Prenatal prediction of neonatal respiratory morbidity: a radiomics method based on imbalanced few-shot fetal lung ultrasound images

Background To develop a non-invasive method for the prenatal prediction of neonatal respiratory morbidity (NRM) by a novel radiomics method based on imbalanced few-shot fetal lung ultrasound images. Methods A total of 210 fetal lung ultrasound images were enrolled in this study, including 159 normal newborns and 51 NRM newborns. Fetal lungs were delineated as the region of interest (ROI), where radiomics features were designed and extracted. Integrating radiomics features selected and two clinical features, including gestational age and gestational diabetes mellitus, the prediction model was developed and evaluated. The modelling methods used were data augmentation, cost-sensitive learning, and ensemble learning. Furthermore, two methods, which embed data balancing into ensemble learning, were employed to address the problems of imbalance and few-shot simultaneously. Results Our model achieved sensitivity values of 0.82, specificity values of 0.84, balanced accuracy values of 0.83 and area under the curve values of 0.87 in the test set. The radiomics features extracted from the ROIs at different locations within the lung region achieved similar classification performance outcomes. Conclusion The feature set we designed can efficiently and robustly describe fetal lungs for NRM prediction. RUSBoost shows excellent performance compared to state-of-the-art classifiers on the imbalanced few-shot dataset. The diagnostic efficacy of the model we developed is similar to that of several previous reports of amniocentesis and can serve as a non-invasive, precise evaluation tool for NRM prediction.

Occupational risk assessment and selected morbidities among cement brick unit workers in a rural area of Bangalore District, India

Introduction: The labor-intensive nature of cement brick manufacturing, its unorganized nature and internal migration, expose the employees to several occupational health hazards. The objective of the study was to assess the occupational risks in cement brick unit settings and to estimate the prevalence of respiratory and musculoskeletal morbidities among the cement brick unit workers in a rural area of Bangalore urban district. Methods: A cross-sectional study was conducted among cement brick unit workers over two months. A semi-structured questionnaire was used to capture sociodemographic details. Multiple observations on the field and the World Health Organization semi-quantitative risk assessment matrix were used to obtain risk scores of the occupational hazards. A structured questionnaire on respiratory symptoms and Minispir Portable Spirometer were used to assess the respiratory morbidities and lung functions. Musculoskeletal morbidities were assessed using the Modified Nordic questionnaire. Proportions were used to describe respiratory and musculoskeletal morbidities. Chi-square test, Fisher’s exact test and multivariate logistic regressions were done to identify significant variables. Results: Among 120 subjects, 110 (91.6%) were men and 85.8% were migrants. Injury due to falls of heavy objects, back injury, respiratory complaints and slips/falls were found to be high-risk health hazards. The prevalence of respiratory morbidity was 21.7% and that of musculoskeletal morbidity was 51.7%. Workers receiving a higher salary (≥ 1500 Indian rupees) had higher odds of having respiratory morbidity. Conclusion: The prevalence of respiratory and musculoskeletal morbidities was high. Introduction of mechanical equipment, decreasing work hours, periodic medical examinations and appropriate use of personal protective equipment will help in risk reduction as per this study.

Recovering from a pandemic: pulmonary fibrosis after SARS-CoV-2 infection

Acute manifestations of SARS-CoV-2 infection continue to impact the lives of many across the world. Post-acute sequelae of coronavirus disease 2019 (COVID-19) may affect 10–30% of survivors of COVID-19, and post-acute sequelae of COVID-19 (PASC)-pulmonary fibrosis is a long-term outcome associated with major morbidity. Data from prior coronavirus outbreaks (severe acute respiratory syndrome and Middle East respiratory syndrome) suggest that pulmonary fibrosis will contribute to long-term respiratory morbidity, suggesting that PASC-pulmonary fibrosis should be thoroughly screened for through pulmonary function testing and cross-sectional imaging. As data accumulates on the unique pathobiologic mechanisms underlying critical COVID-19, a focus on corollaries to the subacute and chronic profibrotic phenotype must be sought as well. Key aspects of acute COVID-19 pathobiology that may account for increased rates of pulmonary fibrosis include monocyte/macrophage–T-cell circuits, profibrotic RNA transcriptomics, protracted elevated levels of inflammatory cytokines, and duration of illness and ventilation. Mechanistic understanding of PASC-pulmonary fibrosis will be central in determining therapeutic options and will ultimately play a role in transplant considerations. Well-designed cohort studies and prospective clinical registries are needed. Clinicians, researchers and healthcare systems must actively address this complication of PASC to minimise disability, maximise quality of life and confront a post-COVID-19 global health crisis.