Prediction of clinical risk assessment and survival in chronic obstructive pulmonary disease with pulmonary hypertension.

BACKGROUND: Patients with pulmonary hypertension (PH) and chronic obstructive pulmonary disease (COPD) have an increased risk of disease exacerbation and decreased survival. We aimed to develop and validate a non-invasive nomogram for predicting COPD associated with severe PH and a prognostic nomogram for patients with COPD and concurrent PH (COPD-PH). METHODS: This study included 535 patients with COPD-PH from six hospitals. A multivariate logistic regression analysis was used to analyse the risk factors for severe PH in patients with COPD and a multivariate Cox regression was used for the prognostic factors of COPD-PH. Performance was assessed using calibration, the area under the receiver operating characteristic curve and decision analysis curves. Kaplan-Meier curves were used for a survival analysis. The nomograms were developed as online network software. RESULTS: Tricuspid regurgitation velocity, right ventricular diameter, N-terminal pro-brain natriuretic peptide (NT-proBNP), the red blood cell count, New York Heart Association functional class and sex were non-invasive independent variables of severe PH in patients with COPD. These variables were used to construct a risk assessment nomogram with good discrimination. NT-proBNP, mean pulmonary arterial pressure, partial pressure of arterial oxygen, the platelet count and albumin were independent prognostic factors for COPD-PH and were used to create a predictive nomogram of overall survival rates. CONCLUSIONS: The proposed nomograms based on a large sample size of patients with COPD-PH could be used as non-invasive clinical tools to enhance the risk assessment of severe PH in patients with COPD and for the prognosis of COPD-PH. Additionally, the online network has the potential to provide artificial intelligence-assisted diagnosis and treatment. HIGHLIGHTS: A multicentre study with a large sample of chronic obstructive pulmonary disease (COPD) patients diagnosed with PH through right heart catheterisation. A non-invasive online clinical tool for assessing severe pulmonary hypertension (PH) in COPD. The first risk assessment tool was established for Chinese patients with COPD-PH.

Prediction and prognosis of adverse maternal and foetal/neonatal outcomes in pulmonary hypertension: an observational study and nomogram construction.

BACKGROUND: Pregnant women with pulmonary hypertension (PH) have higher mortality rates and poor foetal/neonatal outcomes. Tools to assess these risk factors are not well established. METHODS: Predictive and prognostic nomograms were constructed using data from a "Development" cohort of 420 pregnant patients with PH, recorded between January 2009 and December 2018. Logistic regression analysis established models to predict the probability of adverse maternal and foetal/neonatal events and overall survival by Cox analysis. An independent "Validation" cohort comprised data of 273 consecutive patients assessed from January 2019 until May 2022. Nomogram performance was evaluated internally and implemented with online software to increase the ease of use. RESULTS: Type I respiratory failure, New York Heart Association functional class, N-terminal pro-brain natriuretic peptide [Formula: see text] 1400 ng/L, arrhythmia, and eclampsia with pre-existing hypertension were independent risk factors for maternal mortality or heart failure. Type I respiratory failure, arrhythmia, general anaesthesia for caesarean section, New York Heart Association functional class, and N-terminal pro-brain natriuretic peptide [Formula: see text] 1400 ng/L were independent predictors of pulmonary hypertension survival during pregnancy. For foetal/neonatal adverse clinical events, type I respiratory failure, arrhythmia, general anaesthesia for caesarean section, parity, platelet count, fibrinogen, and left ventricular systolic diameter were important predictors. Nomogram application for the Development and Validation cohorts showed good discrimination and calibration; decision curve analysis demonstrated their clinical utility. CONCLUSIONS: The nomogram and its online software can be used to analyse individual mortality, heart failure risk, overall survival prediction, and adverse foetal/neonatal clinical events, which may be useful to facilitate early intervention and better survival rates.

Visibility, wind speed, and dew point temperature are important factors in SARS-CoV-2 transmissibility.

The aim of this study is to provide evidence for the influencing factors of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus mutation by determining the impact of geographical and meteorological factors on SARS-CoV-2 transmission, and the different impacts of SARS-CoV-2 variant strains. From January 20 to March 10, 2020, we collected a number of daily confirmed new cases and meteorological factors in all cities and regions in China and Italy affected by the Alpha "variants of concern" (VOC). We also collected the daily confirmed cases of the Delta VOC infection in China and Italy from May 21 to November 30, 2021. The relationships between daily meteorological data and daily verified new cases of SARS-CoV-2 transmission were then investigated using a general additive model (GAM) with a log link function and Poisson family. The results revealed that latitude was substantially connected with daily confirmed new instances of the Alpha VOC, while there was no such correlation with Delta VOC transmission. When visibility is greater than 7 m, the propagation of the Alpha and Delta VOCs in Italy and China can be controlled. Furthermore, greater temperatures and increased wind speed reduce the transmission of the Alpha and Delta VOCs. In conclusion, geographical and meteorological factors play an important role in SARS-CoV-2 transmissibility and should be considered in virus mitigation strategies.