Elissa Driggin, Mahesh V. Madhavan, B. Bikdeli
et al.
The coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 that has significant implications for the cardiovascular care of patients. First, those with COVID-19 and pre-existing cardiovascular disease have an increased risk of severe disease and death. Second, infection has been associated with multiple direct and indirect cardiovascular complications including acute myocardial injury, myocarditis, arrhythmias, and venous thromboembolism. Third, therapies under investigation for COVID-19 may have cardiovascular side effects. Fourth, the response to COVID-19 can compromise the rapid triage of non-COVID-19 patients with cardiovascular conditions. Finally, the provision of cardiovascular care may place health care workers in a position of vulnerability as they become hosts or vectors of virus transmission. We hereby review the peer-reviewed and pre-print reports pertaining to cardiovascular considerations related to COVID-19 and highlight gaps in knowledge that require further study pertinent to patients, health care workers, and health systems.
Objective: To investigate the association between hypertension and outcome in patients with Coronavirus Disease 2019 (COVID-19) pneumonia. Methods: We performed a systematic literature search from several databases on studies that assess hypertension and outcome in COVID-19. Composite of poor outcome, comprising of mortality, severe COVID-19, acute respiratory distress syndrome (ARDS), need for intensive care unit (ICU) care and disease progression were the outcomes of interest. Results: A total of 6560 patients were pooled from 30 studies. Hypertension was associated with increased composite poor outcome (risk ratio (RR) 2.11 (95% confidence interval (CI) 1.85, 2.40), p < 0.001; I2, 44%) and its sub-group, including mortality (RR 2.21 (1.74, 2.81), p < 0.001; I2, 66%), severe COVID-19 (RR 2.04 (1.69, 2.47), p < 0.001; I2 31%), ARDS (RR 1.64 (1.11, 2.43), p = 0.01; I2,0%, p = 0.35), ICU care (RR 2.11 (1.34, 3.33), p = 0.001; I2 18%, p = 0.30), and disease progression (RR 3.01 (1.51, 5.99), p = 0.002; I2 0%, p = 0.55). Meta-regression analysis showed that gender (p = 0.013) was a covariate that affects the association. The association was stronger in studies with a percentage of males < 55% compared to ⩾ 55% (RR 2.32 v. RR 1.79). Conclusion: Hypertension was associated with increased composite poor outcome, including mortality, severe COVID-19, ARDS, need for ICU care and disease progression in patients with COVID-19.
Thamir M. Alshammari, Mohammed K. Alshammari, Hind M. Alosaimi
Background: Respiratory Syncytial Virus is a predominant source of morbidity and mortality, particularly among babies, the elderly, and immunocompromised patients. Recent developments in RSV vaccines, approved by the FDA for high-risk groups, have highlighted the necessity for post-marketing surveillance to evaluate their real-world safety and efficacy. Method: This study utilized data from the Vaccine Adverse Event Reporting System (VAERS) covering RSV vaccine administration between 2023 and May 2025. The VAERS database reported data on vaccine types, including Arexvy®, Abrysvo®, and mRESVIA® was analyzed for adverse events and vaccination errors. The demographic information, vaccination trends, and hospitalizations post-vaccination among the vaccinated individuals were accessed. Results: The analysis revealed that the most common adverse events were mild, such as injection site pain, erythema, fatigue, and extremity pain. The data also showed a gradual increase in hospitalization rates from 4.8% in 2023 to 7.5% in 2025. Vaccination errors, including inappropriate administration during pregnancy and excess doses, were also observed. A notable trend was the growing proportion of patients who experienced no adverse events, with the highest rate of symptom-free reports seen in 2025 (25.9%). Conclusions: RSV vaccines demonstrate a generally acceptable safety profile based on post-marketing surveillance data. However, the observed increase in hospitalization rates, vaccination errors, and pregnancy-related outcomes warrants continued active surveillance and cautious interpretation.
