hp SUBMITTED 21 APR 22 1 REVISIONS REQ. 18 JUL & 9 AUG 22; REVISIONS RECD. 25 JUL & 28 AUG 22 2 ACCEPTED 20 SEP 22 3 ONLINE-FIRST: DECEMBER 2022 4 DOI: https://doi.org/10.18295/squmj.12.2022.062 5 6 Hematological and Inflammatory Biomarkers among Stable COPD and 7 Acute Exacerbations of COPD Patients 8 Ramya Priya A, *Madhusmita M. Mohapatra, Vinod K. Saka, Rakhee 9 Kar, Sunitha V. Chakkalakkoombil, Mahesh B. Vemuri 10 11 Department of Pulmonary Medicine, Jawaharlal Institute of Postgraduate Medical Education 12 and Research, Puducherry, India. 13 *Corresponding Author’s e-mail: drmadhusmita1@gmail.com 14 15 Abstract 16 Objectives: Chronic Obstructive Pulmonary Disease (COPD) is heterogeneous in nature. 17 Acute exacerbation of COPD (AECOPD) is diagnosed clinically which is subjective and 18 clinical judgment may vary from clinician to clinician. Since chronic inflammation underlies 19 the pathogenesis of COPD, markers of inflammation have generated lot of interest for their 20 potential to be used as biomarkers of COPD. This study aimed to assess the variation in 21 levels of neutrophil lymphocyte ratio (NLR) and platelet indices in patients with stable 22 COPD and acute exacerbation of COPD patients and its association with GOLD stages. 23 Methods: This prospective analytical study was carried out in our tertiary care hospital from 24 December 2018 to July 2020. About 64 subjects (32- stable COPD, 32- AECOPD) who 25 satisfied study criteria were included. Blood sample was taken from stable and AECOPD 26 patients and were compared. Results: It was observed that Neutrophil Lymphocyte Ratio, 27 Platelet Distribution Width, Erythrocyte Sedimentation Rate and C-Reactive Protein were 28 increased in AECOPD patients when compared with stable COPD patients which was 29 statistically significant with p value of <0.001. A positive correlation was observed between 30 Neutrophil Lymphocyte Ratio, Platelet Distribution Width and Erythrocyte Sedimentation 31 Rate, C-Reactive Protein which was statistically significant with p value of <0.001. 32 Conclusion: We found that neutrophil lymphocyte ratio and platelet distribution width values 33 increased significantly in AECOPD patients when compared to stable COPD patients. 34 Keywords: AECOPD; COPD; Neutrophil Lymphocyte Ratio; Platelet Distribution Width. 35 36 Advances in Knowledge 37  This study was done to assess levels of neutrophil lymphocyte ratio, platelet indices 38 and inflammatory biomarkers among stable chronic obstructive pulmonary disease 39 (COPD) patients and patients with acute exacerbation of chronic obstructive 40 pulmonary disease. 41  Since chronic inflammation underlies the pathogenesis of COPD, markers of 42 inflammation have generated lot of interest for their potential to be used as 43 biomarkers of COPD. There are few studies done in India to study the role of these 44 biomarkers in COPD patients. 45 46 Application to Patient Care 47  The stable COPD patients have low graded inflammation with increased 48 inflammatory protein levels and inflammatory cells. Whereas in exacerbation, 49 systemic inflammation worsens and higher levels of inflammatory proteins and cells 50 and mediators have been demonstrated. 51  Heightened inflammatory response is noted well before the clinical symptoms of 52 acute exacerbation period. 53  Even though acute exacerbation of COPD is a clinical diagnosis according to the 54 definitions provided in the literature, during routine follow up of COPD patients, 55 when elevated NLR is detected, it aids in early detection of acute exacerbation and 56 appropriate intervention. 