Video-assisted surgical diagnosis and pleural adhesion management in catamenial pneumothorax: A case and literature review.

Catamenial pneumothorax is a rare primary spontaneous pneumothorax associated with the menstrual phase and is the most common manifestation of thoracic endometriosis syndrome. We report a case of a 32-year-old woman with a history of endometriosis who presented to the emergency ward with a chief complaint of dyspnea and right-sided chest pain, and a chest X-ray showed a right pneumothorax. Initial management was by placing a chest tube to expand the right lung. The patient underwent a video-assisted thoracoscopy and talc pleurodesis, during which we found multiple perforations in the tendinous part of the diaphragm. A partial resection of the tendinous part of the diaphragm was done. Our review indicated that primary spontaneous pneumothorax in women should be suspected as catamenial pneumothorax due to thoracic endometriosis. The gold standard procedure for diagnosis and treatment is surgery. Hormonal therapy is an effective choice to prevent and reduce post-operative recurrence.

Double-Blind, Randomized, Placebo-Controlled Study on hzVSF-v13, a Novel Anti-Vimentin Monoclonal Antibody Drug as Add-on Standard of Care in the Management of Patients with Moderate to Severe COVID-19.

Humanized Virus Suppressing Factor-variant 13 (hzVSF-v13), a monoclonal IgG4 antibody against vimentin, was investigated in moderate to severe COVID-19 pneumonia through a Phase II study. Patients were randomized to two different IV doses of the test drug or saline with standard of care. Overall, 64 patients were recruited, and 62 entered the efficacy assessment in the full analysis set. Primary endpoint: The clinical failure rate at day 28 was 15.8% for placebo, 9.1% for low-dose hzVSF-v13 and 9.5% for high-dose hzVSF-v13 (not significant). A trend toward better efficacy was shown in several secondary endpoints, with statistical significance between low-dose hzVSF-v13 and placebo in terms of the rate of improved patients on the ordinal scale for clinical improvement (OSCI): 90.0% vs. 52.63% (p = 0.0116). In the severe stratum, the results of low-dose hzVSF-v13 vs. placebo were 90.0% and 22.2% for OSCI (p = 0.0092), 9 days and 14 days for time to discontinuation of oxygen therapy (p = 0.0308), 10 days and 15 days for both time to clinical improvement (TTCI) and time to recovery (TTR) and p = 0.0446 for both TTCI and TTR. Change from baseline of NEWS2 score at day 28 was -3.4 vs. + 0.4 (p = 0.0441). The results propose hzVSF-v13 as a candidate in the treatment of severe COVID-19.

The emergence of COVID-19 in Indonesia: analysis of predictors of infection and mortality using independent and clustered data approaches

BackgroundAnalyses of correlates of SARS-CoV-2 infection or mortality have usually assessed individual predictors. This study aimed to determine if patterns of combined predictors may better identify risk of infection and mortality MethodsFor the period of March 2nd to 10th 2020, the first 9 days of the COVID-19 pandemic in Indonesia, we selected all 18 confirmed cases, of which 6 died, and all 60 suspected cases, of which 1 died; and 28 putatively negative patients with pneumonia and no travel history. We recorded data for travel, contact history, symptoms, haematology, comorbidities, and chest x-ray. Hierarchical cluster analyses (HCA) and principal component analyses (PCA) identified cluster and covariance patterns for symptoms or haematology which were analysed with other predictors of infection or mortality using logistic regression. ResultsFor univariate analyses, no significant association with infection was seen for fever, cough, dyspnoea, headache, runny nose, sore throat, gastrointestinal complaints (GIC), or haematology. A PCA symptom component for fever, cough, and GIC tended to increase risk of infection (OR 3.41; 95% CI 1.06-14; p=0.06), and a haematology component with elevated monocytes decreased risk (OR 0.26; 0.07-0.79; 0.027). Multivariate analysis revealed that an HCA cluster of 3-5 symptoms, typically fever, cough, headache, runny nose, sore throat but little dyspnoea and no GIC tended to reduce risk (aOR 0.048; <0.001-0.52; 0.056). In univariate analyses for death, an HCA cluster of cough, fever and dyspnoea had increased risk (OR 5.75; 1.06 - 31.3, 0.043), but no other individual predictor, cluster or component was associated. Other significant predictors of infection were age [≥] 45, international travel, contact with COVID-19 patient, and pneumonia. Diabetes and history of contact were associated with higher mortality. ConclusionsCluster groups and co-variance patterns may be stronger correlates of SARS-CoV-2 infection than individual predictors. Comorbidities may warrant careful attention as would COVID-19 exposure levels.

Clinical Progression of COVID-19 Patient with Extended Incubation Period, Delayed RT-PCR Time-to-positivity, and Potential Role of Chest CT-scan.

Coronavirus Disease 2019 (COVID-19), previously called 2019-nCoV, is a novel disease caused by SARS- CoV-2 which was first identified as outbreak of unknown respiratory illness in Wuhan, China. COVID- 19 was declared as global health emergency by WHO on March 11, 2020 and quickly elevated to global pandemic on 11 March 2020. COVID-19 symptom is highly various in each patient, with fever, fatigue, shortness of breath, and cough as the main presenting symptoms. Patient with COVID-19 may shows severe symptom with severe pneumonia and ARDS, mild symptom resembling simple upper respiration tract infection, or even completely asymptomatic. Approximately 80% of cases is mild. However the number may changes as more people are getting tested. Some experts are estimating that up to 50% of all cases may be asymptomatic carrier.

A novel diagnosis scoring model to predict invasive pulmonary aspergillosis in the intensive care unit.

OBJECTIVES: To improve the quality of invasive pulmonary aspergillosis (IPA) management for intensive care unit (ICU) patients using a practical diagnostic scoring model. METHODS: This nested case-control study aimed to determine the incidence of IPA in 405 ICU patients, between July 2012 and June 2014, at 6 hospitals in Jakarta, Indonesia. Phenotypic identifications and galactomannan (GM) tests of sera and lung excreta were performed in mycology laboratory, Parasitology Department, Faculty of Medicine, Universitas Indonesia in Jakarta, Indonesia. RESULTS: The incidence of IPA in the ICUs was 7.7% (31 of 405 patients). A scoring model used for IPA diagnosis showed 4 variables as the most potential risk factors: lung excreta GM index (score 2), solid organ malignancy (score 2), pulmonary tuberculosis (score 2), and systemic corticosteroids (score 1). Patients were included in a high-risk group if their score was greater than 2, and in a low-risk group if their score was less than 2. CONCLUSION: This study provides a novel diagnosis scoring model to predict IPA in ICU patients. Using this model, a more rapid diagnosis and treatment of IPA may be possible. The application of the diagnosis scoring should be preceded by specified pre-requisites.