Background: Respiratory diseases are a leading cause of childhood morbidity and mortality, yet lung auscultation remains subjective and limited by inter-listener variability, particularly in pediatric populations. Existing AI approaches are further constrained by small datasets and single-task designs. We developed PulmoVec, a multi-task framework built on the Health Acoustic Representations (HeAR) foundation model for classification of pediatric respiratory sounds. Methods: In this retrospective analysis of the SPRSound database, 24,808 event-level annotated segments from 1,652 pediatric patients were analyzed. Three task-specific classifiers were trained for screening, sound-pattern recognition, and disease-group prediction. Their out-of-fold probability outputs were combined with demographic metadata in a LightGBM stacking meta-model, and event-level predictions were aggregated to the patient level using ensemble voting. Results: At the event level, the screening model achieved an ROC-AUC of 0.96 (95% CI, 0.95-0.97), the sound-pattern recognition model a macro ROC-AUC of 0.96 (95% CI, 0.96-0.97), and the disease-group prediction model a macro ROC-AUC of 0.94 (95% CI, 0.93-0.94). At the patient level, disease-group classification yielded an accuracy of 0.74 (95% CI, 0.71-0.77), a weighted F1-score of 0.73, and a macro ROC-AUC of 0.91 (95% CI, 0.90-0.93). Stacking improved performance across all tasks compared with base models alone. Conclusions: PulmoVec links event-level acoustic phenotyping with patient-level clinical classification, supporting the potential of foundation-model-based digital auscultation in pediatric respiratory medicine. Multi-center external validation across devices and real-world conditions remains essential.
COVID-19 is an evolving systemic inflammatory pandemic disease, predominantly affecting the respiratory system. Associated cardiovascular comorbid conditions result in severe to critical illness with mortality up to 14.8 % in octogenarians. The role of endothelial dysfunction in its pathogenesis has been proposed with laboratory and autopsy data, though initially it was thought of as only acute respiratory distress syndrome (ARDS). The current study on endothelial dysfunction in SARS CoV-2 infection highlights its pathophysiology through the effects of direct viral-induced endothelial injury, uncontrolled immune & inflammatory response, imbalanced coagulation homeostasis, and their interactions resulting in a vicious cycle aggravating the disease process. This review may provide further light on proper laboratory tests and therapeutic implications needed for better management of patients. The main objective of the study is to understand the pathophysiology of COVID-19 with respect to the role of endothelium so that more additional relevant treatment may be incorporated in the management protocol.
Damla Serçe Unat, Şener Arikan, Özgür Kirbiyik
et al.
Abstract Introduction Brain metastasis (BM) in non-small cell lung cancer (NSCLC) is still an important reason for morbidity and mortality despite the advances in cancer treatment. Using tyrosine kinase inhibitors against epidermal growth factor receptors (EGFR) mutations revolutionized NSCLC treatment. We investigated whether the presence of EGFR mutation influences survival in patients with lung adenocarcinoma with BM. Material and methods The data of the patients with pathological diagnoses of NSCLC and BM at tertiary hospitals were analyzed retrospectively in terms of survival. A total of 2554 patients diagnosed with NSCLC pathologically between 01 January 2010 and 01 January 2021 were identified. After the exclusion of patients with a lack of data, unknown EGFR mutation status, no brain metastasis, and additional malignancy 336 patients were included in the study. Results It was found that EGFR ( +) patients were more female dominant (48.6% vs 13.3% p < 0.0001) and were have less history of smoking (47.2% vs 87.1%, p < 0.0001) and were better survival (79.2% vs 92.8%). We found negativity of EGFR increased death risk by 1.700 times (95% CI 1.323–2.183, p < 0.0001) in univariate analysis and by 1.724 times (95% CI 1.251–2.377, p = 0.0001) in multivariate analysis. When overall survivals were compared estimated overall survival time of EGFR ( −) patients was 10.088 (95% CI 8.571–11.606) months and of EGFR ( +) patients was 11.829 months (95% CI 10.336–13.323) (p < 0.001). Conclusion EGFR positivity was associated with survival. Also, survival was significantly longer in EGFR-positive patients with brain metastases diagnosed with NSCLC.
