Severity of resting functional impairment only partially predicts the increased risk of death in chronic obstructive pulmonary disease (COPD). Increased ventilation during exercise is associated with markers of disease progression and poor prognosis, including emphysema extension and pulmonary vascular impairment. Whether excess exercise ventilation would add to resting lung function in predicting mortality in COPD, however, is currently unknown. After an incremental cardiopulmonary exercise test, 288 patients (forced expiratory volume in one second ranging from 18% to 148% predicted) were followed for a median (interquartile range) of 57 (47) months. Increases in the lowest (nadir) ventilation to CO2 output (VCO2) ratio determined excess exercise ventilation. Seventy-seven patients (26.7%) died during follow-up: 30/77 (38.9%) deaths were due to respiratory causes. Deceased patients were older, leaner, had a greater co-morbidity burden (Charlson Index) and reported more daily life dyspnea. Moreover, they had poorer lung function and exercise tolerance (p < 0.05). A logistic regression analysis revealed that ventilation/VCO2 nadir was the only exercise variable that added to age, body mass index, Charlson Index and resting inspiratory capacity (IC)/total lung capacity (TLC) ratio to predict all-cause and respiratory mortality (p < 0.001). Kaplan-Meier analyses showed that survival time was particularly reduced when ventilation/VCO2 nadir > 34 was associated with IC/TLC ≤ 0.34 or IC/TLC ≤ 0.31 for all-cause and respiratory mortality, respectively (p < 0.001). Excess exercise ventilation is an independent prognostic marker across the spectrum of COPD severity. Physiological abnormalities beyond traditional airway dysfunction and lung mechanics are relevant in determining the course of the disease.
Objective
Saudi Arabia has succeeded in having one of the lowest rates of COVID-19 worldwide due to the government’s initiatives in taking swift action to control both the spread and severity of the virus. However, Covid-19 can serve as a test case of the expected response of the new healthcare system under Vision 2030. This study used data from the thirteen present administrative regions of KSA to simulate the variations in ICU admission as a quality indicator in the five business units proposed by a new Model of Care.
Methods
We determined the rates of ICU admission for patients with confirmed SARS-CoV-2 (COVID-19) from March to mid-July 2020. The final sample included 1743 inpatients with moderate to severe COVID-19. Patient characteristics, including demographics, pre-existing chronic conditions, and COVID-19 complications, were collected. Business units (BUs) were compared with respect to the relative odds of ICU admission by using multiple logistic regression.
Results
After keeping patient and clinical characteristics constant, clear BU differences were observed in the relative odds of ICU admission of COVID-19 patients. Inpatient admission to ICU in our total sample was almost 50%. Compared to the Central BU, the Northern and Western BUs showed significantly higher odds of ICU admission while the Eastern & Southern BUs had significantly lower odds.
Conclusion
ICU use for COVID-19 patients differed significantly in KSA healthcare BUs, consistent with variations in care for other non-COVID-19-related conditions. These differences cannot be explained by patient or clinical characteristics, suggesting quality-of-care differences. We believe that privatization and the shift to fewer administrative BUs will help lessen or eliminate altogether the present variations in healthcare service provision.
To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.