Role of Red Blood Cell Distribution Width in the evaluation and follow-up of patients with achalasia

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Méndez-Hernández, Miguel Moreno-Fuentes, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5983523/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. Current studies demonstrate red blood cell distribution width (RDW) as a possible surrogate inflammation biomarker. Aim. To determine RDW in achalasia patients, compare it to GERD and healthy donor groups, and evaluate its clinical relevance. Methods . It was an ambispective study. One hundred sixty-one achalasia, 161 gastroesophageal reflux disease (GERD) patients, and 500 healthy donors (HD) were included and followed up 5 years. The achalasia and GERD patient groups were matched with the HD control groups by demographic characteristics and laboratory variables. The achalasia and GERD diagnosis were made with high-resolution esophageal manometry, upper gastrointestinal endoscopy, barium esophagogram, and 24-hour pH monitoring. For the achalasia group, correlation between RDW and clinical characteristics, Eckardt, EAT-10, GERD-HRQL questionnaire scores, achalasia types, gender, comorbidities, and integrated relaxation pressure were evaluated by logistic regression analysis between patients. Results. The RDW values at baseline differed significantly between patients (achalasia versus GERD) and these versus HD ( P <0.001). During follow-up, the achalasia group had significantly higher RDW values than the GERD ( P =0.031). The achalasia patients sustained increased RDW during follow-up compared to its baseline value (All: P =0.010; type I: P =0.006; type II: P < 0.001; female: P =0.003; men: P = 0.948). Conclusion. The results highlight the importance of RDW as an inflammatory marker, showing significant variation over time. This finding contrasts sharply with the stability of RDW observed in patients with GERD. Achalasia Red Cell Distribution Width (RDW) inflammatory disease integrated relaxation pressure (IRP) Figures Figure 1 Figure 2 Figure 3 Introduction Achalasia is a primary, chronic esophageal motility disorder characterized by aperistalsis and failure of the lower esophageal sphincter to relax. The pathophysiology of achalasia seems to involve an autoimmune process and a significant inflammatory component [ 1 – 3 ]. The characteristic distribution of cells and cytokines that promote an inflammatory microenvironment in the lower esophageal sphincter tissue supports this theory [ 4 , 5 ]. Flow cytometry, immunofluorescence, and RNA sequencing analysis helped to identify that achalasia patients suffer from systemic chronic low-grade inflammation with dysregulated immune cells and mediators associated with disease duration [ 4 , 6 – 8 ]. The low-grade inflammation has been proposed as an underlying pathophysiological mechanism linking risk factors or metabolic disorders (e.g., oxidative stress, obesity, diabetes, dyslipidemia), to an increased risk of chronic degenerative disease as well as a common pathogenic denominator in age-related diseases. Nonetheless, in most patients, complete blood count (CBC) is unaltered, or their alterations are related to other underlying pathologies [ 9 ]. In addition, no simple and clinically relevant biomarkers have been identified in the diagnostic approach and follow-up patients with achalasia. It underlines the need to strengthen research into the usefulness of clinical parameters obtained in routine laboratory tests. In this vein, beyond its widely established role in the approach to patients with anemia, the red blood cell distribution width (RDW) has been considered a promising inflammation biomarker. The red blood cells (RBCs) are non-nucleated cells characterized by having a typical