Effect of prone positioning on oxygenation and static respiratory system compliance in COVID-19 ARDS vs. non-COVID ARDS

Background Prone positioning is recommended for patients with moderate-to-severe acute respiratory distress syndrome (ARDS) receiving mechanical ventilation. While the debate continues as to whether COVID-19 ARDS is clinically different from non-COVID ARDS, there is little data on whether the physiological effects of prone positioning differ between the two conditions. We aimed to compare the physiological effect of prone positioning between patients with COVID-19 ARDS and those with non-COVID ARDS. Methods We retrospectively compared 23 patients with COVID-19 ARDS and 145 patients with non-COVID ARDS treated using prone positioning while on mechanical ventilation. Changes in PaO2/FiO2 ratio and static respiratory system compliance (Crs) after the first session of prone positioning were compared between the two groups: first, using all patients with non-COVID ARDS, and second, using subgroups of patients with non-COVID ARDS matched 1:1 with patients with COVID-19 ARDS for baseline PaO2/FiO2 ratio and static Crs. We also evaluated whether the response to the first prone positioning session was associated with the clinical outcome. Results When compared with the entire group of patients with non-COVID ARDS, patients with COVID-19 ARDS showed more pronounced improvement in PaO2/FiO2 ratio [adjusted difference 39.3 (95% CI 5.2–73.5) mmHg] and static Crs [adjusted difference 3.4 (95% CI 1.1–5.6) mL/cmH2O]. However, these between-group differences were not significant when the matched samples (either PaO2/FiO2-matched or compliance-matched) were analyzed. Patients who successfully discontinued mechanical ventilation showed more remarkable improvement in PaO2/FiO2 ratio [median 112 (IQR 85–144) vs. 35 (IQR 6–52) mmHg, P = 0.003] and static compliance [median 5.7 (IQR 3.3–7.7) vs. − 1.0 (IQR − 3.7–3.0) mL/cmH2O, P = 0.006] after prone positioning compared with patients who did not. The association between oxygenation and Crs responses to prone positioning and clinical outcome was also evident in the adjusted competing risk regression. Conclusions In patients with COVID-19 ARDS, prone positioning was as effective in improving respiratory physiology as in patients with non-COVID ARDS. Thus, it should be actively considered as a therapeutic option. The physiological response to the first session of prone positioning was predictive of the clinical outcome of patients with COVID-19 ARDS

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data

Background and objective: As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code). Methods: We show step-by-step how to implement the analytics pipeline for the question: ‘In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?’. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA. Results: Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Conclusion: Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world.</p

Roles of Inflammatory Biomarkers in Exhaled Breath Condensates in Respiratory Clinical Fields

Background Exhaled condensates contain inflammatory biomarkers; however, their roles in the clinical field have been under-investigated. Methods We prospectively enrolled subjects admitted to pulmonology clinics. We collected exhaled breath condensates (EBC) and analysed the levels of six and 12 biomarkers using conventional and multiplex enzyme-linked immunosorbent assay, respectively. Results Among the 123 subjects, healthy controls constituted the largest group (81 participants; 65.9%), followed by the preserved ratio impaired spirometry group (21 patients; 17.1%) and the chronic obstructive pulmonary disease (COPD) group (21 patients; 17.1%). In COPD patients, platelet derived growth factor-AA exhibited strong positive correlations with COPD assessment test (ρ=0.5926, p=0.0423) and COPD-specific version of St. George’s Respiratory Questionnaire (SGRQ-C) score (total, ρ=0.6725, p=0.0166; activity, ρ=0.7176, p=0.0086; and impacts, ρ=0.6151, p=0.0333). Granzyme B showed strong positive correlations with SGRQ-C score (symptoms, ρ=0.6078, p=0.0360; and impacts, ρ=0.6007, p=0.0389). Interleukin 6 exhibited a strong positive correlation with SGRQ-C score (activity, ρ=0.4671, p=0.0378). The absolute serum eosinophil and basophil counts showed positive correlations with pro-collagen I alpha 1 (ρ=0.6735, p=0.0164 and ρ=0.6295, p=0.0283, respectively). In healthy subjects, forced expiratory volume in 1 second (FEV1)/forced vital capacity demonstrated significant correlation with CC chemokine ligand 3 (CCL3)/macrophage inflammatory protein 1 alpha (ρ=0.3897 and p=0.0068). FEV1 exhibited significant correlation with CCL11/eotaxin (ρ=0.4445 and p=0.0017). Conclusion Inflammatory biomarkers in EBC might be useful to predict quality of life concerning respiratory symptoms and serologic markers. Further studies are needed