57 58 Introduction 59 Chronic obstructive pulmonary disease (COPD) is one of the top three leading cause of 60 death worldwide. In 2012, about 3 million people died due to COPD accounting to 6% death 61 all over the world. Burden of COPD is likely to rise in the coming years because of increased 62 prevalence of smoking and smokeless tobacco use, aging, environmental pollution and other 63 risk factors. COPD is characterised by persistent respiratory symptoms and airflow limitation 64 that results secondary to airway and/or alveolar abnormalities caused mostly by significant 65 exposure to noxious particles or gases and can be influenced by host factors which include 66 abnormal lung development.1 67 68 From 1990 to 2016, prevalence of COPD has increased by 29%. In 2016, out of the total 69 deaths, 8.7% of deaths was attributed to COPD.2 It is a preventable and treatable disease with 70 considerable systemic and extra pulmonary effects. Frequent exacerbations of COPD not only 71 have serious impact on the severity and course of disease but also on the quality of life.3 72 Therefore, strategy for prevention, early diagnosis and treatment of COPD exacerbations is 73 essential to better address the disease. 74 75 Since chronic inflammation underlies the pathogenesis of COPD, markers of inflammation 76 have generated lot of interest for their potential to be used as biomarkers of COPD. There are 77 few studies done in India to study the role of these biomarkers in COPD patients.More 78 studies are needed to confirm their association with COPD. It will help in assessing 79 individualized risk stratification, disease severity and better management of COPD.4 Under 80 this perspective, The study aimed to assess levels of neutrophil lymphocyte ratio, platelet 81 indices and inflammatory biomarkers among stable COPD and acute exacerbation of chronic 82 obstructive pulmonary disease (AECOPD) patients and association of haematological 83 markers with GOLD staging. 84 85 Methods 86 This cross-sectional comparative study was conducted in department of pulmonary medicine 87 of a tertiary care centre for a period of 18 months from December 2018 to July 2020.Patients 88 aged ≥ 18 years with clinical and spirometry based diagnosis of COPD were recruited. Stable 89 COPD patients with or without inhaled medications and not on systemic steroid during the 90 last 3 months were recruited. AECOPD patients having aggravation of symptoms reported to 91 emergency were also recruited. Patients who were diagnosed and proven cases of asthma, 92 pneumonia, sepsis, pulmonary embolism and with obstructive sleep apnoea were excluded 93 from the study. Patients with autoimmune diseases, haematological malignancies and solid 94 tumours were also excluded as they were potential confounders. Demographic and clinical 95 details of the patients were noted in prerequisite data collection proforma. History of smoking 96 and biomass fuel exposure was obtained in a face-to-face interview. Patients with smoking 97 history were categorized as never smoker/current smoker/ex-smokers. Details of years of 98 biomass fuel exposure and details of the co-morbidities were also noted. Patients underwent 99 spirometry by JAEGER MASTER SCREEN PFT machine in spirometry laboratory placed in 100 pulmonary medicine department. Patients were given 400mcg of salbutamol by metered dose 101 inhaler and spirometry was repeated to get post bronchodilator value. Patients with post-102 bronchodilator FEV1/FVC ratio < 0.7 was included in the study and who were suspected to 103 have AECOPD underwent spirometry after stabilization following a period of six weeks if 104 possible and were included if their post bronchodilator FEV1/FVC < 0.7. Eligible COPD 105 patients meeting the inclusion criteria were subjected to chest X-Ray PA view and high 106 resolution computed tomography (HRCT) thorax in full inspiration at a later date when stable 107 to rule out alternative diagnosis and emphysema extent with PHILIPS 6 slice CT placed in 108 the department of radio diagnosis. Blood sample of 5ml was taken from stable COPD patients 109 during their outpatient visit. Patients who presented with AECOPD, blood sample of 5 ml 110 was taken within 1 hour of hospital admission or before administration of any treatment 111 whichever was the earliest. These blood samples were divided into two separate vials. A vial 112 with 2ml of blood was sent in ethylene diamine tetra acetate (EDTA) vials to department of 113 pathology for neutrophil-lymphocyte ratio, platelet indices and erythrocyte