oval biconcave shape, with a diameter of 6 to 8 µm and a thickness of 2 µm. The average volume of RBCs ranges from 80 to 100 femtoliter (fL), but different physiological and pathological conditions may increase the degree of anisocytosis. The RDW is a quantitative measure of variation in the size of circulating RBCs, which is receiving increasing interest as a diagnostic and prognostic marker in a vast array of human disorders, including autoimmune, inflammatory diseases, functional bowel conditions, COVID-19, various types of cancer and multiple hospital admissions in subjects with chronic conditions [ 10 – 11 ]. The RDW is calculated automatically by hematological analyzers by dividing the standard deviation (SD) of the mean corpuscular volume (MCV) by the MCV and multiplying by 100 to yield a percentage value. An RDW value below the reference range has been considered without clinical relevance. In contrast, an increased RDW value reflects a more significant difference in the size of RBCs, which can be due to the presence of smaller or larger RBCs or both. An elevated RDW usually results from increased or ineffective production of RBCs and excessive fragmentation or destruction of RBCs [ 12 ]. These studies suggest that altered RDW, indicating a higher level of systemic inflammation and oxidative stress, could be associated with worse outcomes and more severe in multiple pathologies [ 13 ]. Therefore, the purpose of this study was to explore the relationship between achalasia and RDW, to evaluate its utility in diagnosis, treatment, and follow-up, as well as to determine its association with the integrated relaxation pressure (IRP), defined as the average lowest pressure through the EGJ, a standardized manometric parameter to determine obstruction [ 14 – 15 ]. Materials and Methods Participant Characteristics This ambispective study was conducted at the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, a tertiary referral center, from 2013 to 2024. It was approved by our institute's medical ethics committee (Ref. No. 1522) following the principles of the 1989 Declaration of Helsinki. All patients participated voluntarily, and only those who provided written informed consent were included. One hundred sixty-one achalasia, 161 gastroesophageal reflux disease (GERD) patients, and 500 healthy donors were included. The control group was matched by demographic characteristics. The diagnosis of achalasia and GERD was made with a high-resolution esophageal manometry, upper gastrointestinal endoscopy, barium esophagogram, and 24-hour pH monitoring. Patients older than 18 years were included in the study. Patients with the following diagnoses were excluded: pregnancy, Chagas disease, esophageal stricture, scleroderma, gastric cancer, esophageal cancer, peptic stricture, other esophageal motility disorders, severe hematologic, renal or hepatic disease, as well as patients on anticoagulant, aspirin or steroid therapy. Patients' clinical records were carefully reviewed according to a pre-established protocol. The following data were collected retrospectively for each study participant from the hospital's medical records: demographic features, clinical characteristics, type of achalasia, family history of autoimmunity, and current diagnosis of organ or systemic autoimmunity. When a comorbid autoimmune diagnosis was found in patients with achalasia, all relevant data (i.e., date of diagnosis, presenting symptoms, clinical and laboratory confirmatory test results, and treatment administered) were recorded. Finally, chronic inflammatory conditions (i.e., asthma, allergic rhinitis, gout, and rosacea) were recorded in the achalasia group. CBC parameters used in the study were the latest laboratory findings recorded before and five years