The association between hospital length of stay before rapid response system activation and clinical outcomes: a retrospective multicenter cohort study

Background Rapid response system (RRS) is being increasingly adopted to improve patient safety in hospitals worldwide. However, predictors of survival outcome after RRS activation because of unexpected clinical deterioration are not well defined. We investigated whether hospital length of stay (LOS) before RRS activation can predict the clinical outcomes. Methods Using a nationwide multicenter RRS database, we identified patients for whom RRS was activated during hospitalization at 9 tertiary referral hospitals in South Korea between January 1, 2016, and December 31, 2017. All information on patient characteristics, RRS activation, and clinical outcomes were retrospectively collected by reviewing patient medical records at each center. Patients were categorized into two groups according to their hospital LOS before RRS activation: early deterioration (LOS < 5 days) and late deterioration (LOS ≥ 5 days). The primary outcome was 28-day mortality and multivariable logistic regression was used to compare the two groups. In addition, propensity score-matched analysis was used to minimize the effects of confounding factors. Results Among 11,612 patients, 5779 and 5883 patients belonged to the early and late deterioration groups, respectively. Patients in the late deterioration group were more likely to have malignant disease and to be more severely ill at the time of RRS activation. After adjusting for confounding factors, the late deterioration group had higher 28-day mortality (aOR 1.60, 95% CI 1.44–1.77). Other clinical outcomes (in-hospital mortality and hospital LOS after RRS activation) were worse in the late deterioration group as well, and similar results were found in the propensity score-matched analysis (aOR for 28-day mortality 1.66, 95% CI 1.45–1.91). Conclusions Patients who stayed longer in the hospital before RRS activation had worse clinical outcomes. During the RRS team review of patients, hospital LOS before RRS activation should be considered as a predictor of future outcome.This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI18C0599)

Pulmonary function and chest computed tomography abnormalities 6-12 months after recovery from COVID-19: a systematic review and meta-analysis

Background Some coronavirus disease 2019 (COVID-19) survivors experience prolonged and varying symptoms, a condition termed post-acute COVID-19 syndrome (PACS). However, the prevalence of chronic pulmonary sequelae of PACS during long-term follow-up remains unclear. Several studies have examined this issue and reported heterogeneous results. Methods We conducted a systematic review and meta-analysis using a random-effects model to estimate the pooled prevalence of the pulmonary sequelae of COVID-19, as demonstrated by pulmonary function testing (PFT) and chest computed tomography (CT) performed at least 6 months after initial infection. PubMed, Embase, and Cochrane Library databases were searched from January 1, 2020 to December 31, 2021 to identify related studies. We investigated whether the prevalence of pulmonary sequelae decreased over time and attempted to identify the factors associated with their development by performing multiple subgroup and meta-regression analyses. Results Of the 18,062 studies identified, 30 met our eligibility criteria. Among these studies, 25 and 22 had follow-up PFT and chest CT data, respectively. The follow-up durations were approximately 6 and 12 months in 18 and 12 studies, respectively. Impaired diffusion capacity was the most common abnormality on PFT (pooled prevalence 35%, 95% confidence interval [CI] 30-41%) with a prevalence of 39% (95% CI 34-45%) and 31% (95% CI 21-40%) in the 6-month and 12-month follow-up studies, respectively (P = 0.115). Restrictive pulmonary dysfunction evident as reduced forced vital capacity was less frequent (pooled prevalence 8%, 95% CI 6-11%); however, its prevalence was lower in the 12-month follow-up studies than in the 6-month follow-up studies (5% [95% CI 3-7%] vs. 13% [95% CI 8-19%], P = 0.006). On follow-up chest CT, the pooled prevalence of persistent ground-glass opacities and pulmonary fibrosis was 34% (95% CI 24-44%) and 32% (95% CI 23-40%), respectively, and the prevalence did not decrease over time. As every meta-analysis showed significant between-study heterogeneity, subgroup and meta-regression analyses were performed to identify potential effect modifiers; the severity of index infection was associated with the prevalence of impaired diffusion capacity and pulmonary fibrosis. Conclusions A substantial number of COVID-19 survivors displayed pulmonary sequelae as part of PACS. Except for restrictive pulmonary dysfunction, the prevalence of these sequelae did not decrease until 1 year after initial infection. Considering the association between the severity of acute COVID-19 and risk of pulmonary sequelae, patients who recover from severe COVID-19 require close respiratory follow-up. Systematic review registration number PROSPERO CRD42021234357N