Diseases of the respiratory system, Medical emergencies. Critical care. Intensive care. First aid
Respiratory sound datasets are limited in size and quality, making high performance difficult to achieve. Ensemble models help but inevitably increase compute cost at inference time. Soft label training distills knowledge efficiently with extra cost only at training. In this study, we explore soft labels for respiratory sound classification as an architecture-agnostic approach to distill an ensemble of teacher models into a student model. We examine different variations of our approach and find that even a single teacher, identical to the student, considerably improves performance beyond its own capability, with optimal gains achieved using only a few teachers. We achieve the new state-of-the-art Score of 64.39 on ICHBI, surpassing the previous best by 0.85 and improving average Scores across architectures by more than 1.16. Our results highlight the effectiveness of knowledge distillation with soft labels for respiratory sound classification, regardless of size or architecture.
Niccolò McConnell, Pardeep Vasudev, Daisuke Yamada
et al.
Low-dose computed tomography (LDCT) imaging employed in lung cancer screening (LCS) programs is increasing in uptake worldwide. LCS programs herald a generational opportunity to simultaneously detect cancer and non-cancer-related early-stage lung disease. Yet these efforts are hampered by a shortage of radiologists to interpret scans at scale. Here, we present TANGERINE, a computationally frugal, open-source vision foundation model for volumetric LDCT analysis. Designed for broad accessibility and rapid adaptation, TANGERINE can be fine-tuned off the shelf for a wide range of disease-specific tasks with limited computational resources and training data. Relative to models trained from scratch, TANGERINE demonstrates fast convergence during fine-tuning, thereby requiring significantly fewer GPU hours, and displays strong label efficiency, achieving comparable or superior performance with a fraction of fine-tuning data. Pretrained using self-supervised learning on over 98,000 thoracic LDCTs, including the UK's largest LCS initiative to date and 27 public datasets, TANGERINE achieves state-of-the-art performance across 14 disease classification tasks, including lung cancer and multiple respiratory diseases, while generalising robustly across diverse clinical centres. By extending a masked autoencoder framework to 3D imaging, TANGERINE offers a scalable solution for LDCT analysis, departing from recent closed, resource-intensive models by combining architectural simplicity, public availability, and modest computational requirements. Its accessible, open-source lightweight design lays the foundation for rapid integration into next-generation medical imaging tools that could transform LCS initiatives, allowing them to pivot from a singular focus on lung cancer detection to comprehensive respiratory disease management in high-risk populations.
François-Xavier Blaudin de Thé, C. Klemann, Ward De Witte
et al.
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that primarily affects motor neurons, leading to loss of muscle control, and, ultimately, respiratory failure and death. Despite some advances in recent years, the underlying genetic and molecular mechanisms of ALS remain largely elusive. In this respect, a better understanding of these mechanisms is needed to identify new and biologically relevant therapeutic targets that could be developed into treatments that are truly disease-modifying, in that they address the underlying causes rather than the symptoms of ALS. In this study, we used two approaches to model multi-omics data in order to map and elucidate the genetic and molecular mechanisms involved in ALS, i.e., the molecular landscape building approach and the Patrimony platform. These two methods are complementary because they rely upon different omics data sets, analytic methods, and scoring systems to identify and rank therapeutic target candidates. The orthogonal combination of the two modeling approaches led to significant convergences, as well as some complementarity, both for validating existing therapeutic targets and identifying novel targets. As for validating existing targets, we found that, out of 217 different targets that have been or are being investigated for drug development, 10 have high scores in both the landscape and Patrimony models, suggesting that they are highly relevant for ALS. Moreover, through both models, we identified or corroborated novel putative drug targets for ALS. A notable example of such a target is MATR3, a protein that has strong genetic, molecular, and functional links with ALS pathology. In conclusion, by using two distinct and highly complementary disease modeling approaches, this study enhances our understanding of ALS pathogenesis and provides a framework for prioritizing new therapeutic targets. Moreover, our findings underscore the potential of leveraging multi-omics analyses to improve target discovery and accelerate the development of effective treatments for ALS, and potentially other related complex human diseases.
