Blood monocyte levels predict the risk of acute exacerbations of chronic obstructive pulmonary disease: a retrospective case-control study

Development and validation of a nomogram for assessing survival in acute exacerbation of chronic obstructive pulmonary disease patients

BACKGROUND

Early prediction of survival of hospitalized acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients is vital. We aimed to establish a nomogram to predict the survival probability of AECOPD patients.

METHODS

Retrospectively collected data of 4601 patients hospitalized for AECOPD. These patients were randomly divided into a training and a validation cohort at a 6:4 ratio. In the training cohort, LASSO-Cox regression analysis and multivariate Cox regression analysis were utilized to identify prognostic factors for in-hospital survival of AECOPD patients. A model was established based on 3 variables and visualized by nomogram. The performance of the model was assesed by AUC, C-index, calibration curve, decision curve analysis in both cohorts.

RESULTS

Coexisting arrhythmia, invasive mechanical ventilation (IMV) usage and lower serum albumin values were found to be significantly associated with lower survival probability of AECOPD patients, and these 3 predictors were further used to establish a prediction nomogram. The C-indexes of the nomogram were 0.816 in the training cohort and 0.814 in the validation cohort. The AUC in the training cohort was 0.825 for 7-day, 0.807 for 14-day and 0.825 for 21-day survival probability, in the validation cohort this were 0.796 for 7-day, 0.831 for 14-day and 0.841 for 21-day. The calibration of the nomogram showed a good goodness-of-fit and decision curve analysis showed the net clinical benefits achievable at different risk thresholds were excellent.

CONCLUSION

We established a nomogram based on 3 variables for predicting the survival probability of AECOPD patients. The nomogram showed good performance and was clinically useful.

Predictive Role of White Blood Cell Differential Count for the Development of Acute Exacerbation in Korean Chronic Obstructive Pulmonary Disease

Purpose

Chronic obstructive pulmonary disease (COPD) is a respiratory disease characterized by chronic inflammation. Acute exacerbation of COPD (AECOPD) manifests as acute worsening of respiratory symptoms and is associated with high morbidity and mortality. The aim of the present study was to evaluate the predictive value of white blood count (WBC) and its derived inflammatory biomarkers for AECOPD.

Methods

From the Korean COPD Subgroup Study cohort, a prospective and multicenter observational study, 826 patients who had baseline complete blood count (CBC) and 3-year AECOPD data were included. Follow-up CBC data at 1 (n = 385), 2 (n = 294), and 3 (n = 231) years were collected for available patients. The primary outcome was the occurrence of AECOPD at 3 years. The risk of AECOPD was evaluated using a binary logistic analysis.

Results

The cumulative incidences of 12-, 24-, and 36-month AECOPD were 47.6%, 60.5%, and 67.6%, respectively. Patients with AECOPD at 3 years had higher baseline WBC counts, neutrophil counts, neutrophil/lymphocyte ratio (NLR), and neutrophil/monocyte ratio than those without AECOPD. Higher WBC count, neutrophil count, and NLR were associated with the 3-year occurrence of AECOPD in the univariate analysis, but only the higher neutrophil count was a significant risk factor (odds ratio [OR] = 1.468; 95% confidence interval [CI]: 1.024-2.104) in the covariates-adjusted analysis. In the analysis of changes in inflammatory parameters, a decrease in the platelet count (OR = 0.502; 95% CI: 0.280-0.902) and NLR (OR = 0.535; 95% CI: 0.294-0.974) at 2 years and an increase in the eosinophil count (OR = 2.130; 95% CI: 1.027-4.416) at 3 years were significantly associated with AECOPD in the adjusted analysis.

Conclusion

Our data suggest that a high baseline WBC count, particularly neutrophil count, was associated with a higher incidence of long-term AECOPD.

A predictive model for frequent exacerbator phenotype of acute exacerbations of chronic obstructive pulmonary disease

Background

The frequent exacerbator phenotype of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is characterized by experiencing at least two exacerbations per year, leading to a significant economic burden on healthcare systems worldwide. Although several biomarkers have been shown to be effective in assessing AECOPD severity in recent years, there is a lack of studies on markers to predict the frequent exacerbator phenotype of AECOPD. The current study aimed to develop a new predictive model for the frequent exacerbator phenotype of AECOPD based on rapid, inexpensive, and easily obtained routine markers.

