IMPORTANCE Alteration in lung microbes is associated with disease progression in idiopathic pulmonary fibrosis. OBJECTIVE To assess the effect of antimicrobial therapy on clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS Pragmatic, randomized, unblinded clinical trial conducted across 35 US sites. A total of 513 patients older than 40 years were randomized from August 2017 to June 2019 (final follow-up was January 2020).INTERVENTIONS Patients were randomized in a 1:1 allocation ratio to receive antimicrobials (n = 254) or usual care alone (n = 259). Antimicrobials included co-trimoxazole (trimethoprim 160 mg/sulfamethoxazole 800 mg twice daily plus folic acid 5 mg daily, n = 128) or doxycycline (100 mg once daily if body weight <50 kg or 100 mg twice daily if Ն50 kg, n = 126). No placebo was administered in the usual care alone group. MAIN OUTCOMES AND MEASURESThe primary end point was time to first nonelective respiratory hospitalization or all-cause mortality. RESULTS Among the 513 patients who were randomized (mean age, 71 years; 23.6% women), all (100%) were included in the analysis. The study was terminated for futility on December 18, 2019. After a mean follow-up time of 13.1 months (median, 12.7 months), a total of 108 primary end point events occurred: 52 events (20.4 events per 100 patient-years [95% CI, 14.8-25.9]) in the usual care plus antimicrobial therapy group and 56 events (18.4 events per 100 patient-years [95% CI, 13.2-23.6]) in the usual care group, with no significant difference between groups (adjusted HR, 1.04 [95% CI, 0.71-1.53; P = .83]. There was no statistically significant interaction between the effect of the prespecified antimicrobial agent (co-trimoxazole vs doxycycline) on the primary end point (adjusted HR, 1.15 [95% CI 0.68-1.95] in the co-trimoxazole group vs 0.82 [95% CI, 0.46-1.47] in the doxycycline group; P = .66). Serious adverse events occurring at 5% or greater among those treated with usual care plus antimicrobials vs usual care alone included respiratory events (16.5% vs 10.0%) and infections (2.8% vs 6.6%); adverse events of special interest included diarrhea (10.2% vs 3.1%) and rash (6.7% vs 0%).CONCLUSIONS AND RELEVANCE Among adults with idiopathic pulmonary fibrosis, the addition of co-trimoxazole or doxycycline to usual care, compared with usual care alone, did not significantly improve time to nonelective respiratory hospitalization or death. These findings do not support treatment with these antibiotics for the underlying disease.

Clopidogrel resistance is an emerging clinical scenario, as antiplatelet therapy has become the cornerstone of modern cardiovascular treatment. This leads to an increase in stent thromboses and recurrent ischemic events which add to the health care costs, and increased periprocedural morbidity and mortality. Management of clopidogrel resistance is challenging as there are no standardized guidelines. The arrival of newer antiplatelet drugs and the detection of genetic polymorphisms in susceptible populations may have an impact on the management. Further trials are needed regarding the target population who should be screened for clopidogrel resistance, a standardized diagnostic test to detect clopidogrel resistance, the role of pharmacogenetics, and the need for tailored therapeutic options for a patient with clopidogrel resistance.

Oxidants play an important role in homeostatic function, but excessive oxidant generation has an adverse effect on health. The manipulation of Reactive Oxygen Species (ROS) can have a beneficial effect on various lung pathologies. However indiscriminate uses of anti-oxidant strategies have not demonstrated any consistent benefit and may be harmful. Here we propose that nuanced strategies are needed to modulate the oxidant system to obtain a beneficial result in the lung diseases such as Acute Lung Injury (ALI) and Chronic Obstructive Pulmonary Disease (COPD). We identify novel areas of lung oxidant responses that may yield fruitful therapies in the future.

The Cystic Fibrosis Transmembrane conductance Regulator (CFTR) delF508 variant, which is responsible for 86% of cystic fibrosis (CF) cases, is present in Caucasian populations at a frequency of 3-5%. The vast majority of CFTR delF508 carriers do not have CF. There is little information on health and disease in heterozygous delF508 individuals. Previous studies have suggested risk-enhancing and risk-reducing effects for various diseases, with sometimes conflicting conclusions. Our aims are to determine if heterozygous delF508, in the absence of CF, is associated with risks for certain cancers. We took a genotype-first approach in a retrospective exploratory case-control study to determine cancer risks of delF508 carriers. We tested this using a unique database of 50,778 whole exome sequences (WES) linked to the extensive electronic health record (EHR) data of patients of Geisinger Health System who consented to participate in the MyCode Community Health Initiative biobanking project.

Doubts have been raised about the value of DNA-based screening for low-prevalence monogenic conditions following reports of testing this approach using available electronic health record (EHR) as the sole phenotyping source. We hypothesized that a better model for EHR-focused examination of DNA-based screening is Cystic Fibrosis (CF) since the diagnosis is proactively sought within the healthcare system. We reviewed CFTR variants in 50,778 exomes. In 24 cases with bi-allelic pathogenic CFTR variants, there were 21 true-positives. We considered three cases “potential” false-positives due to limitations in available EHR phenotype data. This genomic screening exhibited a positive predictive value of 87.5%, negative predictive value of 99.9%, sensitivity of 95.5%, and a specificity of 99.9%. Despite EHR-based phenotyping limitations in three cases, the presence or absence of pathogenic CFTR variants has strong predictive value for CF diagnosis when EHR data is used as the sole phenotyping source. Accurate ascertainment of the predictive value of DNA-based screening requires condition-specific phenotyping beyond available EHR data.