Machine Learning Approach Using Routine Immediate Postoperative Laboratory Values for Predicting Postoperative Mortality

Background: Several prediction models have been proposed for preoperative risk stratification for mortality. However, few studies have investigated postoperative risk factors, which have a significant influence on survival after surgery. This study aimed to develop prediction models using routine immediate postoperative laboratory values for predicting postoperative mortality. Methods: Two tertiary hospital databases were used in this research: one for model development and another for external validation of the resulting models. The following algorithms were utilized for model development: LASSO logistic regression, random forest, deep neural network, and XGBoost. We built the models on the lab values from immediate postoperative blood tests and compared them with the SASA scoring system to demonstrate their efficacy. Results: There were 3817 patients who had immediate postoperative blood test values. All models trained on immediate postoperative lab values outperformed the SASA model. Furthermore, the developed random forest model had the best AUROC of 0.82 and AUPRC of 0.13, and the phosphorus level contributed the most to the random forest model. Conclusions: Machine learning models trained on routine immediate postoperative laboratory values outperformed previously published approaches in predicting 30-day postoperative mortality, indicating that they may be beneficial in identifying patients at increased risk of postoperative death

Comparisons of exacerbations and mortality among regular inhaled therapies for patients with stable chronic obstructive pulmonary disease: Systematic review and Bayesian network meta-analysis.

BackgroundAlthough exacerbation and mortality are the most important clinical outcomes of stable chronic obstructive pulmonary disease (COPD), the drug classes that are the most efficacious in reducing exacerbation and mortality among all possible inhaled drugs have not been determined.Methods and findingsWe performed a systematic review (SR) and Bayesian network meta-analysis (NMA). We searched Medline, EMBASE, the Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, the European Union Clinical Trials Register, and the official websites of pharmaceutical companies (from inception to July 9, 2019). The eligibility criteria were as follows: (1) parallel-design randomized controlled trials (RCTs); (2) adults with stable COPD; (3) comparisons among long-acting muscarinic antagonists (LAMAs), long-acting beta-agonists (LABAs), inhaled corticosteroids (ICSs), combined treatment (ICS/LAMA/LABA, LAMA/LABA, or ICS/LABA), or a placebo; and (4) study duration ≥ 12 weeks. This study was prospectively registered in International Prospective Register of Systematic Reviews (PROSPERO; CRD42017069087). In total, 219 trials involving 228,710 patients were included. Compared with placebo, all drug classes significantly reduced the total exacerbations and moderate to severe exacerbations. ICS/LAMA/LABA was the most efficacious treatment for reducing the exacerbation risk (odds ratio [OR] = 0.57; 95% credible interval [CrI] 0.50-0.64; posterior probability of OR > 1 [P(OR > 1)] 1] = 0.004; and OR = 0.86, 95% CrI 0.76-0.98, P[OR > 1] = 0.015, respectively). The results minimally changed, even in various sensitivity and covariate-adjusted meta-regression analyses. ICS/LAMA/LABA tended to lower the risk of cardiovascular mortality but did not show significant results. ICS/LAMA/LABA increased the probability of pneumonia (OR for triple therapy = 1.56; 95% CrI 1.19-2.03; P[OR > 1] = 1.000). The main limitation is that there were few RCTs including only less symptomatic patients or patients at a low risk.ConclusionsThese findings suggest that triple therapy can potentially be the best option for stable COPD patients in terms of reducing exacerbation and all-cause mortality