sedimentation rate 114 (ESR). The remaining 3 ml sample was taken in plain vials and serum was separated and kept 115 at -70°c. This centrifuged blood sample was used for estimating C- reactive protein (CRP) 116 values by ELISA. Neutrophil lymphocyte ratio (NLR), platelet indices including mean 117 platelet volume (MPV), platelet distribution width (PDW), ESR, CRP in both stable and 118 AECOPD patients were noted down. 119 120 Data was collected and spread in excel sheet. Statistical analysis was done using SPSS 121 version 19.4 Due to not normal distribution, NLR, MPV, PDW, ESR, CRP values were 122 presented as median and inter-quartile range. Continuous variables were expressed as mean 123 and standard deviation. The dependent variables (haematological parameters and 124 inflammatory biomarkers) were compared between stable COPD and AECOPD by two-tailed 125 t test. Karl Pearson correlation analysis was used to compare the correlation between NLR, 126 MPV, PDW (haematological parameters) with ESR and CRP (inflammatory biomarkers). 127 Confounders were analysed using multivariate regression analysis. 128 129 In a study done by Sharma et al, mean NLR levels in stable COPD group was 4.263±1.900 130 and in AECOPD group was 6.389±3.071.5 NLR measurement demonstrated a sensitivity and 131 specificity of 40%and 77.14%. Assuming a mean difference of 2.1, sample size was 132 calculated assuming a power of 80% as 32 patients in each group amounting to a total of 64 133 patients. 134 135 Results 136 A total of 106 patients were screened during the study period from December 2018 to July 137 2020. Eighteen stable COPD patients and 7 AECOPD patients were excluded from the study 138 as they did not fulfill the inclusion criteria. There was no statistically significant difference in 139 the age groups among stable COPD and AECOPD patients with a p value of 0.119. There 140 was male gender predilection in both stable AECOPD patients group. Majority of patients 141 belonging to both stable COPD and AECOPD groups were agricultural labourers. Majority of 142 patients with AECOPD were obese while majority of stable COPD had normal body mass 143 index. Baseline characteristics like gender, occupation, smoking index and biomass fuel 144 exposure were analysed with multivariate analysis and were found to have no significant 145 impact on the outcome of COPD with exacerbation status. 146 Mean FEV1 value for stable COPD patients was 44 ± 14.61 and for AECOPD patients was 147 37.37 ± 14.72. Mean FEV1/FVC value for stable COPD patients was 51.38 ± 11.04 and for 148 AECOPD patients was 51.35 ± 9.69. In our study, majority of stable COPD patients belonged 149 to ≤ 55years of age with mean age of 58.02 ± 8.07 and majority of AECOPD patients were of 150 ≥ 65 years age group with a mean age of 62.56 ± 10.03.In our study, median ± interquartile 151 range for NLR in stable COPD patients was (2.14 ± 0.97) and in AECOPD patients was (11.2 152 ± 9.42). Median ± interquartile range for MPV in stable COPD patients was (9.40 ± 1.05) and 153 in AECOPD patients was (13.657 ± 2.35). Median ± interquartile range for PDW in stable 154 COPD patients was (8.60 ± 1.33) and in AECOPD patients was (8.35 ± 0.85). 155 156 Statistically significant difference was noted for NLR and platelet distribution width (p < 157 0.001) between stable COPD patients and AECOPD patients.. Statistically significant 158 difference for ESR and CRP (p < 0.001) was found between stable COPD patients and 159 AECOPD. 160 161 Area under Receiver Operating Characteristic analysis obtained for NLR was 0.986 (98%) 162 with 95% confidence interval. It was noted that sensitivity and specificity of NLR for 163 predicting AECOPD were 94%and 94% respectively for the cut-off value of 3.79. The PDW 164 had an AUC of is 0.99 (99%) with 95% confidence interval and the sensitivity and specificity 165 was 93.8% and 93.7 % respectively for the cut-off value of 11.55. Area under Receiver 166 Operating Characteristic analysis obtained for CRP was 0.988 (98%). It was noted that 167 sensitivity and specificity of CRP were 97% and 97%, respectively, for the cut-off value of 168 14.15. 