after surgical intervention. For comparison, 500 healthy volunteers at the blood bank were recruited as controls for the study. All included controls had not previously known cardiovascular, metabolic, inflammatory, or neoplastic disease. Demographic and laboratory variables were also collected for this group. Laboratory information All CBC analyses were performed with an automatic hematologic analyzer (Beckman coulter DxH 800 Hematology Analyzer). Hemoglobin (Hb), RDW, white blood cell (WBC), neutrophils, lymphocytes, monocytes, eosinophils, and platelet counts were obtained. Blood samples were collected in dipotassium ethylenediaminetetraacetic acid tubes. Clinical evaluation Following a diagnosis of achalasia, patients were asked to complete three standardized and validated questionnaires: the Eckardt symptom score, the Eat Assessment Tool-10 (EAT), and the Gastroesophageal Reflux Disease-Related Quality of Life (GERD-HRQL). These instruments are designed to assess the frequency and severity of symptoms associated with esophageal disease. IRP from manometry was collected in achalasia patients to indicate disease severity [16]. Statistical analysis Descriptive statistics were performed. The Shapiro-Wilk test was used to evaluate the normality of the data. Continuous parameters were expressed as mean ± standard deviation (SD). Continuous variables, including age, BMI, disease evolution, questionnaires, neutrophil to lymphocyte ratio (NLR), RDW, platelets, hemoglobin, and IRP, were performed using the Kruskal–Wallis one-way ANOVA on ranks. All the pairwise multiple comparison procedures were done using the Dunn or Holm–Sidak method. Qualitative parameters were expressed as numbers and percentages. Categorical variables were compared using the 𝜒2 test or Fisher's exact test. Pearson's correlation coefficient was used to assess the correlation between hematologic indices, clinical questionnaire scores, and HRM parameters in the distribution of RDW values between all cases and controls and between achalasia subtypes. Linear regression analyses were also performed to explore the relationship between RDW and sex, the prevalence and incidence of autoimmune and inflammatory diseases, and IRP, which are closely associated with symptomatic severity. A P -value < 0.05 was considered statistically significant for all analyses. These were performed using JASP software version 0.19 for Mac OS Sonoma 14.5. Results Demographic and clinical characteristics Sixty-six percent of achalasia patients were female, with a mean age of 48 years and a preoperative mean body mass index of 23 kg/m 2 (Fig. 1 A-C). At diagnosis, 99% of patients had dysphagia, 92% had regurgitation, and 88% had weight loss. The prevalence of autoimmune comorbidity was 19% (Fig. 2A), inflammatory comorbidity was 22% (Fig. 2B), and neurological comorbidity was 3% (Fig. 2C) in patients with achalasia (Table 1 ). Table 1 Demographic and clinical characteristics and laboratory variables Healthy Donors (n = 500) GERD (n = 161) Achalasia Total (n = 161) Achalasia Male (n = 54) Achalasia Female (n = 107) Type I Achalasia (n = 60) Type II Achalasia (n = 101) Demographics Age (years), mean ± SD Median Range 36.6 ± 11.7 36 18–63 49.9 ± 11.1 50 18–66 47.9 ± 15.0 49.0 22–64 47.2 ± 14.6 47.5 22–76 48.3 ± 15.3 50.0 24–86 48.5 ± 14.5 49.5 24–83 47.2 ± 15.4 48.0 22–86 Sex, Female (%) Male (%) 315 (63) 185 (37) 107 (66) 54 (34) 107 (66) 54 (34) 0 (0) 54 (100) 107 (100) 0 (0) 31 (51) 29 (48) 74 (75) 24 (24) Disease evolution (mo), mean ± SD Median Range ND ND 30.3 ± 41.5 13.0 1–288 33.0 ± 53.1 13.0 2–288 28.9 ± 34.5 13.0 1–156 39.3 ± 55.3 18.0 1–288 25.2 ± 30.0 12.0 1–156 Body mass index (kg/m 2 ) mean ± SD Median Range ND 26.8 ± 5.1 27.5 17.0–45.7 23.0 ± 4.5 22.5 14.9–36.8 23.0 ± 3.8 23.4 16.1–32.0 