases in a large, real-world population. Unsupervised machine learning applied to national-scale EHR data revealed distinct and partially stable subtypes that transcend conventional diagnostic boundaries. These findings highlight the complexity and overlap of airway disease phenotypes and demonstrate the value of clustering approaches for uncovering clinically and biologically meaningful subgroups. This work lays the foundation for further exploration into mechanisms and prognosis within and across airway disease phenotypes.

After neonatal conditions, the leading causes of child mortality in sub-Saharan Africa are malaria, lower respiratory infections, and dehydration. Many of these deaths could be averted with basic and widely-available health interventions, but quality of care remains low. We aimed to assess adherence to clinical guidelines for these conditions in Burundi, the Democratic Republic of the Congo (DRC), and Nigeria, and estimate the proportion of guideline non-adherence that is explained by gaps in health care provider knowledge versus other factors.

We conducted an observational study in randomly-sampled health facilities in each study country, linking data from direct observations of under-5 sick child visits, knowledge assessments of the treating health care providers, and interviews with caregivers. For children diagnosed with malaria, severe respiratory infection, or dehydration, we defined the "adherence gap" as the percentage who did not receive correct treatment, and the "know-do gap" as the percentage who received incorrect care despite the provider knowing the correct treatment. We evaluated the portions of overall adherence gaps that were explained by know-do gaps, and described factors associated with know-do gaps.

A total of 2,212 sick child visits treated by 852 providers were analyzed. In the pooled sample, 87%, 75%, and 77% percent of providers were familiar with the main treatment recommendations for malaria, pneumonia, and dehydration, respectively. When observed by survey staff during consultations with sick children, compliance with the same guidelines was 76%, 74%, and 51%. Knowledge gaps explained between 0% of the total adherence gap for pneumonia treatment in Burundi and 40% of the gap for pneumonia treatment in the DRC.

To improve quality of care, it is critical to understand why providers do not consistently follow clinical guidelines. Our findings suggest that adherence to protocols is low, but that knowledge is not the primary barrier. Interventions to improve quality must go beyond improving knowledge to also address other drivers of provider behavior such as motivation, workload, and systemic constraints.

The reported annual incidence of pertussis in China has shown a marked increase over the past decade, but it may be still underestimated. The purpose of this study was to understand the seroepidemiologic characteristics of pertussis in community-based populations and to assess the level of pertussis infection in the population.

Between 2017 and 2023, one or two cities in each of the eastern, central and western regions of Shandong Province were selected as survey sites, and a total of six age groups of healthy individuals were enrolled by multistage stratified random sampling to carry out the survey. The serum level of pertussis toxin (PT) IgG antibody was quantified by indirect enzyme-linked immunosorbent assay.

A total of 9,238 subjects were enrolled, and the mean positive rate of PT-IgG antibody was 8.05% (95%CI: 7.50%~8.60%), with the highest in 2019 (10.70%, 95% CI: 9.19%~12.21%) and the lowest in 2020 (6.32%, 95% CI: 4.98%~7.66%). The highest positive rate was found in the age group of less than 3 years old (11.46%, 95%CI: 9.87%~13.05%), and the lowest rate was found in the 3 ~ 5 years group (5.40%, 95%CI: 4.28%~6.52%). There was a significant difference in the positive rate between age groups (χ² = 43.098, p < 0.001). Comparison of trends in recent infection rates and reported incidence rates in the population, that showed a very strong linear correlation in the annual distribution (r = 0.821, p = 0.023), and an extremely weak linear correlation in age distribution (r = 0.086, p = 0.872). Estimated infection rates (/100,000) among people aged ≥ 3 years ranged from 5,257 (95%CI: 3,918 ~ 6,596) to 24,449 (95%CI: 22,157 ~ 26,740) by years, with estimated infection rates in eastern region (31,544.44-fold) and in older age group (292,340.00-fold for ≥ 20 years old group, 216,388.89-fold for 17 ~ 19 years old group) differed significantly from the reported incidence rate.

The annual distribution trend of reported pertussis incidence rate aligns with the infection rate observed among community populations, the actual level of infection is likely to be seriously underestimated. Therefore there is a need to emphasize surveillance and consider additional booster immunizations for adolescents and adults.

The COVID-19 pandemic has influenced violence against women worldwide, but its impact on female homicides in low- and middle-income countries remains poorly understood. Brazil, which records some of the highest female homicide rates globally, provides a critical setting to examine this association. This study assessed the temporal association between the pandemic and monthly female homicide rates in Brazil from January 2017 to December 2022.