169 170 There was a positive correlation between NLR and Erythrocyte Sedimentation Rate with 171 correlation coefficient value of 0.489 (p< 0.001) and a positive correlation with C-Reactive 172 Protein with correlation coefficient value of 0.721 (p < 0.001). A positive correlation between 173 PDW and Erythrocyte Sedimentation Rate with correlation coefficient value of 0.518 (p< 174 0.001) and C - reactive protein with correlation coefficient value of 0.754 (p < 0.001) was 175 observed. Pearson correlation analysis and scatter plot showed negative correlation 176 which was not statistically significant between MPV and ESR (r - 0.146, P value of 177 0.251), between MPV and CRP (r -0.181 , P value of 0.151 ).9 178 The haematological markers like NLR, Mean Platelet Volume And Platelet distribution width 179 did not show any statistically significant difference in all the GOLD stages of COPD and 180 regression coefficient was not significant. 181 182 Discussion 183 During acute exacerbation of COPD, systemic inflammation worsens and higher levels of 184 inflammatory proteins, cells and mediators are secreted. These forms the basis for 185 development of neutrophil lymphocyte ratio as a marker to predict increased systemic 186 inflammation during the period of acute exacerbation.6 A total of 64 patients were recruited 187 of which 32 were stable COPD patients and 32 were AECOPD patients. Socio demographic 188 data, haematological and inflammatory biomarkers between the stable COPD patients and 189 AECOPD patients were compared and analyzed. In our study, it was observed that mean 190 neutrophil lymphocyte ratio among stable COPD patients was 2.32 ± 8.4 and among 191 AECOPD patients was 11.22 ± 5.88 which was statistically significant(p<0.001). Ercan 192 Kurtipek et al. did a cross sectional study on 94 male patients over 40 years.7 They observed 193 that NLR among stable COPD patients was 2.75 ± 1.11 and among AECOPD patients was 194 7.99±5.72. They proposed that mean NLR levels were higher in AECOPD patients when 195 compared to patients with stable COPD patients and the observation was statistically 196 significant. Their findings were similar to our results. From the systematic review, in 197 AECOPD, NLR cut-off value of 3.34 with a median AUC of 0.86 would help in diagnosis 198 with sensitivity of 80% and specificity of 86%.8 In our study, it was found that AUC obtained 199 for NLR was 0.986 (98%) with 95% confidence interval. It was noted that sensitivity of NLR 200 was 94%and specificity of 94% for the cut-off value of 3.79. It means that value of NLR ≥ 201 3.79 has 94% chance of predicting exacerbation in COPD patients. 202 203 Pearson correlation analysis and scatter plot showed positive correlation between NLR and 204 ESR (r 0.714, P < 0.000), between NLR and CRP (r 0.609, P < 0.000).9 205 206 Observed elevated levels of Willebrand factor, D-dimer, and prothrombin fragment- 1, 2 207 which are surrogate markers for inflammation, endothelial damage and clotting activation 208 respectively from various studies led to the concept that COPD exacerbation is associated 209 with systemic inflammation and is a prothrombotic state.10 In our study, it was observed that 210 mean platelet volume among stable COPD patients was 8.50± 0.84 and among AECOPD was 211 8.27 ± 0.56 which was not statistically significant (p- 0.189). Dentener et al. in 2001 212 proposed the idea that increased production of proinflammatory cytokines and acute phase 213 reactants during AECOPD interfere with megakaryopoiesis thereby reducing the size of 214 platelets in the bone marrow which is then released into the blood circulation.10 Thus explains 215 the fall in MPV in AECOPD when compared to stable COPD patients. 