Bronchopleural fistula and bilateral pneumothorax in a patient with COVID‐19

COVID‐19 pneumonia causes several complications that include pneumothorax, hydropneumothorax, empyema, and rarely leads to bronchopleural fistula (BPF). BPF is a communication between the pleural space and the bronchial tree. We report a case of 24 years man with pneumothorax, hydropneumothorax, and BPF that appeared after COVID‐19 infection.     

Changes in symptom reflux association using dynamic pH thresholds during ambulatory pH monitoring: an observational cross‐sectional study

Symptom reflux association (SRA) assesses symptoms associated with reflux events defined by pH <4.0, but limited symptoms associate with reflux events. We evaluated the impact of alternate pH thresholds on SRA in a large ambulatory pH database. Acid exposure time (AET), reflux events, and associated symptoms (within 2 minutes following a reflux event) were extracted from ambulatory pH studies performed off antireflux therapy (722 patients, 49.1 ± 0.5 years, 66.8% F) over a 7‐year period. Symptom association probability (SAP) and symptom index (SI) were calculated at pH 3.5, 4.0, 4.5, and 5. Receiver operating characteristics (ROC) were generated using SRA at any pH as gold standard; areas under the curve (AUCs) were determined. Discordant cases were reanalyzed to determine changes in SRA and predictors of change using multivariate regression. At pH 4.0, 41% had a positive SAP, and 34% had a positive SI. While there was sustained gain in SI positivity from acidic to more weakly acidic pH thresholds, SAP positivity was highest at pH 4.5. On ROC analysis, performance characteristics were best at pH 4.0 (AUC 0.97) for SAP, and at pH 4.5 and 5.0 (AUC 0.92–0.94) for SI. On multivariate logistic regression adjusting for age, gender, and change in AET and reflux events, only number of associated symptoms predicted change in SRA (P < 0.0001). Changing pH thresholds for reflux events augments SRA by increasing reflux events associated with existing symptoms, while symptom recording remains the principal determinant of SRA.     

An evaluation of two commercial deep learning-based information retrieval systems for COVID-19 literature

The COVID-19 pandemic has resulted in a tremendous need for access to the latest scientific information, leading to both corpora for COVID-19 literature and search engines to query such data. While most search engine research is performed in academia with rigorous evaluation, major commercial companies dominate the web search market. Thus, it is expected that commercial pandemic-specific search engines will gain much higher traction than academic alternatives, leading to questions about the empirical performance of these tools. This paper seeks to empirically evaluate two commercial search engines for COVID-19 (Google and Amazon) in comparison with academic prototypes evaluated in the TREC-COVID task. We performed several steps to reduce bias in the manual judgments to ensure a fair comparison of all systems. We find the commercial search engines sizably underperformed those evaluated under TREC-COVID. This has implications for trust in popular health search engines and developing biomedical search engines for future health crises.