The Correlation between Neutrophil Percentage-to-Albumin Ratio and Chronic Obstructive Pulmonary Disease: A Cross-sectional Analysis Based On NHANES

doi:10.21203/rs.3.rs-4925344/v1

Background

Inflammation plays a crucial role in the development of chronic obstructive pulmonary disease (COPD). The neutrophil percentage-to-albumin ratio (NPAR) is an emerging inflammatory biomarker that is cost-effective and easily accessible. Its predictive value has been demonstrated in different clinical scenarios, including myocardial infarction, heart failure, and sepsis. Despite this, the connection between NPAR and COPD is not fully understood. Therefore, we carried out a cross-sectional study to explore the relationship between NPAR and COPD.

Methods

This study analyzed data from the U.S. National Health and Nutrition Examination Survey (NHANES) spanning the years 2017 to 2020. Various statistical methods such as multiple logistic regression analysis, smooth curve fitting, threshold effect analysis, subgroup analysis, and interaction tests were utilized to explore the association between NPAR and COPD risk.

Results

The study involved 5807 participants aged 20 years and older, including 550 individuals diagnosed with COPD. Using multiple logistic regression analysis, the research found a direct link between NAPR and COPD risk, viewing NAPR as both a continuous and categorical variable. The fully adjusted model revealed that higher NAPR levels were independently linked to an increased COPD risk (OR = 1.05, 95% CI: 1.02–1.09, P = 0.007). Moreover, individuals in the highest NAPR quartile (Q4) had a 34% higher risk of COPD compared to those in the lowest quartile (Q1) ( OR = 1.34 ; 95% CI: 1.01–1.77, P = 0.039). Subgroup analyses and interaction tests supported a consistent relationship between NAPR and COPD risk, with no significant interactions found.

Conclusion

NAPR, a newly discovered inflammatory biomarker, has been shown to be associated with an increased risk of COPD, as indicated by recent research. These findings imply that NAPR could potentially be used as a prognostic tool to evaluate the likelihood of developing COPD.

NHANES

Chronic Obstructive Pulmonary Disease

Neutrophil Percentage Albumin Ratio

Cross-Sectional Study

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory condition characterized by recurring symptoms and partially reversible airflow limitation[1, 2]. It ranks as the third leading cause of mortality worldwide, resulting in over 3 million deaths each year. Projections indicate that this number will surpass 5 million by 2060[3]. Currently, the global COPD patient population exceeds 250 million, a figure that continues to grow due to rising environmental pollution and an aging population[4]. This increasing prevalence not only impacts the physical and mental well-being of individuals but also places a significant economic burden on families and society as a whole[5]. In the United States alone, the economic cost of COPD is estimated to reach around $40 billion annually in the next two decades[6]. Therefore, the identification of reliable clinical markers for assessing COPD risk is essential in the fight against this disease.

The association between inflammatory response and COPD development is well-established, with changes in inflammatory cells and mediators serving as key indicators of COPD progression[7]. While various inflammatory markers like systemic immune inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and c-reactive protein to albumin ratio (CAR) have been explored for predicting COPD risk and prognosis, their sensitivity and specificity remain suboptimal^8 ~ 11. However, these measures are not perfect because they have low sensitivity or specificity. Therefore, there is a need to explore new inflammatory predictors for COPD risk assessment. Neutrophil percentage-to-albumin ratio (NPAR) is a novel composite inflammatory marker that highlights the role of neutrophils in inflammatory responses[12], while serum albumin (ALB) is known for its anti-inflammatory effects through specific inhibition of adhesion molecules[13]. Previous research has demonstrated the predictive value of NAPR in various conditions like chronic heart failure, acute myocardial infarction, acute kidney injury, sepsis, and stroke^14 ~ 18. Based on these findings, it is plausible to consider NPAR as a potential biomarker for assessing COPD risk. However, there is currently a lack of studies investigating the relationship between NAPR and COPD risk.

In this study, we investigated the relationship between NPAR and the risk of COPD using data from the 2017–2020 National Health and Nutrition Examination Survey (NHANES). The aim was to offer clinicians better tools for evaluating COPD risk. Our hypothesis suggested that higher NAPR levels would be linked to a greater likelihood of COPD.

2. 1 Design of the study and individuals involved.