216 217 Pearson correlation analysis and scatter plot showed negative correlation which was not 218 statistically significant between MPV and ESR (r - 0.146, P value of 0.251), between MPV 219 and CRP (r -0.181 , P value of 0.151).9 220 221 The most widely used application of PDW is to provide information on the viability of 222 platelets which is to be transfused.12 Increase in PDW indicate that abnormally large and 223 small platelets are in circulation. Steiropoulos et al. reported no significance difference in 224 PDW amongst different stages of COPD.13 In our study, we observed that mean PDW was 225 9.48 ± 0.94 for stable COPD patients and 13.67 ± 1.43 for AECOPD patients. Statistically 226 significant difference was observed for PDW (p < 0.001) between stable COPD patients and 227 AECOPD patients. 228 229 Günay E et al. did retrospective study on 319 subjects with 269 COPD patients (178 stable 230 COPD patients, 91 AECOPD patients) and 50 were age and sex matched control group.14 231 They assessed the levels of NLR, MPV, PDW, RDW, CRP among three groups (control, 232 stable COPD and COPD with acute exacerbation patients). They also assessed the levels of 233 these parameters among GOLD stages of COPD. They observed that PDW levels were 234 similar in all 3 groups. So, further correlation of levels of PDW with CRP was not done.Our 235 study observed lower PDW values in stable and AECOPD patients. Variability could be due 236 to the presence or absence of underlying co-morbid conditions which was not noted in the 237 study by Günay E et al.14 In the meta-analysis by Ma et al., levels of MPV were compared 238 pair wise among control group, stable COPD group, AECOPD group.15 Also, correlations 239 between MPV level and levels of systemic inflammatory biomarkers such as high sensitivity 240 C-reactive protein (hs-CRP), C-reactive protein (CRP), white blood cells (WBC), neutrophils 241 were also compared. They concluded that levels of MPV cannot be used to discriminate 242 between patients with stable COPD group, AECOPD group, and control group. The study 243 could not find significant correlation between MPV levels and other inflammatory 244 biomarkers. The proposed hypothesis for this was MPV can be affected by multiple risk 245 factors like diabetes, hypertension, dyslipidemia, smoking.15 It was observed from our results 246 that mean value for MPV for stable COPD patients was 8.50 ± 0.84 and for AECOPD 247 patients was 8.27 ± 0.56. The difference of MPV value between stable COPD patients and 248 AECOPD patients was not statistically significant (p= 0.189). Ulasli et al. did a study on 47 249 patients with COPD and on 40 healthy subjects.16 In their study they observed that the mean 250 MPV levels for control, stable and acute exacerbation group was 9.3 ±0.8 fl, 9.3 ±1.4 and 8.6 251 ±1.0 fl. They suggested that MPV can be used as a negative acute phase reactant in 252 AECOPD.16 Our study is also in agreement that MPV falls during acute exacerbation. 253 254 It was observed that there was a positive correlation between PDW and ESR with correlation 255 coefficient value of 0.518 (p<0.001). Also, positive correlation was observed between PDW 256 and CRP with correlation coefficient value of 0.721 (p < 0.001). It was observed from the 257 current study that there was a positive correlation between NLR and ESR with correlation 258 coefficient value of 0.489 (p<0.001). Also, positive correlation was observed between NLR 259 and ESR with correlation coefficient value of 0.754 (p < 0.001). To our knowledge, 260 correlation between MPV levels and ESR has not been studied previously. We found that 261 Mean Platelet volume has negative correlation between ESR which was not statistically 262 significant (p value- 0.251) and also negative correlation was observed between MPV and 263 CRP which was not statistically significant (p value- 0.151).Wang et al. did study on 70 264 patients with AECOPD with age, sex matched controls.17 They compared levels of MPV, 265 CRP, WBC and fibrinogen between stable COPD patients and in patients with AECOPD. 266 They shared their observation that during acute exacerbation, levels of MPV were lower and 267 CRP values were higher. Thus, a statistically significant negative correlation was found 268 between MPV and CRP during the acute event (p<0.001).17 Though negative correlation 269 between MPV and CRP was observed in our results, it was not statistically significant. 