Effect of chlorhexidine Mouthrinse on prevention of microbial contamination during EBUS-TBNA: a randomized controlled trial

Background Although endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive procedure, fatal infectious complications have been reported. However, adequate preventive strategies have not been determined. We aimed to investigate the effect of chlorhexidine mouthrinse on the prevention of microbial contamination during EBUS-TBNA. Methods In this single-center, assessor-blinded, parallel-group randomized controlled trial, we randomly assigned adult participants undergoing EBUS-TBNA using a convex probe to gargle for 1 minute with 100 mL of 0.12% chlorhexidine gluconate before EBUS-TBNA or to receive usual care (no chlorhexidine mouthrinse). Aspiration needle wash samples were collected immediately after completion of EBUS-TBNA by instilling sterile saline into the used needle. The primary outcome was colony forming unit (CFU) counts per mL of needle wash samples in aerobic cultures. Secondary outcomes were CFU counts per mL of needle wash samples in anaerobic cultures, fever within 24 hours after EBUS-TBNA, and infectious complications within 4 weeks after EBUS-TBNA. Results From January 2021 to June 2021, 106 patients received either chlorhexidine mouthrinse (n = 51) or usual care (n = 55). The median CFU counts of needle wash samples in aerobic cultures were not significantly different in the two groups (10 CFU/mL vs 20 CFU/mL; P = 0.70). There were no significant differences between the groups regarding secondary outcomes, including median CFU counts in anaerobic cultures (P = 0.41) and fever within 24 hours after EBUS-TBNA (11.8% vs 5.6%, P = 0.31). There were no infectious complications within 4 weeks in both groups. Conclusions Chlorhexidine mouthrinse did not reduce CFU counts in needle wash samples of EBUS-TBNA.This study was supported by a 2020 Grant from the Korean Academy of Tuberculosis and Respiratory Diseases

Effect of prone positioning on gas exchange according to lung morphology in patients with acute respiratory distress syndrome

Background: There are limited data on the clinical effects of prone positioning according to lung morphology. We aimed to determine whether the gas exchange response to prone positioning dif-fers according to lung morphology. Methods: This retrospective study included adult patients with moderate-to-severe acute respira-tory distress syndrome (ARDS). The lung morphology of ARDS was assessed by chest computed to-mography scan and classified as &amp; ldquo;diffuse &amp; rdquo; or &amp; ldquo;focal.&amp; rdquo; The primary outcome was change in partial pressure of arterial oxygen to fraction of inspired oxygen (PaO2/FiO2) ratio after the first prone po-sitioning session: first, using the entire cohort, and second, using subgroups of patients with dif-fuse ARDS matched 2 to 1 with patients with focal ARDS at baseline. Results: Ninety-five patients were included (focal ARDS group, 23; diffuse ARDS group, 72). Before prone positioning, the focal ARDS group showed worse oxygenation than the diffuse ARDS group (median PaO2/FiO2 ratio, 79.9 mm Hg [interquartile range (IQR)], 67.7 &amp; ndash;112.6 vs. 104.0 mm Hg [IQR, 77.6 &amp; ndash;135.7]; P=0.042). During prone positioning, the focal ARDS group showed a greater improve-ment in the PaO2/FiO2 ratio than the diffuse ARDS group (median, 55.8 mm Hg [IQR, 11.1 &amp; ndash;109.2] vs. 42.8 mm Hg [IQR, 11.6 &amp; ndash;83.2]); however, the difference was not significant (P=0.705). Among the PaO2/FiO2-matched cohort, there was no significant difference in change in PaO2/FiO2 ratio af-ter prone positioning between the groups (P=0.904). Conclusions: In patients with moderate-to-severe ARDS, changes in PaO2/FiO2 ratio after prone positioning did not differ according to lung morphology. Therefore, prone positioning can be con-sidered as soon as indicated, regardless of ARDS lung morphology. &lt;comment&gt;Superscript/Subscript Available&lt;/commentN