In this study, we conducted a thorough screening of 15, 560 participants sourced from the U. S. National Health Survey, spanning from 2017 to March 2020. To ensure the accuracy and reliability of our results, we implemented strict exclusion criteria: (1) individuals under 20 years old, (2) individuals with incomplete COPD data, (3) individuals with incomplete NAPR data, and (4) participants with any other missing variable data. After applying these criteria, 5, 807 participants were ultimately chosen from the initial cohort of 15, 560 (Figure 1).

2. 2Definition of NAPR and COPD.

A complete blood cell count was conducted using an automated hematology analyzer (BeckmanCoulterDxH800) to measure neutrophil levels. The concentration of albumin was assessed using a two-color digital endpoint method. In this process, albumin interacts with the bromocresol violet reagent, resulting in the formation of a complex. The instrument tracks changes in absorbance at 600nm, with fluctuations in albumin concentration directly linked to changes in absorbance. The NAPR is determined by dividing the percentage of neutrophils by the albumin concentration, both of which are derived from the same blood sample. The formula for calculating NAPR is as follows: (neutrophil percentage (%) * 100 / albumin (g/dl))[19]. For a detailed description of the laboratory methods, please visit: https://wwwn. cdc. gov/Nchs/Nhanes/2003-2004/L25_C. htm.

The history of COPD, our study's outcome variable, was evaluated by asking participants if they had ever been diagnosed with the disease by a physician or other medical professional. The questionnaire included three self-reported measures of chronic obstructive lung disease outcomes (emphysema, chronic bronchitis, and COPD). Participants were asked during individual interviews if they had ever been informed by a doctor or health professional about having COPD, emphysema, or chronic bronchitis. A positive response to this question indicated a diagnosis of COPD.

2. 3 Selection and definition of covariates

In our research, we utilized a range of covariates to adjust for potential confounding variables. These covariates encompassed factors such as age, gender, race/ethnicity (including Mexican American, non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, other Hispanic, other/multiracial), education level (categorized as less than high school, high school graduate, more than high school), poverty income ratio (PIR), body mass index (BMI), smoking habits, alcohol consumption, presence of hypertension, diabetes, and coronary heart disease. The PIR was calculated by dividing the annual family income by the poverty line and serves as a key indicator of socioeconomic status. BMI was divided into three groups: normal (< 25kg/m2), overweight (≥ 25kg/m2 and < 30kg/m2), and obese (≥ 30kg/m2). Smoking status was classified as current smoker, former smoker, or never smoker. Current smokers were individuals who had smoked more than 100 cigarettes in their lifetime and currently smoked occasionally or regularly. Former smokers were individuals who had smoked more than 100 cigarettes in their lifetime but were not currently smoking. Never smokers were individuals who had smoked fewer than 100 cigarettes in their lifetime. Drinkers were defined as participants who reported consuming any type of alcoholic beverage at least once per month in the past 12 months. Hypertension was identified in participants who reported being diagnosed with hypertension on two or more occasions. Diabetes was defined as self-reported diagnosis along with the use of diabetes medication or having glycohemoglobin A1C ≥ 6. 5% in the laboratory dataset. For coronary heart disease, individuals who had been informed by a doctor or other health professionals of their condition were considered to have the disease.

2. 4 Statistical analysis

Participants were grouped based on COPD status. Continuous variables were described using mean ± standard deviation (Mean ± SD), while categorical variables were presented as numbers (N) and percentages (%). Kruskal-Wallis Rank sum test was used for continuous variables, and chi-square test for categorical variables to compare characteristics between those with and without COPD. A multiple logistic regression model was employed to assess the relationship between NAPR and COPD. Model adjustments included age, sex, race, education level, marital status, PIR, BMI, smoking status, drinking status, hypertension, diabetes, and coronary heart disease. Smooth curve fitting was conducted to analyze the NAPR threshold effect on COPD prevalence. Subgroup analysis and interaction tests were performed to explore associations between NAPR and COPD in specific populations based on age, gender, race, BMI, smoking habits, alcohol consumption, and hypertension. Statistical analyses were carried out using EmpowerStats 4.2 and R software, with statistical significance set at P < 0.05.