270 Estimated sample size could not be attained due to pandemic and trends of haematological 271 parameters could not be analysed. 272 273 Conclusion 274 In our study, we assessed the utility of parameters like neutrophil lymphocyte ratio and 275 platelet indices (mean platelet volume, platelet distribution width) in stable COPD and 276 AECOPD patients. We found that neutrophil lymphocyte ratio and platelet distribution width 277 values increased significantly in COPD patients with acute exacerbation when compared to 278 stable COPD patients. Thus, these biomarkers which could be obtained from routine 279 hemogram can be used for predicting acute exacerbation in COPD patients. 280 281 Authors’ Contribution 282 RPA, MMM, VKS, RK and SVC conceptualized and designed the study. All authors 283 collected the data. RPA, VKS, RK, SVC and MBV analysed and interpreted the data. MMM 284 drafted the manuscript. All authors approved the final version of the manuscript. 285 286 Conflict of Interest 287 The authors declare no conflicts of interest. 288 289 Funding 290 No funding was received for this study. 291 292 References 293 1. 2021 GOLD Reports [Internet]. Global Initiative for Chronic Obstructive Lung Disease 294 - GOLD. [cited 2022 Feb 15]. Available from: https://goldcopd.org/2021-gold-reports/ 295 2. Salvi S, Kumar GA, Dhaliwal RS, Paulson K, Agrawal A, Koul PA, et al. The burden of 296 chronic respiratory diseases and their heterogeneity across the states of India: the Global 297 Burden of Disease Study 1990–2016. 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Respirol Carlton Vic. 2013 342 Nov;18(8):1244–8. 343 344 Table 1: Demographic details. 345 Variables Categories Stable COPD patients N = 32 AECOPD patients N= 32 P value Age ≤ 55 years 14(43.8) 8(25) 0.119 56-65 years 12(37.5) 11(34.4) ≥65 years 6(18.8) 13(40.6) Gender Male 31(96.9) 23(71.9) 0.006 Female 1(3.1) 9(28.1) Occupation Laborer 31(96.9) 22(68.8) 0.012 House wife 1(3.1) 9(28.1) Coal mine worker 0 1(3.1) Systemic Hypertension 5(15.6) 1(3.1) Diabetes Mellitus& systemic hypertension 1(3.1) 1(3.1) Thyroid disorder 1(3.1) 1(3.1) Systemic 0 1(3.1) hypertension and Thyroid disorder None 22(68.8) 25(78.1) BMI Underweight (<18.5) 3(9.4) 3(9.4) 3.841 Overweight (25-29.9) 4(12.5) 6(18.8) Obese (≥ 30) 12(37.5) 17(53.1) Normal (18.5-24.9) 13(40.6) 6(18.8) 346 Table 2: Distribution of haematological and inflammatory biomarkers among stable COPD 347 patients and COPD with acute exacerbation patients. 348 S.NO Haematological parameter Stable COPD patients (Median ± IQR) AECOPD patients (Median± IQR) P value 1. Mean Neutrophil Lymphocyte Ratio (2.14 ± 0.97) (11.24 ± 9.42) <0.001 2. Mean Platelet Volume (fl) (8.60 ± 1.33) (8.35 ± 0.85) 0.189 3. Mean Platelet Distribution Width (9.40 ± 1.05) (13.65 ± 2.35) <0.001 1. Erythrocyte Sedimentation Rate(mm/hr) (27 ± 23.25) (54 ± 10.25) <0.001 2. C-Reactive Protein(mg/dl) (5.95 ± 4.58) (22.3 ± 5.3) <0.001 349 Table 3: Correlation of haematological parameters (neutrophil lymphocyte ratio, Mean 350 Platelet Volume, Platelet distribution width) with GOLD stages of COPD. 351 Haematologic al parameter GOLD Stage(I) (N=1) GOLD Stage (II) (N=15) Range Mean±SD GOLD Stage (III) (N=29) Range Mean±SD GOLD Stage (IV) (N=19) Range Mean±SD F Value P value Neutrophil lymphocyte ratio 5.70 1.32-12.19 3.60 ± 3.42 1.02-23.65 7.36 ± 6.40 1.47-20.73 8.43 ± 6.80 1.996 0.124 Mean Platelet Volume 8.30 7.20-10.60 8.53 ± 0.91 7.40-9.60 8.31 ± 0.62 7.10-9.40 8.37 ± 0.72 0.295 0.829 Platelet Distribution Width 13.40 8.60-14.90 10.94± 1.96 8.20-15.90 11.58 ± 2.60 8.50-15.80 11.97 ± 2.52 0.692 0.561 352 353 Area Under the Curve Test Result Variable(s) Area MPV .403 PDW .991 ESR .878 CRP .988 N_L_ratio .986 Figure 1: Receiver Operating Characteristic analysis to evaluate the performance of 354 haematological parameters (Neutrophil Lymphocyte Ratio, Mean platelet Volume, Platelet 355 Distribution Width) and inflammatory biomarkers (Erythrocyte Sedimentation Rate, C-356 Reactive Protein). 357