Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data

The role of neutrophil to lymphocyte ratio in patients with COPD-OSA overlap syndrome

PURPOSE

The aim of this study is to investigate the role of the neutrophil to lymphocyte ratio (NLR) in patients diagnosed with the chronic obstructive pulmonary disease-obstructive sleep apnea (COPD-OSA) overlap syndrome and comorbid pulmonary hypertension (PH).

PATIENTS AND METHODS

We enrolled a consecutive of stable COPD patients and conducted spirometry measurements, nocturnal polysomnography (PSG), and echocardiography for all participants. Clinical laboratory data were collected.

RESULTS

A total of 178 patients with stable COPD were enrolled among whom 33.14% (59/178) were diagnosed with OSA. Of the patients with overlap syndrome, 35.59% (21/59) showed comorbid PH, compared to 34.45% (41/119) in COPD patients without OSA. There was no significant difference in the occurrence of PH between COPD with and without OSA. NLR was significantly higher in patients with overlap syndrome compared to those with either disease alone. The difference in NLR between COPD-OSA patients with and without PH was not significant. Correlation analysis revealed that NLR was associated with age, total sleep time spent with oxygen saturation below 90% (T90), CRP, pulmonary artery systolic pressure (PASP), and minimum peripheral capillary oxygen saturation (SpO2min) in all COPD patients. NLR was identified as an independent factor contributing to OSA in COPD. The median cut-off value for detecting OSA in stable COPD was 2.49. However, NLR was not found to be a predictor for PH in COPD-OSA overlap syndrome.

CONCLUSIONS

NLR can serve as a predictive marker for comorbid OSA in patients with COPD. NLR is expected to increase its clinical application as a convenient and cost-effective biomarker for COPD-OSA overlap syndrome.

CT-based whole lung radiomics nomogram: a tool for identifying the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease

OBJECTIVES

To evaluate the value of CT-based whole lung radiomics nomogram for identifying the risk of cardiovascular disease (CVD) in patients with chronic obstructive pulmonary disease (COPD).

MATERIALS AND METHODS

A total of 974 patients with COPD were divided into a training cohort (n = 402), an internal validation cohort (n = 172), and an external validation cohort (n = 400) from three hospitals. Clinical data and CT findings were analyzed. Radiomics features of whole lung were extracted from the non-contrast chest CT images. A radiomics signature was constructed with algorithms. Combined with the radiomics score and independent clinical factors, multivariate logistic regression analysis was used to establish a radiomics nomogram. ROC curve was used to analyze the prediction performance of the model.

RESULTS

Age, weight, and GOLD were the independent clinical factors. A total of 1218 features were extracted and reduced to 15 features to build the radiomics signature. In the training cohort, the combined model (area under the curve [AUC], 0.731) showed better discrimination capability (p < 0.001) than the clinical factors model (AUC, 0.605). In the internal validation cohort, the combined model (AUC, 0.727) performed better (p = 0.032) than the clinical factors model (AUC, 0.629). In the external validation cohort, the combined model (AUC, 0.725) performed better (p < 0.001) than the clinical factors model (AUC, 0.690). Decision curve analysis demonstrated the radiomics nomogram outperformed the clinical factors model.

CONCLUSION

The CT-based whole lung radiomics nomogram has the potential to identify the risk of CVD in patients with COPD.

CLINICAL RELEVANCE STATEMENT

This study helps to identify cardiovascular disease risk in patients with chronic obstructive pulmonary disease on chest CT scans.

KEY POINTS

• To investigate the value of CT-based whole lung radiomics features in identifying the risk of cardiovascular disease in chronic obstructive pulmonary disease patients. • The radiomics nomogram showed better performance than the clinical factors model to identify the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease. • The radiomics nomogram demonstrated excellent performance in the training, internal validation, and external validation cohort (AUC, 0.731; AUC, 0.727; AUC, 0.725).

Sex differences in comorbidities and mortality risk among patients with chronic obstructive pulmonary disease: a study based on NHANES data

BACKGROUND

Patients with chronic obstructive pulmonary disease (COPD) commonly have coexisting comorbidities that contribute to higher exacerbation frequency, poorer health status, and increased all-cause mortality; however, there are only a few studies available on the sex discrepancy in the comorbidity distribution and outcomes among COPD patients, and there is limited information about the discrepancy in all-cause mortality between men and women.

METHODS

Based on data from the U.S. National Health and Nutrition Examination Survey conducted between 2007 and 2012, we compared participants aged 40-79 years with spirometry-defined COPD to compare the prevalence of comorbidities between men and women. The survival of the subjects was documented, and the sex discrepancy was determined using Kaplan-Meier analysis. Comorbidities and all-cause mortality were analyzed by using a Cox proportional hazards model to determine their strength of association in different sex groups.