3. 1 Baseline Characteristics of Participants

Among the 5, 807 participants analyzed in this study, 550 were diagnosed with COPD (9.47%). The eligible subjects had an average age of 50.61 ± 17.20 years, with 2, 880 females and 2, 927 males. The study revealed that, when compared with the non-COPD group, the COPD group exhibited higher proportions of males, non-Hispanic whites, individuals with a high school education or above, widowed/divorced/separated individuals, smokers, drinkers, and those with underlying diseases (such as hypertension, diabetes, and coronary heart disease) (p < 0.05). Moreover, there were statistically significant differences between the two groups in terms of age, PIR, BMI, and NPAR levels (p < 0.05). The general characteristics of the study population are detailed in Table 1.

TABLE 1 Basic characteristics of participants (n =5807) in the NHANES 2017–2020.

Outcomes	Total, N = 5807（100%）	Non-COPD, N = 5257 (93%)	COPD, N = 550 (7. 3%)	P-value
Age (years)	50.62 ± 17.27	49.63 ± 17.20	60.05 ± 14.89	<0.001
PIR	2.66 ± 1.63	2.72 ± 1.63	2.09 ± 1.43	<0.001
BMI (kg/m2)	30.23 ± 7.63	30.05 ± 7.38	31.98 ± 9.55	<0.001
NAPR	14.20 ± 2.85	14.11 ± 2.80	15.12 ± 3.15	<0.001
Gender				0.202
Male	2927 (50.40%)	2664 (50.68%)	263 (47.82%)
Female	2880 (49.60%)	2593 (49.32%)	287 (52.18%)
Race				<0.001
Mexican American	681 (11.73%)	662 (12.59%)	19 (3.45%)
Other Hispanic	565 (9.73%)	532 (10.12%)	33 (6.00%)
Non-Hispanic White	2276 (39.19%)	1946 (37.02%)	330 (60.00%)
Non-Hispanic Black	1456 (25.07%)	1344 (25.57%)	112 (20.36%)
Other Race	829 (14.28%)	773 (14.70%)	56 (10.18%)
Education level				<0.001
Less than high school	906 (15.60%)	801 (15.24%)	105 (19.09%)
High school	1402 (24.14%)	1229 (23.38%)	173 (31.45%)
More than high school	3499 (60.25%)	3227 (61.38%)	272 (49.45%)
Marital Status				<0.001
Married/Living with Partner	3410 (58.72%)	3135 (59.63%)	275 (50.00%)
Widowed/Divorced/Separated	1315 (22.65%)	1121 (21.32%)	194 (35.27%)
Never married	1082 (18.63%)	1001 (19.04%)	81 (14.73%)
Smoke status				<0.001
Now	1110 (19.11%)	911 (17.33%)	199 (36.18%)
Never	3162 (54.45%)	3025 (57.54%)	137 (24.91%)
Former	1535 (26.43%)	1321 (25.13%)	214 (38.91%)
Alcohol				<0.001
Yes	2802 (48.25%)	2469 (46.97%)	333 (60.55%)
No	3005 (51.75%)	2788 (53.03%)	217 (39.45%)
Hypertension				<0.001
Yes	3586 (61.75%)	3352 (63.76%)	234 (42.55%)
No	2221 (38.25%)	1905 (36.24%)	316 (57.45%)
Diabetes				<0.001
Yes	4734 (81.52%)	4356 (82.86%)	378 (68.73%)
No	1073 (18.48%)	901 (17.14%)	172 (31.27%)
CHD				<0.001
Yes	5537 (95.35%)	5072 (96.48%)	465 (84.55%)
No	270 (4.65%)	185 (3.52%)	85 (15.45%)

Results are shown as N (%) for binary variables, and as mean ± standard deviation (SD) for continuous variables. Bold values indicate p-value < 0.05.

NHANES, National Health and Nutrition Examination Survey; COPD, Chronic Obstructive Pulmonary Disease; PIR, Poverty Income Ratio; BMI, Body Mass Index; NPAR, Neutrophil percentage-to-albumin ratio;CHD,Coronary heart disease.