22.9 ± 4.7 21.9 14.9 ± 36.8 23.1 ± 4.2 23.0 14.9–35.6 22.9 ± 4.7 21.8 16.1–36.8 Clinical Dysphagia (%) ND ND 160 (99) 53 (98) 107 (100) 59 (98) 98 (100) Regurgitation (%) ND ND 148 (92) 48 (88) 100 (93) 56 (93) 91 (92) Weight loss (%) ND ND 142 (88) 48 (88) 94 (87) 55 (91) 85 (86) Heartburn (%) ND ND 104 (64.5) 29 (53) 75 (70) 39 (65) 65 (66) Autoimmune disease (%) ND ND 30 (19) 6 (11) 24 (23) 9 (15) 21 (21) Inflammatory disease (%) ND ND 35 (22) 9 (17) 26 (25) 12 (20) 23 (23) Neurological disease (%) ND ND 6 (3) 2 (3) 4 (3) 2 (3) 4 (4) Questionnaires GERD-HQRL, mean ± SD Median Range ND ND 24.3 ± 12.7 22.0 0–48 22.3 ± 13.2 21.5 2–47 25.4 ± 12.4 23.0 0–48 25.6 ± 13.7 22.0 2–47 23.6 ± 12.0 23.0 0–48 EAT-10, mean ± SD Median Range ND ND 29.9 ± 9.0 33.5 1–43 28.0 ± 9.8 30.0 1–40 31.0 ± 8.4 35.0 4–43 30.0 ± 8.3 32.0 1–40 29.9 ± 9.6 34.0 4–43 ECKARDT, mean ± SD Median Range ND ND 9.1 ± 2.2 9.0 2–12 8.9 ± 2.5 9.0 2–12 9.2 ± 2.1 10.0 4–12 9.3 ± 2.4 10.0 2–12 9.0 ± 2.1 9.0 3–12 Laboratory variables Hemoglobin (g/dL), mean ± SD Median Range 15.3 ± 1.1 15.3 13.3–18.6 14.4 ± 1.8 14.5 5.7–19.6 14.6 ± 1.5 14.5 10.0–18.2 15.7 ± 1.2 15.8 13.6–18.2 14.0 ± 1.3 14.2 10.0–17.5 14.8 ± 1.6 14.7 10.0–17.9 14.5 ± 1.5 14.5 10.1–18.2 RDW (%), mean ± SD Median Range 10.4 ± 0.5 10.4 8.9–13.7 13.6 ± 0.7 13.5 12.8–15.0 13.6 ± 0.7 13.5 12.6–14.4 13.7 ± 0.8 13.5 12.5–16.0 13.8 ± 1.2 13.5 12.3–20.5 13.9 ± 1.2 13.6 12.3–20.5 13.7 ± 1.0 13.6 12.5–17.8 Platelets 10^3 / µL, mean ± SD Median Range 275 ± 52 271 144–460 263 ± 60 258 108–499 242 ± 58 240 135–427 222 ± 41 223 150–326 250 ± 64 244 135–427 238 ± 53 231 145–392 244 ± 61 244 135–427 Leukocytes 10^3 / µL, mean ± SD Median Range 7.0 ± 1.5 6.9 3.6–11.2 6.7 ± 2.4 6.5 2.8–23.1 6.54 ± 1.9 6.3 2.9–12.4 6.6 ± 1.7 6.6 3.6–11.4 6.5 ± 1.9 6.1 2.9–12.4 6.4 ± 2.0 6.1 2.9 ± 11.4 6.6 ± 1.8 6.6 3.5–12.4 Lymphocytes (%), mean ± SD Median Range 33.4 ± 7.1 32.8 15.8–55.8 30.5 ± 9.1 29.7 2.5–50 29.6 ± 9.2 29.6 5.5–54.9 29.3 ± 9.7 29.6 10.9–54.9 29.7 ± 9.0 29.6 5.5–50.6 29.5 ± 9.4 29.7 10.9–47.0 29.6 ± 9.3 29.6 5.5–54.9 Monocytes (%), mean ± SD Median Range 7.4 ± 1.4 7.3 3.5–14.2 7.6 ± 2.5 7.4 2.1–28.0 7.1 ± 1.8 7.0 1.0–13.6 7.5 ± 1.4 7.6 4.7–11.9 6.9–2.0 6.8 1.0–13.6 7.7 ± 1.7 7.6 4.4–13.6 6.8 ± 1.8 6.8 1.0–13.0 Eosinophils (%), mean ± SD Median Range 2.3 ± 1.8 1.8 0.0–22.6 2.1 ± 1.6 1.9 0–13.0 2.4 ± 2.2 1.9 0.0–13.0 2.7 ± 2.4 2.2 0.1–13.0 2.2 ± 2.0 1.7 0.0–13.0 2.7 ± 2.7 2.1 0.1–13.0 2.2 ± 1.8 1.8 0.0–12.0 Basophils (%), mean ± SD Median Range 1.0 ± 0.6 1.0 0.2–12.0 0.64 ± 0.4 0.60 0–13.0 0.6 ± 0.4 0.6 0.0–5.0 0.5 ± 0.3 0.6 0.0–2,0 0.6 ± 0.5 0.6 0.0–5.0 0.6 ± 0.4 0.6 0.0–2.0 0.6 ± 0.5 0.6 0.0–5.0 Neutrophils (%), mean ± SD Median Range 56.0 ± 7.7 56.2 31.7–77.0 58.9 ± 10.5 58.7 31–91.4 59.1 ± 11.2 59.4 6.1–92.4 59.6 ± 10.8 59.4 33.0–79.1 58.8 ± 11.4 59.4 6.1–92.4 58.7 ± 10.4 58.6 37.0–78.5 59.3 ± 11.9 59.4 6.1–92.4 CRP (mg/dL), mean ± SD Median Range ND 0.77 ± 1.2 0.36 0.09–3.6 0.57 ± 1.0 0.23 0.02–4.24 0.4 ± 0.6 0.1 0.02–3.2 0.3 ± 0.7 0.1 0.02–4.7 0.3 ± 0.6 0.1 0.02–3.2 0.4 ± 0.7 0.1 0.02–4.7 In the 5-year postoperative follow-up in patients with achalasia, body mass index increased by 12%, dysphagia decreased by 67%, regurgitation by 82%, and weight loss by 83%. The prevalence of autoimmune comorbidity increased from 19 to 25%, inflammatory comorbidity from 22 to 30%, and neurological comorbidity from 3 to 6% (Table 2 ). Table 2 Demographic, clinical, and laboratory variables at follow-up (60 months) GERD (n = 161) Achalasia Total (n = 161) Achalasia Male (n = 54) Achalasia Female (n = 107) Type I Achalasia (n = 60) Type II Achalasia (n = 101) Demographics Age (years), mean ± SD Median Range 47 ± 12.1 48 22–88 48.3 ± 15.5 49.0 19–84 47.5 ± 16.1 47.5 19–84 48.7 ± 15.2 49 21–84 48.3 ± 15.7 43.5 19–84 47.0 ± 15.4 44.0 21–81 