We applied an interrupted time series (ITS) design with quasi-Poisson regression to estimate changes in homicide levels and trends after the pandemic onset, adjusting for serial autocorrelation and seasonality. Pre-pandemic trend linearity was tested, and sensitivity and placebo analyses were performed. To address underreporting and deaths classified as undetermined intent, homicide counts were corrected for misclassification.

From 2017 to 2022, 23,727 female homicides were recorded, corresponding to an adjusted mortality rate of 5.09 per 100,000 women, a 16.0% increase after correction. Rates were highest in the North and Northeast. Domestic homicides exceeded those in public spaces (1.50 vs. 1.37 per 100,000 women), and firearms were the predominant method. The Northeast showed a significant level change with an abrupt increase (RR = 1.236; p = 0.002), followed by a progressive decline (RR = 0.9923; p < 0.001). In other regions, across age groups, and in blunt-related cases, no significant level change occurred (p > 0.05), although downward trends emerged during the pandemic (p < 0.05).

Findings warrant cautious interpretation due to ITS constraints, sensitivity to the observation window, and omitted variables. Nonetheless, persistently high female homicide rates in Brazil, particularly in the Northeast, highlight the need to strengthen mortality surveillance, improve misclassification corrections, and adopt region-specific prevention strategies, including firearm control, protective services, and targeted social policies.

Critically ill children are vulnerable to fluid overload due to complex fluid management. Early positive fluid balance may lead to systemic venous and pulmonary congestion, which can be challenging to detect clinically. Venous excess ultrasound (VExUS) and lung ultrasound (LUS) are emerging point-of-care tools to assess these complications. In adults, VExUS is classified into five grades (A-E) based on Doppler flow patterns. However, evidence on the use of VExUS, particularly in combination with LUS, in critically ill children with fluid overload is scarce, and their clinical utility in this setting is yet to be established.

To evaluate the correlation between positive fluid balance and VExUS and LUS scores in critically ill children.

A cross-sectional study was conducted in the pediatric intensive care unit (PICU) of Dr. Cipto Mangunkusumo Hospital, from November to December 2024. The study included critically ill children aged 1 month to 18 years with a positive fluid balance within the first 24 h of admission. Correlations between VExUS and LUS scores, fluid balance, and clinical signs were analyzed.

In 40 critically ill children, there was no correlation between VExUS or LUS scores with positive fluid balance > 5%. Additional results revealed a correlation between VExUS A and rhonchi (r = 0.367, p = 0.020), VExUS B and rhonchi (r = 0.367, p = 0.020), and VExUS D and edema (r = 0.328, p = 0.039).

VExUS and LUS scores were not significantly correlated with positive fluid balance. VExUS A, B, and D correlated with rhonchi and edema in critically ill children with fluid overload.

Investigate the association between residential segregation and the incidence of chlamydia and gonorrhea from 2013 to 2021 at the county level in contiguous U.S. states.

National-level secondary US data from 2013 to 2021 from the Centers for Diseases Control and Prevention Sexually Transmitted Infection surveillance dataset, American Community Survey, and Racial Segregation Index were analyzed using the Generalized Estimating Equation, and spatial regression. Analysis was divided into two periods (2013-2019; 2020-2021) to account for COVID-19 disruptions. Residential segregation was measured by dissimilarity index categorized into reference (< 0.25), moderate (0.26-0.50), high (0.51-0.75), and extreme (> 0.75) levels. Primary outcome measures were chlamydia and gonorrhea incidence rates. Residential segregation was the key independent variable with other social determinants of health covariates. 3,211 counties within the contiguous United States were included within this study. Counties with missing data, and not within the contiguous United States were excluded.

For chlamydia, from 2013 to 2019, segregation coefficients (i.e.,13.77 and 15.84 for moderate and high segregation) indicated that greater residential segregation was associated with higher chlamydia incidence rates (P < 0.0001). From 2020 to 2021, these coefficients increased (from 13 to 15 to 28.25 and 34.16), suggesting growing segregation-driven disparities. Gonorrhea followed a similar trend, with the coefficients increasing from 0.47 to 0.55 (P < 0.001) to 1.53 and 1.62 (P < 0.05), respectively. Spatial variation in the association between segregation and chlamydia incidence remained consistent, with more pronounced associations in the Southeastern, Midwest, and Western regions. Spatial variation in the association between segregation and gonorrhea incidence were more pronounced in the South and parts of the Midwest, with weaker associations in some Northern and Western regions.