3. 2 Relationship Between NAPR and COPD

Table 2 presents the correlation between NAPR and COPD. The findings reveal a positive correlation between the NAPR index and COPD. In the unadjusted model, a one-unit increase in NAPR was associated with a 13% increase in the prevalence of COPD (OR=1.13; 95% CI: 1.09~1. 16, P<0.001). Model 1, which adjusted for gender, age, and race, showed a consistent relationship between NAPR and COPD (OR=1.10; 95% CI: 1.06~1.13, P<0.001). Even in the fully adjusted Model 2, which accounted for various factors including age, gender, race, education level, marital status, PIR, BMI, smoking status, drinking status, hypertension, diabetes, and coronary heart disease, the correlation between NAPR and COPD remained significant (OR=1.05; 95% CI: 1.01~1.08, P=0.007). Model 2 also revealed that individuals in the highest quartile of NAPR (Q4) had a 34% higher risk of developing COPD compared to those in the lowest quartile (Q1) (OR=1.34; 95% CI: 1.01~1. 77, P=0.039). Furthermore, the study observed a trend of increasing prevalence of COPD with higher NAPR levels (P for trend =0.015).

TABLE 2 The associations between NAPR and COPD

Exposure	Non-adjusted		Adjust I		Adjust II
Exposure	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value
NAPR	1.13 (1.09, 1.16)	<0.001	1.09 (1.06, 1.13)	<0.001	1.05 (1.01, 1.08)	0.007
Q1	Ref		Ref		Ref
Q2	1.07 (0.80, 1.43)	0.636	0.99 (0.73, 1.33)	0.926	0.96 (0.71, 1.31)	0.811
Q3	1.56 (1.19, 2.04)	0.001	1.24 (0.94, 1.65)	0.124	1.08 (0.81, 1.45)	0.584
Q4	2.41 (1.87, 3.10)	<0.001	1.79 (1.37, 2.33)	<0.001	1.34 (1.01, 1.77)	0.039
P for trend	<0.001		<0.001		0.015

Non-adjusted model adjust for: None ;

Adjust I model adjust for: Gender; Age ;Race;

Adjust II model adjust for: Gender;Age ; Race; Education level; Marital Status; Income to poverty ratio; BMI; Smoke status; Alcohol; Hypertension; Diabetes; Coronary heart disease；BMI was classified as normal (<25kg/m2), overweight (≥25kg/m2, <30kg/m2) and obese (≥30 kg/m2).

NPAR, Neutrophil percentage-to-albumin ratio;Ref, Reference; OR,odds ratio. 95%CI,95% confidence interval; Q1-4 respectively represent the groups divided according to the quantiles of NAPR.

3. 3 Smoothing Curve Fitting and Threshold Effect Analysis

A smoothing curve fitting model was utilized, revealing a non-linear correlation between NAPR and the prevalence of COPD, as illustrated in Figure 2. Below the inflection point of 16. 34, NAPR did not exhibit a statistically significant difference with COPD (OR=1.02, 95% CI: 0.96-1.07, P=0.577); however, above the inflection point, NAPR demonstrated a significant positive correlation with COPD (OR=1.20, 95% CI: 1.10-1.31, P<0.001). The results of the Log-likelihood ratio test further supported these findings (P=0.007) as shown in Table 3.

TABLE 3 Two-piecewise linear regression explained the threshold effect analysis of NAPR with COPD prevalence

NAPR		Adjusted β(95% CI), P-value
ULR Test		1.07 (1.03, 1.11) < 0.001
PLR Test	Inflection point	16.34
	NAPR < 16.34	1.02 (0.96, 1.07) 0.577
	NAPR ≥ 16.34	1.20 (1.10, 1.31) < 0.001
	LRT	0.007

Adjust for: Gender;Age ; Race; Education level; Marital Status; Income to poverty ratio; BMI;Smoke status; Alcohol; Hypertension; Diabetes; Coronary heart disease；BMI was classified as normal (<25kg/m²), overweight (≥ 25kg/m², < 30kg/m²) and obese (≥ 30 kg/m²).

NPAR, Neutrophil percentage-to-albumin ratio; ULR, univariate linear regression; PLR, piecewise linear regression; LRT, logarithmic likelihood ratio test; 95%CI,95% confidence interval; statistically significant: P = 0.007.