Body mass index (kg/m 2 ) mean ± SD Median Range 27.5 ± 5.3 27.4 17.3–45.7 26.1 ± 6.3 25.2 16.5–66.6 26.6 ± 7.5 25.5 16.5–66.6 25.9 ± 5.5 25.2 16.7–45.3 25.3 ± 4.7 25.2 16.5–36.4 26.6 ± 7.1 25.3 17.5–66.6 Clinical Dysphagia (%) ND 48 (32) 17 (32) 31 (31) 15 (27) 33 (35) Regurgitation (%) ND 27 (17) 11 (20) 16 (16) 11 (20) 16 (16) Weight loss (%) ND 15 (15) 6 (15) 9 (14) 8 (18) 6 (11) Weight gain (%) ND 71 (73) 27 (71) 44 (74) 30 (68) 41 (78) Heartburn (%) ND 37 (24) 16 (30) 21 (21) 14 (25) 23 (24) Autoimmune disease (%) ND 41 (25) 9 (16) 32 (30) 11(19) 30 (31) Inflammatory disease (%) ND 48 (30) 13 (25) 35 (33) 18 (30) 30 (31) Neurological disease (%) ND 10 (6) 2 (3) 9 (9) 2(3) 8 (8) Questionnaires GERD-HQRL, mean ± SD Median Range ND 4.3 ± 5.3 3.0 0–26 3.5 ± 5.6 1.0 0–26 4.7 ± 5.1 3.5 0–23 3.1 ± 4.8 0.0 0–18 5.1 ± 5.6 4.0 0–26 EAT-10, mean ± SD Median Range ND 2.7 ± 4.4 1.0 0–24 2.6 ± 5.0 1.0 0–24 2.7 ± 4.1 1.0 0–19 2.2 ± 3.6 1.0 0–14 3.0 ± 4.9 1.0 0–24 ECKARDT, mean ± SD Median Range ND 1.7 ± 1.5 1.0 0–8 1.6 ± 1.6 1.0 0–8 1.7 ± 1.4 1.0 0–0.6 1.8 ± 1.1 2.0 0–4 1.6 ± 1.7 1.0 0–0.8 Laboratory variables Hemoglobin (g/dL), mean ± SD Median Range 14.6 ± 1.8 14.7 5.7–19.6 14.0 ± 2.0 14.0 6.1–18.2 15.7 ± 1.4 16.0 12.4–18.2 13.3 ± 1.9 13.5 6.1–17.4 14.2 ± 2.3 14.3 6.1–18. 13.9 ± 1.9 14.0 6.1–17.9 RDW (%), mean ± SD Median Range 13.7 ± 0.8 13.6 12.7–14.3 14.7 ± 1.9 13.9 12.6–26.5 13.8 ± 1.2 13.5 12.3–18.2 15.4 ± 2.8 14.3 12.3–26.5 15.2 ± 3.0 14.0 12.7–26.5 15.0 ± 2.3 14.2 12.3–25.1 Platelets 10^3 / µL, mean ± SD Median Range 254 ± 62 255 108–476 245 ± 58 242 128–433 29 ± 47 230 150–348 251 ± 61 249 128–433 241 ± 63 242 129–433 248 ± 56 243 128–372 Leukocytes 10^3 / µL, mean ± SD Median Range 6.7 ± 2.4 6.5 2.8–23.1 6.3 ± 2.3 6.0 3.0–21.6 6.8 ± 3.1 6.2 3.7–21.6 6.2 ± 2 5.9 3–13.8 6.6 ± 2.2 6.4 3.4–13.8 6.2 ± 2.4 5.9 3.0–21.6 Lymphocytes (%), mean ± SD Median Range 30.5 ± 9.1 29.7 2.5–50.0 29.3 ± 8.8 29.8 3.0–54.5 28.3 ± 10.5 30.3 3.0–54.5 29.7 ± 8.2 29.7 7–47.8 28.7 ± 10.4 30.0 5.1–54.5 29.6 ± 8.1 29.4 3.0–43.1 Monocytes (%), mean ± SD Median Range 7.7 ± 2.5 8 3.6–28 7.6 ± 2.4 7.4 2.0–22.0 8.1 ± 1.7 8.0 4.5–12.4 7.4 ± 2.5 7.1 2.0–22.0 7.5 ± 2.05 7.7 2.0–12.2 7.6 ± 2.6 7.3 4.0–22.0 Eosinophils (%), mean ± SD Median Range 2.1 ± 0 1.9 0- 12.8 3.2 ± 6.8 2.1 0.0–75.0 2.9 ± 2.2 2.4 0.0–9.2 3.3 ± 7.9 2.0 0.0 75 4.6 ± 11.1 2.3 0.0–75.0 2.4 ± 2.2 1.9 0.0–12.8 Basophils (%), mean ± SD Median Range 0.6 ± 0.4 0.6 0–3.4 0.6 ± 0.3 0.6 0.0–2.3 0.6 ± 0.3 0.6 0.1–1.2 0.6 ± 0.3 0.5 0.0–2.3 0.6 ± 0.4 0.6 0.0–2.3 0.5 ± 0.3 0.5 0.0–1.6 Neutrophils (%), mean ± SD Median Range 57.8 ± 12.5 57.6 3.6–91.4 58.4 ± 11.5 58.8 8.1–90.2 57.3 ± 13.6 58.9 8.1–90.2 58.8 ± 10.7 58.7 12–85.9 57.1 ± 15.6 58.7 8.1–90.2 59.1 ± 8.7 59.1 43.0–81.9 CRP (mg/dL), mean ± SD Median Range ND 0.5–1.0 0.2 0.02–4.2 0.9 ± 1.8 0.08 0.05–4.2 0.4 ± 0.8 0.2 0.02–3.9 0.9 ± 1.8 0.2 0.02–4.24 0.5 ± 0.9 0.2 0.03–3.9 Achalasia patients increase body mass index after myotomy. Achalasia patients, regardless of type and sex, have a significantly lower preoperative body mass index than the GERD group ( P < 0.001; (Fig. 1 A-C). However, this difference disappears during follow-up (Fig. 1 A-C). The integrated relaxation pressure in patients with achalasia during the 5-year follow-up is within normal parameters regardless of the type of achalasia and the patient sex after surgical intervention Achalasia patients showed abnormal IRP at baseline. Type II achalasia had a higher IPR than type I ( P < 0.001, Fig. 1 G). At 5-year follow-up, notwithstanding the achalasia type or patient sex, the IRP decreased to normal parameters after surgical intervention (IRP < 15 mmHg; P < 0.001, Fig. 1 G). Achalasia is associated with a higher neutrophil-to-lymphocyte ratio than healthy individuals Patients with achalasia ( P < 0.001, Fig. 1 D), regardless of type (type I: P = 0.047; and type II: P = 0.005; Fig. 1 E) and sex (Female: P = 0.006; and Male: P = 0.040; Fig. 1 F), had a higher neutrophil-to-lymphocyte ratio than healthy individuals. NLR ratio increased slightly during follow-up (Fig. 1 D-F). No differences were determined with the GERD group. The prevalence of autoimmune, inflammatory, and neurological diseases increases in patients with achalasia during 5-year follow-up The prevalence of autoimmune diseases in the achalasia group was 25%, in type I achalasia 19%, in type II 31%, in the female group 30%, and in the male group 16%. The most significant increases occurred in type II achalasia and female patients (Fig. 2A). Regarding inflammatory diseases, the prevalence in the achalasia group was 30%, in type I 30%, in type II 31%, in women 33%, and in men 30%. The most significant increase occurred in type I achalasia patients (Fig. 2B). Finally, neurological diseases increased from 3 to 6% (basal vs 5-year follow-up) in the achalasia group, and this was subrogated to patients with achalasia type II and female gender (Fig. 2C). Symptom assessment in achalasia patients at five years of follow-up post-myotomy decreases to clinically significant scores According to the international standardized and validated questionnaires, the Eckardt score, used for the evaluation of symptoms and efficacy of the treatment, the EAT-10 measures swallowing difficulties, and the GERD-HRQL, which measures GERD symptoms, at five years after myotomy, patients with achalasia had a significant improvement compared to baseline ( P < 0.001, (Fig. 2CD-F). More remarkable recovery was determined in the GERD-HRQL score in type I compared to type II achalasia ( P = 0.005, Fig. 2D) and in the male vs. female group ( P = 0.05, (Fig. 2D). Achalasia patients have alterations in RDW, hemoglobin, and platelets, which are persistent during follow-up. Baseline hemoglobin concentration in achalasia and GERD patients was decreased compared to healthy individuals ( P < 0.001; (Fig. 3 A), and it was associated with a decrease in females ( P < 0.001; Fig. 3 C) and type II achalasia ( P < 0.001; Fig. 3 B) but not in males or type I achalasia. The decrease in hemoglobin became even higher during follow-up compared to baseline in female patients ( P = 0.003, Fig. 3 C) and type II achalasia ( P = 0.029, Fig. 3 B). Meanwhile, in men, hemoglobin remained within normal parameters ( P < 0.001; Fig. 3 C). The RDW at baseline was significantly higher in the GERD and achalasia patient groups than in healthy donors ( P < 0.001; Fig. 3 D). Achalasia Type I and II and female and male groups had a significantly higher erythrocyte distribution width than healthy donors ( P < 0.001; Fig. 3 D). During follow-up, the RDW increased significantly in achalasia type I ( P = 0.006; Fig. 3 E), type II ( P < 0.001; Fig. 3 E), and in the female group ( P = 0.006; Fig. 3 F) concerning their respective baseline value. In the male group, the RDW remained unchanged during the follow-up (Fig. 3 F). This increase suggests that RDW changes over time in response to the natural evolution of the disease, which affects only the female group, regardless of the type of achalasia. In contrast, RDW in GERD patients showed no significant differences between the time of diagnosis and follow-up, indicating that RDW in this population remains stable. The baseline platelet cell number in the GERD and achalasia types I and II, male and female patient groups, was significantly lower than in the healthy individual group ( P < 0.001; Fig. 3 G). Predictive value of clinical characteristics A 5-year linear regression analysis was performed to examine the influence of sex and autoimmune disease on RDW alterations. In achalasia patients, both