The Encyclopaedia Cloacae is a novel and centralised digital platform designed to support and advance wastewater-based epidemiology (WBE) by cataloguing pathogens detectable in wastewater and their relevance to public health surveillance. The platform is hosted on the EU Wastewater Observatory for Public Health (EU4S) website, where it is populated with peer-reviewed research through a structured workflow under harmonised criteria which address the presence of pathogens in human excreta, detectability in wastewater, and integration into public health systems. This tri-criteria approach ensures that the database is both scientifically robust and operationally actionable. Complemented by the Visualising the Invisible dashboard, the platform offers geospatial insights into global WBE research activity. By consolidating peer-reviewed evidence on pathogen detectability in wastewater and human excreta, the Encyclopaedia Cloacae enables early detection of infectious diseases, whether already known or newly emerging. The continuously updated repository and geospatial dashboards help to identify surveillance gaps and research hotspots, to support timely public health responses, enhance pandemic preparedness, and strengthen global health security. In addition, it supports One Health strategies, connecting the health of humans, animals, and the shared environment. This article outlines the platform’s architecture, data curation methodology, and future directions, including automation and expansion to encompass broader health determinants such as antimicrobial resistance and chemical hazards.
Introduction Achieving and maintaining optimal glycemic control from the onset of type 1 diabetes (T1D) is crucial in pediatric care, especially in early childhood when the developing brain is highly vulnerable to both hypo- and hyperglycemia [1-3]. Hyperglycemia during early childhood increases the risk of long-term vascular complications, while severe hypoglycemia may impair neurocognitive development, causes family anxiety, and complicates social integration [4-5]. Although automated insulin delivery (AID) systems have demonstrated efficacy in controlled trials, real-world evidence in children under six years of age, particularly involving off-label use, remains limited. The Control-IQ (CIQ) algorithm, integrated into the Tandem t:slim X2 insulin pump, has shown benefits in adolescents and school-aged children [6-10]. However, few studies have evaluated its long-term use in children under six in routine clinical practice. Objective This study aimed to compare the real-world effectiveness and safety of the CIQ system in two pediatric age groups—children aged 0.5–5 years and children aged 6–10 years—over an 18-month follow-up period. We evaluated effectiveness in terms of glycemic control (% of time in glucose range 70–180 mg/dL [TIR], % of time in glucose range 70–140 mg/dL [TITR], and HbA1c) and safety in term of adverse events (diabetic ketoacidosis [DKA], hyperglycemia and severe hypoglycemia). Methods This prospective, multicenter observational study used retrospective data from 32 Italian pediatric diabetes centers. Eligible participants had T1D diagnosed ≥ 6 months, , were 10 years at CIQ start were excluded. Participants were stratified by age at CIQ initiation (0.5–5 and 6–10 years). At CIQ initiation (baseline) sex, presence of celiac disease or thyroiditis and parents’ age, nationality and education, were collected. HbA1c, BMI z-score, CGM-derived data (TIR, TITR, % of time spent in glucose ranges: 250 mg/dL, Glucose Monitoring Indicators and coefficient of variation of glucose), Glycemia, Standard Deviation of Glycemia [SD] and DKA episodes were assessed at baseline, 6, 12, and 18 months. Descriptive statistics were used for baseline comparisons. Chi-square or t tests evaluated group differences. Trend over time points in TIR, TITR, and HbA1c were analysed using mixed-effects models for repeated measures, adjusted by age group, sex, time from diagnosis to CIQ initiation, DKA at onset and parents’ socio-economic characteristics (at least one non-Italian parent, parents’ education). A sequential difference contrast was used to model time; interaction between time and age groups was evaluated. Only children with complete data on the outcomes at all four time points were included in these models. Safety outcomes included the proportions of DKA and severe hypoglycaemias occurring during 18-month follow-up. Results Of the 334 children enrolled, 253 (106 aged 0.5–5; 147 aged 6–10) had complete data on the outcomes and were included in longitudinal analyses. At T1D diagnosis, a higher prevalence of thyroiditis in the older group was found, and no significant sociodemographic differences. At CIQ initiation, younger children had a significantly shorter time from diagnosis to CIQ initiation (1.36 vs 2.61 