3. 4 Subgroup Analysis and Interaction Test

A subgroup analysis (Figure 3) was conducted to explore potential variations in the association between NAPR and COPD across different populations. Following adjustment for all covariates, NAPR showed a significant relationship with COPD incidence in subgroups including males, individuals aged over 40, those with a BMI < 25 kg/m2, former smokers, drinkers, and non-coronary heart disease patients (all P < 0.05). Moreover, irrespective of hypertension or diabetes status, the subgroup analysis revealed a notable correlation between NAPR and COPD incidence (all P < 0.05). Interaction tests indicated that age, gender, race, BMI, smoking status, drinking status, hypertension, diabetes, and coronary heart disease did not significantly impact this relationship (P for interaction > 0.05).

To our knowledge, there are currently very few studies on the relationship between NAPR and COPD. This is the first study based on representative national sample data to confirm the correlation between NAPR and COPD. In this observational study involving 5807 participants, we found a significant positive correlation between NAPR and COPD, suggesting that higher NAPR levels may increase the risk of COPD. Even after adjusting for covariates, the relationship remained stable, with each unit increase in NAPR associated with a 5% increase in COPD incidence (OR=1.05; 95% CI: 1.01-1.08, P=0.007). In the smoothing curve fitting, we observed a nonlinear correlation between NAPR and COPD in the entire study population. When NAPR was less than 16.34, the prevalence of NAPR gallstone disease remained stable; when NAPR was 16.34 or higher, NAPR was significantly positively correlated with COPD. Based on these results, the management of NAPR might reduce the occurrence of COPD. Additionally, subgroup analysis and interaction tests indicated that this correlation could be applied to different populations based on gender, age, race, BMI, smoking status, drinking status, and comorbidities.

Currently, numerous studies have explored the relationship between chronic inflammation, immune stress, and COPD[20, 21]. Research indicates that COPD is linked to chronic inflammation primarily affecting the lung parenchyma and peripheral airways, characterized by an increase in alveolar macrophages, neutrophils, T lymphocytes (specifically TC1, TH1, and TH17 cells), and innate lymphoid cells[22]. Despite being an effective inflammatory biomarker, no studies have yet explored the association between NAPR and the risk of COPD. Previous research has identified NAPR as an indicator for various diseases. For example, a study in China demonstrated a close relationship between NAPR levels and all-cause mortality in patients with chronic heart failure[14]. Lin et al found that NAPR is an independent predictor of all-cause mortality in critically ill patients with acute myocardial infarction[15]. Furthermore, numerous studies suggest that NAPR is not only associated with cardiovascular diseases but may also be related to several other diseases. One study investigated the association between NAPR and nonalcoholic fatty liver disease and advanced fibrosis in a non-diabetic population, finding that increased NAPR significantly raised the risk of nonalcoholic fatty liver disease and advanced fibrosis. [23]. He et al found that elevated NAPR is associated with an increased risk of diabetic retinopathy in diabetic patients[24]. Zhou et al discovered that NAPR is related to the risk of death in American community residents with COPD and outperforms other hematological inflammatory biomarkers in predicting 5-year all-cause mortality[25]. Therefore, we investigated the potential association between NAPR and COPD risk using data from the NHANES database. The results of the multivariate logistic regression model revealed a significant positive association between NAPR and the likelihood of developing COPD. This finding can be valuable in the clinical identification of COPD patients. Unlike the diagnosis of COPD, which necessitates pulmonary function tests, calculating NAPR simply involves determining the ratio of neutrophil percentage to albumin level. Given that complete blood count and albumin levels are routine tests, NAPR may offer greater feasibility compared to pulmonary function tests. As a result, NAPR could serve as a novel and convenient indicator of COPD prevalence, assisting clinicians in deciding whether further pulmonary function tests are necessary.