Residential segregation remained associated with chlamydia and gonorrhea transmission. The spatial patterns varied over time for both diseases. Further research should extend post-COVID-19 analysis to assess evolving relationships between residential segregation and STI incidence across U.S. regions.

What is already known on this topic: Chlamydia and gonorrhea in 2023 were the most reported sexually transmitted infections in the United States, disproportionately affecting Black Americans.

This study found that residential segregation was associated with race-specific differences in chlamydia and gonorrhea transmission, especially during the COVID-19 pandemic.How this study might affect research, practice or policy: Study findings suggest that interventions aiming to reduce chlamydia and gonorrhea incidence rates in the United States should also include intervention activities that address adversities associated with residential segregation.

The rapid spread of the Omicron BA.1 (B.1.1.529.1) SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) variant in 2021 resulted in international efforts to quickly assess its escape from immunity generated by vaccines and previous infections. Numerous laboratories published BA.1 neutralization data as preprints and reports. We collated this data in real time and regularly presented updates of the aggregated results in US, European and WHO research and advisory settings. Here, we retrospectively analyzed the accuracy of these aggregations from 85 different sources published during a time period from 2021/12/08 up to 2022/08/14. We found that the mean titer fold change from wild type-like variants to BA.1, a standard measure of a variant's immune escape, remained stable after the first 15 days of data reporting in people who were twice vaccinated, and incoming data increased the confidence in this quantity. Further, it is possible to build reliable, stable antigenic maps from this collated data already after one month of incoming data. We here demonstrate that combining early reports from variable, independent sources can rapidly indicate a new virus variant's immune escape and can therefore be of immense benefit for public health.

Parametric response mapping (PRM) on computed tomography (CT) is an imaging technique for assessing small airway disease (SAD) and emphysema in chronic obstructive pulmonary disease (COPD). This study was aimed to examine the relationship between individual spirometry components decline and PRM-CT-derived data changes over a 6-year observation period in mild and moderate COPD patients using a COPD cohort chronically exposed to dust. This study utilized longitudinal data of the COPD in Dusty Areas (CODA) cohort from 2012 to 2014. COPD was confirmed by a post-bronchodilator forced expiratory volume in one second (FEV₁) over forced vital capacity (FVC) value < 0.70. Among the 427 included patients, 106 with 6-year follow-up PRM CT data and having mild (FEV₁% of the predicted value [%pred] ≥ 80) or moderate (FEV₁%pred 50 to < 80) airflow limitation were analyzed. PRM CT metrics, including percentage of emphysema (PRM^emph) and functional small airway disease (PRM^fSAD), were also assessed. A positive correlation was found between baseline log-transformed PRM^fSAD and PRM^emph, which was stronger in patients with moderate airflow limitation. Over the 6-year follow-up, every 10% increase in PRM^fSAD was associated with a significant decline in FVC (- 8.0 mL/y, P = 0.016) and FEV₁ (- 6.0 mL/y, P = 0.001). This association was only significant in moderate COPD patients (FVC: -26.6 mL/y, P < 0.001; FEV₁: -11.8 mL/y, P = 0.002). There was the greater relative contribution of PRM^fSAD to lung function decline in moderate COPD compared to mild COPD, suggesting that the utility of PRM CT may differ according to COPD severity even in early stage of COPD.

The Community-Acquired Pneumonia, Endotypes, and Phenotypes (NACef) Dataset is a single-center dataset that includes clinical information from 768 patients diagnosed with Community-Acquired Pneumonia (CAP) at Clinica Universidad de La Sabana, Colombia. CAP continues to be a prevalent infectious condition linked to high morbidity and mortality rates during hospitalization. To help construct knowledge around this condition, this dataset encompasses Baseline Clinical Data, In-hospital follow-up, and post-hospital discharge information. This repository was captured in a prospective research study, constituting an observational cohort in translational science medicine, as we also collected biological samples to dissect the underlying mechanisms associated with severe CAP. This dataset provides opportunities for diverse statistical analyses and educational initiatives, since it contains robust clinical data and laboratory results from patients diagnosed with CAP, including data regarding COVID-19 infection. Being the first Colombian clinical database available on PhysioNet, it will contribute to a better understanding of CAP, its endotypes, and phenotypes in low- and middle-income countries (LMIC).