RESULTS

Compared to men, women had a significantly higher prevalence of asthma (OR 1.93, 95% CI 1.46 to 2.57, p < 0.001) and arthritis (OR 1.77, 95% CI 1.39 to 2.24, p < 0.001). Women had a significantly lower prevalence of coronary heart disease (OR 0.48, 95% CI 0.27 to 0.87, p = 0.015) and gout (OR 0.42, 95% CI 0.25 to 0.67, p = 0.001). Kaplan-Meier analysis revealed that compared with that of the female group, the survival rate of the male group was significantly lower (p < 0.001). Among men, the presence of anemia (HR 2.38, [95% CI 1.52-3.73], p < 0.001), gout (HR 1.55, [95% CI 1.04-2.30], p = 0.029) and congestive heart failure comorbidities (HR 1.85, [95% CI 1.12-3.04] p = 0.016) was associated with a higher risk of mortality; among women, the presence of anemia (HR 2.21, [95% CI 1.17-4.20], p = 0.015) and stroke (HR 2.04, [95% CI 1.07-3.88], p = 0.031) comorbidities was associated with a higher risk of mortality after adjusting for age, race/Hispanic status, BMI, smoking status, FEV1% predicted and prevalent comorbidities.

CONCLUSIONS

COPD-related comorbidities and all-cause mortality were discrepant between men and women, and men had poorer survival than women in the nationally representative data that were analyzed.

The Emerging Clinical Significance of the Red Cell Distribution Width as a Biomarker in Chronic Obstructive Pulmonary Disease: A Systematic Review

There is an intense focus on the identification of novel biomarkers of chronic obstructive pulmonary disease (COPD) to enhance clinical decisions in patients with stable disease and acute exacerbations (AECOPD). Though several local (airway) and circulatory inflammatory biomarkers have been proposed, emerging evidence also suggests a potential role for routine haematological parameters, e.g., the red cell distribution width (RDW). We conducted a systematic literature search in PubMed, Web of Science, and Scopus, from inception to April 2022, for articles investigating the diagnostic and prognostic role of the RDW in stable COPD and AECOPD. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Significant associations between the RDW and the presence and severity of disease, outcomes (mortality, hospital readmission), and other relevant clinical parameters (right heart failure, pulmonary arterial hypertension) were reported in 13 out of 16 studies in stable COPD (low risk of bias in 11 studies), and 17 out of 21 studies of AECOPD (low risk of bias in 11 studies). Pending further research, our systematic review suggests that the RDW might be useful, singly or in combination with other parameters, for the diagnosis and risk stratification of patients with stable COPD and AECOPD (PROSPERO registration number: CRD42022348304).

Prognostic value of neutrophils to lymphocytes and platelets ratio for 28-day mortality in patients with acute respiratory distress syndrome: a retrospective study

Background

Acute respiratory distress syndrome (ARDS) is a rapidly progressive and fatal respiratory failure disease that often occurs in critically ill patients. Since ARDS is associated with immune dysregulation and coagulation abnormalities, it is necessary to identify an appropriate predictor that can accurately predict ARDS mortality based on its pathophysiology. Therefore, this study aimed to evaluate the clinical value of neutrophils to lymphocytes and platelets ratio (N/LPR) in predicting 28-day mortality in ARDS patients.

Methods

From July 2018 to October 2021, the medical records of ARDS patients were retrospective reviewed. Neutrophil count, lymphocyte count, and platelet count were collected, and the neutrophil-to-lymphocyte ratio (NLR) and N/LPR were calculated. Multivariate logistic regression analyses were performed to identify independent predictors of 28-day mortality in ARDS. Receiver operating characteristic (ROC) curve with the area under curve (AUC) was used to evaluate optimal cut-off values for 28-day mortality in ARDS. Kaplan–Meier analysis was used to estimate the 28-day survival probabilities stratified by optimal cut-off values of N/LPR and NLR.

Results

A total of 136 ARDS patients were included in this study and were further divided into survivors (n = 69) and non-survivors (n = 67) groups according to their survival status on day 28. There were no significant differences between the two groups in age, sex, history of smoking and drinking, comorbidities, and reasons of admission (P > 0.05). Non-survivors had significantly higher neutrophil counts, NLR and N/LPR and had significantly lower platelet counts than survivors (P < 0.05). Multivariate regression analysis revealed that N/LPR, NLR and platelet counts were independent predictors for 28-day mortality in ARDS (P < 0.05). The ROC analyses showed that N/LPR with optimal cut-off value of 10.57 (sensitivity: 74.6%; specificity: 72.5%) is a more reliable predictor for 28-day mortality in ARDS than NLR and platelet count (AUC: 0.785 vs. 0.679 vs. 0.326). Further subgroup analysis confirmed that ARDS patients with N/LPR < 10.57 had significantly lower 28-day mortality than patients with N/LPR ≥ 10.57 (P < 0.001). Kaplan–Meier analysis also confirmed that ARDS patients with N/LPR < 10.57 had significantly longer survival.

Conclusion

N/LPR is an independent risk factor associated with 28-day mortality in ARDS patients and shows better performance in predicting mortality rate than NLR.