Our study results indicate a positive correlation between NAPR and the risk of COPD. However, the exact pathophysiological mechanisms of NAPR and COPD remain unclear. The potential pathophysiological mechanisms between NAPR and COPD may be closely related to the inflammatory response and systemic inflammatory state. From the perspective of NAPR, neutrophils play an important role in the inflammatory response. Firstly, chronic inflammation present in the airways and lung parenchyma, and the increase in neutrophils may reflect the degree of inflammatory response^26~28. Additionally, the activation of neutrophils can release specific inflammatory mediators such as neutrophil elastase and myeloperoxidase (MPO)[29]. Neutrophil elastase can stimulate the production and secretion of mucin, leading to mucus hypersecretion and airway obstruction, while MPO can promote oxidative tissue damage, initiate changes in cellular homeostasis, and increase the response of lung epithelial cells to pro-inflammatory stimuli, resulting in irreversible airway damage and promoting the pathophysiological progression of COPD[30, 31]. Albumin plays an important role in maintaining physiological homeostasis, nutritional metabolism, and anti-inflammatory effects[32, 33]. Hypoalbuminemia is closely associated with the risk of inflammatory response and malnutrition[34]. Under oxidative stress and chronic inflammatory conditions, albumin may be oxidized, leading to significant hypoalbuminemia, thereby participating in the pathogenesis of inflammatory diseases[35, 36]. COPD involves systemic inflammatory response and oxidative stress[37]. However, the exact mechanisms by which NAPR affects COPD require further research. Additionally, prospective studies and randomized trials are needed to validate these associations and explore the therapeutic significance of NAPR.

Our study has several key strengths. Firstly, we conducted comprehensive statistical analyses and included a large sample size to ensure precise measurement of NAPR and a thorough evaluation of COPD outcomes. Secondly, we considered several important confounding factors such as demographics, lifestyle habits, and underlying diseases to eliminate biases in the results. Thirdly, we validated the stability and reliability of our conclusions through subgroup analyses and interaction tests. However, our study also has some limitations. Firstly, the sample population was limited to Americans, so the findings cannot be generalized to other populations. Secondly, the participants' age range only included individuals aged 20 and above, excluding adolescents. Thirdly, the diagnosis of COPD was based on self-reports rather than more specific diagnostic methods, which might lead to recall bias. Lastly, as the study adopted a cross-sectional design, it is impossible to establish a causal relationship between NAPR exposure and COPD.

NAPR, a novel inflammatory biomarker, shows potential for predicting COPD risk in American adults aged 20 and above. Elevated levels of NAPR are linked to increased COPD prevalence. Nevertheless, further large-scale, long-term studies are necessary to validate these results. These future studies should delve deeper into the causal relationship between NAPR and COPD, as well as explore other potential influencing factors to improve the study's reliability and applicability.

NHANES, National Health and Nutrition Examination Survey;

COPD, chronic obstructive pulmonary disease;

SII, systemic immune inflammatory index;

NLR, neutrophil to lymphocyte ratio;

PLR, platelet to lymphocyte ratio;

CAR, c-reactive protein to albumin ratio ;

NPAR, Neutrophil-Percentage-to-Albumin Ratio;

ALB, serum albumin;

PIR, income to poverty ratio;

BMI, body mass index;

CHD,Coronary heart disease;

Ref, Reference;

OR: odds ratio;

95%CI: 95% confidence interval;

ULR, univariate linear regression;

PLR, piecewise linear regression;

LRT, logarithmic likelihood ratio test;

MPO: myeloperoxidase.

Data Availability

The data utilized in this study were procured from the NHANES database, a publicly accessible and complimentary resource (https://www.cdc.gov/nchs/nhanes).

Ethical Approval

The research involving human subjects was subjected to review and approval by the Ethics Review Board of the National Center for Health Statistics.

Informed Consent

Written informed consent was secured from all participants involved in the study.

Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Author Contributions

Yingming Liu: Writing – original draft, Data curation, Conceptualization. Ziming Wang: Writing – review & editing, Project admin istration, Data curation, Conceptualization. Yuhang Xia: Software. Yan Zhang: Methodology. Mingfei Li: Visualization, Data curation. Hao Chen: Formal analysis, Data curation. Shuang Zhao: Formal analysis, Data curation.Yun Lu: Writing – review & editing, Supervision, Project administration. Xiaoyan Yang: Writing – review & editing, Project administration.

Acknowledgements

The authors thank all the staff and participants in NHANES for their contribution of donation, collection and sharing data.

Funding

This research was supported by the Traditional Chinese Medicine Development Fund of Sichuan Province (CJJ2021051) and the Key Research Special Project of Traditional Chinese Medicine of the Administration of Traditional Chinese Medicine of Sichuan Province (2023zd003).

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No competing interests reported.

The Correlation between Neutrophil Percentage-to-Albumin Ratio and Chronic Obstructive Pulmonary Disease: A Cross-sectional Analysis Based On NHANES

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1 Introduction

2 Materials and methods

3. Results

4 Discussion

5 Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1