years, p<0.001), higher HbA1c (8.3%% vs 7.7%, p=0.020) and higher glycaemic variability (SD 63.3 mg/dL vs 58.3 mg/dL, p = 0.023) while TIR, TITR, and the other CGM-derived data were comparable. Longitudinal analysis (Figure 1) showed significant improvement in both groups 6 months after CIQ initiation: TIR increased by 6.62% (95% CI: 4.89–8.36) and TITR by 5.63% (95% CI: 3.61–7.66), corresponding to over 80 additional minutes/day spent in target ranges. These improvements were sustained at 12 and 18 months. HbA1c decreased by an average of 0.82% (95% CI: –1.01 to –0.62) in the first 6 months, remaining stable thereafter. No significant interaction between time and age groups was observed, indicating similar trends in both cohorts. Having at least one non-Italian parent was significantly associated with lower TIR (-5.82%, 95% CI: -10.33 to -1.31) and higher HbA1c levels (0.31%, 95% CI: 0.01 to 0.63). A high parental education level (university or higher vs. up to lower secondary education) was associated with higher TIR (8.61%, 95% CI: 3.03–14.18) and lower HbA1c levels (−0.42%, 95% CI: −0.78 to −0.06). Age at CIQ initiation, time from diagnosis to CIQ initiation, DKA at diagnosis, and sex were not significant predictor. Regarding safety, no severe hypoglycaemia episodes were reported in the younger group, and only one occurred in the older group after 12 months. A single DKA episode was recorded in a child under six. Moreover, CGM-derived data indicated that time spent in hypoglycaemia (<54 and 54–69 mg/dL) remained consistently below clinically relevant thresholds (<1% and <3%, respectively). Conclusion In this large real-world cohort of young children with T1D, the CIQ system demonstrated consistent and sustained improvements in glycaemic outcomes over 18 months, with minimal adverse events. Significant gains in TIR, TITR, and HbA1c were observed in both age groups, particularly in the first 6 months after CIQ initiation. These benefits were maintained long-term, regardless of initial glycaemic status and presence of DKA at diagnosis. The system proved safe even in children under six, supporting its current use in off-label settings with appropriate clinical oversight. Our findings reinforce the value of early AID adoption to optimize long-term metabolic outcomes in pediatric T1D.
N. M. Hettiarachchi, S. Manilgama, I. K. Jayasinghe
Coronavirus disease 2019 (COVID-19), pandemic caused by the novel coronavirus SARS-CoV-2, has caused marked morbidity and mortality globally. The clinical spectrum of COVID-19 can be classified as asymptomatic, mild, moderate and severe disease. Majority of the symptomatic patients complain of fever, dry cough, sore throat and shortness of breath, while others present with non-specific symptoms like altered sense of smell or taste, myalgia, lethargy, diarrhoea and other gastrointestinal disturbances. Though COVID-19 mainly affects the respiratory system, disease may cause widespread systemic and organ specific symptoms involving gastrointestinal, neurological, cardiovascular, immunological, cutaneous, hematological and coagulation systems. Minority of patients present with large vessel strokes, rare neurological syndromes like Guillain-Barre syndrome and Miller Fisher syndrome, which may be the sole manifestation of the disease. Some of the clinical presentations and pathogenesis of COVID are yet to be unraveled.
The lung is continuously exposed to particles, toxicants, and microbial pathogens that are cleared by a complex mechanical, innate, and acquired immune system. Mucociliary clearance, mediated by the actions of diverse conducting airway and submucosal gland epithelial cells, plays a critical role in a multilayered defense system by secreting fluids, electrolytes, antimicrobial and antiinflammatory proteins, and mucus onto airway surfaces. The mucociliary escalator removes particles and pathogens by the mechanical actions of cilia and cough. Abnormalities in mucociliary clearance, whether related to impaired fluid secretion, ciliary dysfunction, lack of cough, or the disruption of epithelial cells lining the respiratory tract, contribute to the pathogenesis of common chronic pulmonary disorders. Although mucus and other airway epithelial secretions play a critical role in protecting the lung during acute injury, impaired mucus clearance after chronic mucus hyperproduction causes airway obstruction and infection, which contribute to morbidity in common pulmonary disorders, including chronic obstructive pulmonary disease, asthma, idiopathic pulmonary fibrosis, cystic fibrosis, bronchiectasis, and primary ciliary dyskinesia. In this summary, the molecular and cellular mechanisms mediating airway mucociliary clearance, as well as the role of goblet cell metaplasia and mucus hyperproduction, in the pathogenesis of chronic respiratory diseases are considered.