sex and autoimmune comorbidities influenced the increase in erythrocyte distribution width (Table 3 ). Table 3 Linear Regression Model Summary- RDW Achalasia at follow-up (%) Model R R 2 Adjusted R 2 RMSE R 2 Change df1 df2 p Sex – Follow-up M 0 0.000 0.000 0.000 2.552 0.000 0 132 M 1 0.213 0.045 0.038 2.503 0.045 1 131 0.014 Note. M 1 includes Sex Autoimmune disease – Follow-up Model R R 2 Adjusted R 2 RMSE R 2 Change df1 df2 p M 0 0.000 0.000 0.000 2.552 0.000 0 132 M 1 0.181 0.033 0.026 2.520 0.033 1 131 0.037 Note. M 1 includes Autoimmune disease However, the strongest association was determined between IRP and RDW in achalasia patients. It was statistically significant between baseline and follow-up, with a coefficient of determination (R²) of 0.762 and a P value < 0.001 (Table 4 ). The coefficient of IRP was 0.384 (± 0.020), indicating that a high IRP is associated with a higher RDW. This finding reinforces the relevance of IRP as a tangible parameter to assess the severity of achalasia, closely associated with the patient's symptoms. Table 4 Linear Regression – IRP – Baseline Model Summary- RDW Achalasia at baseline (%) Model R R 2 Adjusted R 2 RMSE R 2 Change df1 df2 p M 1 0.873 0.762 0.760 6.753 0.762 1 119 < 0.001 Note. M 1 includes IRP at baseline. Discussion RDW is a simple and inexpensive clinical test that can be performed in any laboratory. However, clinicians barely use it when analyzing hemograms, maybe because physicians are not used to these meaningful parameters. Anisocytosis could be due to inflammation, nutritional status, iron deficiency, inadequate erythropoietin production, or even oxidative stress. It can lead to tiredness, shortness of breath, dizziness, headache, cold hands and feet, pale skin, and chest pain [ 17 ]. RDW seems to be a surrogate parameter of the inflammatory process, like the erythrocyte sedimentation rate. In our view, the mechanism by which inflammation may increase RDW in patients with achalasia is through ineffective erythropoiesis mediated by cytokines, as has been demonstrated in the pathophysiology of other diseases, where TNF-α, IL-6, and IL-1β impair erythrocyte maturation. These cytokines could modulate erythropoiesis through the following pathways: (i) inhibiting erythropoietin (EPO) gene transcription, (ii) blocking antiapoptotic and maturation effects of EPO, and iii) decreased renal EPO synthesis by inflammatory cytokines desensitization of EPO erythroid progenitors in bone marrow [ 18 ]. Even more, these cytokines could directly inhibit the mean lifespan of erythrocytes and their membrane deformity. Therefore, inflammation could contribute to anisocytosis through damage in erythrocyte maturation induced by EPO and immature erythrocyte release to peripheral blood, thus increasing RDW. In the sera of achalasia patients, we have determined increased levels of TNF-α and IL-6 compared with healthy donors ( data not shown ), suggesting that this systemic inflammation could contribute to the increase in RDW. In this study, RDW was positively correlated with ultrasensitive CRP, and it predicted an increase in RDW level in a multivariate analysis independent of age, gender, and hemoglobin ( P = 0.003). It was also determined that female patients had higher levels of RDW and that these were associated with a higher IRP. At the same time, a linear analysis demonstrated the influence of sex and autoimmune disease on RDW alterations. The results highlight the importance of RDW as a relevant marker in evaluating women with diagnosis of achalasia and type II achalasia patients, showing significant variation over time. This finding contrasts clearly with the stability of RDW observed in patients with GERD. The variation between baseline RDW and after follow-up in achalasia suggests