Methods

This was a single-center, retrospective study that enrolled a total of 2,236 AECOPD patients. The participants were divided into two groups based on the frequency of exacerbations: infrequent group (n=1,827) and frequent group (n=409). They underwent a complete blood count, as well as blood biochemistry, blood lipid and coagulation testing, and general characteristics were also recorded. Univariate analysis and binary multivariate logistic regression analyses were used to explore independent risk factors for the frequent exacerbator phenotype of AECOPD, which could be used as components of a new predictive model. The receiver operator characteristic (ROC) curve was used to assess the predictive value of the new model, which consisted of all significant risk factors predicting the primary outcome. The nomogram risk prediction model was established using R software.

Results

Age, gender, length of stay (LOS), neutrophils, monocytes, eosinophils, direct bilirubin (DBil), gamma-glutamyl transferase (GGT), and the glucose-to-lymphocyte ratio (GLR) were independent risk factors for the frequent exacerbator phenotype of AECOPD. The area under the curve (AUC) of the new predictive model was 0.681 [95% confidence interval (CI): 0.653-0.708], and the sensitivity was 63.6% (95% CI: 58.9-68.2%) and the specificity was 65.0% (95% CI: 60.3-69.6%).

Conclusions

A new predictive model based on demographic characteristics and blood parameters can be used to predict the frequency of acute exacerbations in the management of chronic obstructive pulmonary disease (COPD).

Association of preoperative monocyte/lymphocyte ratio with postoperative oxygenation impairment in patients with acute aortic syndrome

BACKGROUND

Postoperative oxygenation impairment represents a common complication in patients with the acute aortic syndrome (AAS). The study aimed to explore the relationship between inflammatory indicators and AAS patients with oxygenation impairment after operation.

METHODS

In this study, 330 AAS patients who underwent surgery were enrolled and divided into 2 groups based on postoperative oxygenation impairment (non-oxygenation impairment group and oxygenation impairment group). Regression analysis was performed to assess the relationship between inflammatory indicators and postoperative oxygenation impairment. A smooth curve and interaction analysis were further conducted. Stratified analysis was used according to preoperative monocyte/lymphocyte ratio (MLR) (Tertiles).

RESULTS

Multivariate analysis showed that preoperative MLR was independently related to oxygenation impairment after surgery in AAS patients (OR, 95% CI, P: 2.77, 1.10-7.00, 0.031). The smooth curve indicated the risk of postoperative oxygenation impairment was higher with the elevated preoperative MLR. Interaction analysis revealed that patients with AAS with high preoperative MLR who had coronary artery disease (CAD) had a higher risk of oxygenation impairment after operation. Moreover, stratified analysis was performed according to baseline MLR (Tertiles), and a higher baseline MLR level in AAS patients was correlated with a lower arterial oxygen tension (P_aO2) / inspiratory oxygen fraction (F_iO2) ratio perioperatively.

CONCLUSIONS

In AAS patients, preoperative MLR level was independently related to postoperative oxygenation impairment.

Monocyte to eosinophil ratio as a diagnostic biomarker for overlap syndrome and predictor of disease exacerbation

Objectives: Chronic Obstructive Pulmonary Disease (COPD) is one of the most common pulmonary diseases. The concomitant association of Obstructive Sleep Apnea (OSA) and COPD is known as the Overlap Syndrome (OS). This study aimed to identify markers for predicting OS, among routine laboratory tests, including differential blood counts.Methods: One hundred twenty-five patients with exacerbated COPD were enrolled in the study and screened for OSA using the Epworth Sleepiness Scale (ESS). Those with a positive ESS score underwent polysomnography (PSG) for confirmation. All patients were followed for 90 days to monitor for subsequent exacerbations.Results: Out of the 125 patients with exacerbated COPD, 25 were confirmed to have OSA. Those with OS had a significantly higher body mass index (BMI) (p < 0.001). The monocyte to eosinophil ratio (MER) was significantly higher in the OS group, while the neutrophil to monocyte (NMR) ratio and platelets to monocyte (PMR) ratio were significantly lower. Younger age, male sex, and higher body mass index (BMI) were all associated with OS. During the 90-day follow-up period after hospital discharge, 60% of patients with OS were re-admitted due to acute exacerbations. The hazard ratio for a second exacerbation increased by two-fold for every one-unit increase MER. The MER demonstrated excellent utility in predicting a second exacerbation, with an area under the curve (AUC) of 83% and a p-value of .005.Conclusion: The monocyte to eosinophil ratio (MER) was independent predictors of OS among exacerbated COPD patients and had a very good prognostic utility for predicting the next exacerbation episodes. Long term follow up is recommended to evaluate the severity of exacerbations and the effect of complications of OS on the morbidity and mortality of these patients.