Coronavirus disease 2019 (COVID-19) is mainly an infectious disease of the respiratory system transmitted through air droplets, and pulmonary symptoms constitute main presentations of this disease. However, COVID-19 demonstrates a clinically diverse manifestation ranging from asymptomatic presentation to critically illness with severe pneumonia, acute respiratory distress syndrome, respiratory failure, or multiple organ failure. Accumulating evidences demonstrated that COVID-19 has extrapulmonary involvement, including neurological, smelling sensation, cardiovascular, digestive, hepatobiliary, renal, endocrinologic, dermatologic system, and others. Over a third of COVID-19 patients manifest a wide range of neurological symptoms involving the central/peripheral nervous system. Underlying cardiovascular comorbidities were associated with detrimental outcomes, meanwhile the occurrence of cardiovascular complications correlate to poor survival. Gastrointestinal symptoms frequently occur and have been associated with a longer period of illness. Impaired hepatic functions were associated with the severity of the disease. Higher rate of acute kidney injury was reported in critically ill patients with COVID-19. Endocrinologic presentations of COVID-19 include exacerbating hyperglycemia, euglycemic ketosis, and diabetic ketoacidosis. The most common cutaneous manifestation was acro-cutaneous (pernio or chilblain-like) lesions, and other skin lesions consist of maculopapular rash, vesicular lesions, livedoid/necrotic lesions, exanthematous rashes, and petechiae. This review article summarized the general clinical signs and symptoms, radiologic features, and disease manifestation with progression in patients with COVID-19.
Abstract Background A multi-component self-management intervention ‘CFHealthHub’ was developed to reduce pulmonary exacerbations in adults with Cystic Fibrosis (CF) by supporting adherence to nebuliser medication. It was evaluated in a randomized controlled trial (RCT) involving 19 CF centres, with 32 interventionists, 305 participants in the intervention group, and 303 participants in the standard care arm. Ensuring treatment fidelity of intervention delivery was crucial to ensure that the intervention produced the expected outcomes. Methods Fidelity of the CFHealthHub intervention and standard care was assessed using different methods for each of the five fidelity domains defined by the Borrelli framework: study design, training, treatment delivery, receipt, and enactment. Study design ensured that the groups received the intended intervention or standard care. Interventionists underwent training and competency assessments to be deemed certified to deliver the intervention. Audio-recorded intervention sessions were assessed for fidelity drift. Receipt was assessed by identifying whether participants set Action and Coping Plans, while enactment was assessed using click analytics on the CFHealthHub digital platform. Results Design: There was reasonable agreement (74%, 226/305) between the expected versus actual intervention dose received by participants in the CFHealthHub intervention group. The standard care group did not include focused adherence support for most centres and participants. Training: All interventionists were trained. Treatment delivery: The trial demonstrated good fidelity (overall fidelity by centre ranged from 79 to 97%), with only one centre falling below the mean threshold (> 80%) on fidelity drift assessments. Receipt: Among participants who completed the 12-month intervention, 77% (205/265) completed at least one action plan, and 60% (160/265) completed at least one coping plan. Enactment: 88% (268/305) of participants used web/app click analytics outside the intervention sessions. The mean (SD) number of web/app click analytics per participant was 31.2 (58.9). Additionally, 64% (195/305) of participants agreed to receive notifications via the mobile application, with an average of 53.6 (14.9) notifications per participant. Conclusions The study demonstrates high fidelity throughout the RCT, and the CFHealthHub intervention was delivered as intended. This provides confidence that the results of the RCT are a valid reflection of the effectiveness of the CFHealthHub intervention compared to standard care. Trial registration ISRCTN registry: ISRCTN55504164 (date of registration: 12/10/2017).
BACKGROUND: A post-authorisation safety study (PASS) on delamanid (DLM) was conducted as part of a post-approval commitment to the European Medicines Agency. The aim of this study was to evaluate the use of DLM in a real-life setting, its safety, and treatment outcomes in patients with multidrug-resistant TB (MDR-TB).METHODS: This was a prospective, multicentric, non-interventional study conducted in the European Union. MDR-TB Regimen selection and patient monitoring were conducted in accordance with existing medical practices. Data on the use of DLM, related adverse events, and treatment outcomes were collected for up to 30 months after the first DLM dose. Descriptive summary statistics were used for continuous and categorical variables.RESULTS: Out of 86 patients, one had extrapulmonary TB. Two-thirds of the patients were treated with DLM for more than 24 weeks. The most frequent adverse drug reaction to DLM was QT interval prolongation. Resistance to DLM was detected in one patient during treatment. The treatment success rate was 77%.CONCLUSION: No new safety concerns were revealed, including in patients treated with DLM for more than 24 weeks. QT interval prolongations were well managed and did not lead to any clinically significant cardiac effects. The treatment outcomes were in line with the WHO target for Europe.
Adiba Sultana, Giovanni Battista Migliori, Lia D’Ambrosio
et al.
ABSTRACT Objective: Many biologic agents cause some degree of immunosuppression, which can increase the risk of reactivation of tuberculosis infection (TBI). This risk is variable between individual biologics. We aimed to assess current (and recommended) clinical practice of TBI screening and treatment among patients initiating treatment with biologic agents. Methods: An online questionnaire was distributed via email to members of the Global Tuberculosis Network and associated professional organisations to seek insights into the screening for and treatment of TBI in patients treated with biologics. Results: A total of 163 respondents in 27 countries answered at least one question. For all biologics described in the questionnaire, respondents advised increasing screening relative to current practice. Observed and supported TBI screening rates in patients treated with TNF-a inhibitors were high, especially for older TNF-a inhibitors. Most participants supported TBI screening in patients treated with B- or T-cell inhibitors but not in those treated with interleukin inhibitors. Guideline awareness was higher for TNF-a inhibitors than for other biologic classes (79% vs. 34%). Conclusions: Although respondents stated that TBI screening rates are lower than what they consider ideal, there was a tendency to recommend TBI screening in patients treated with biologics not known to be associated with an increased risk of TBI. As a result, there is a potential risk of over-screening and over-treatment of TBI, potentially causing harm, in patients treated with biologics other than TNF-a inhibitors. There is a need to research the risk of TBI associated with biologics and for guidelines to address the spectrum of TBI risk across all types of biologics.
Yi-Heng Cao, Vincent Bourbonne, François Lucia
et al.
Objective: Four-dimensional computed tomography (4DCT) imaging consists in reconstructing a CT acquisition into multiple phases to track internal organ and tumor motion. It is commonly used in radiotherapy treatment planning to establish planning target volumes. However, 4DCT increases protocol complexity, may not align with patient breathing during treatment, and lead to higher radiation delivery. Approach: In this study, we propose a deep synthesis method to generate pseudo respiratory CT phases from static images for motion-aware treatment planning. The model produces patient-specific deformation vector fields (DVFs) by conditioning synthesis on external patient surface-based estimation, mimicking respiratory monitoring devices. A key methodological contribution is to encourage DVF realism through supervised DVF training while using an adversarial term jointly not only on the warped image but also on the magnitude of the DVF itself. This way, we avoid excessive smoothness typically obtained through deep unsupervised learning, and encourage correlations with the respiratory amplitude. Main results: Performance is evaluated using real 4DCT acquisitions with smaller tumor volumes than previously reported. Results demonstrate for the first time that the generated pseudo-respiratory CT phases can capture organ and tumor motion with similar accuracy to repeated 4DCT scans of the same patient. Mean inter-scans tumor center-of-mass distances and Dice similarity coefficients were $1.97$mm and $0.63$, respectively, for real 4DCT phases and $2.35$mm and $0.71$ for synthetic phases, and compares favorably to a state-of-the-art technique (RMSim).