that the RDW may reflect changes in disease activity and its natural evolution. However, it is essential to consider each patient's characteristics and comorbidities. The stability of RDW in patients with GERD may be due to differences in pathophysiology between achalasia and GERD. Furthermore, the association between RDW and IRP underlines the usefulness of RDW as a potential indicator of disease severity. Therefore, the positive correlation with IRP suggests that RDW could be a complementary tool in the assessment of achalasia patients. This relationship also indicates that alterations in red blood cells associated with systemic inflammation could offer additional insight into the progression and prognosis of patients with achalasia. Moreover, having a low-cost biomarker might allow the determination of low-grade inflammation, which has been demonstrated to contribute to the development of metabolic disorders (e.g. obesity, diabetes, dyslipidemia), and an increased risk of chronic degenerative disease as well as a common pathogenic denominator in age-related diseases. This could influence the design of therapeutic strategies that allow long-term control of inflammation and thus avoid a worse disease prognosis. The advantages of using RDW are that it does not represent an additional charge and seems unaltered by infectious processes in the short term, as may occur with ESR and CRP. On the other hand, limitations to be considered when interpreting RDW are that it is equipment- and laboratory-dependent; that is, each piece of equipment is calibrated with a different frequency histogram, and each lab defines its standard rate. Moreover, RDW could be modified by many medical conditions, including hepatic disease, anemia, and deficiencies of folate and vitamin B12 [ 19 ]. Conclusion This study determined that RDW is a marker associated with the underlying inflammation in patients with achalasia. Additionally, the positive correlation between RDW and IRP suggests its usefulness in clinical assessment as a valuable and easily determined tool for the follow-up of patients with achalasia. However, future prospective studies are required to consolidate its role as a prognostic marker in achalasia. Declarations Conflict of interest The authors declare no conflicts of interest relevant to this study. Ethical approval This is an observational study. This study was approved by the Institutional Review Board of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (Ref. No. 1522). Author Contribution D.A.-L., D.P.M.-H., M.M.-F., J.F.-C., G.T.-V. Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing, E.C.-A., L.R.V.-G., M.A.V. Data curation, Formal analysis, Writing – review & editing. Data Availability Data are available on request from the authors. References Furuzawa-Carballeda J, Aguilar-León D, Gamboa-Domínguez A, Valdovinos MA, Nuñez-Álvarez C, Martín-del-Campo LA, Enríquez AB, Coss-Adame E, Svarch AE, Flores-Nájera A, Villa-Baños A, Ceballos JC, Torres-Villalobos G. Achalasia--An Autoimmune Inflammatory Disease: A Cross-Sectional Study. J Immunol Res . 2015;2015:729217. Goyal RK, Rattan S. Role of mechanoregulation in mast cell-mediated immune inflammation of the smooth muscle in the pathophysiology of esophageal motility disorders. Am J Physiol Gastrointest Liver Physiol. 2024;326(4):G398-G410. Romero-Hernández F, Furuzawa-Carballeda J, Hernández-Molina G, Alejandro-Medrano E, Núñez-Álvarez CA, Hernández-Ramírez DF, Azamar-Llamas D, Olivares-Martínez E, Breña B, Palacios A, Valdovinos MA, Coss-Adame E, Ramos-Ávalos B, Torres-Landa S, Hernández-Ávila AA, Flores-Nájera A, Torres-Villalobos G. Autoimmune comorbidity in achalasia patients. J Gastroenterol Hepatol. 2018;33(1):203-208. López-Verdugo F, Furuzawa-Carballeda J, Romero-Hernández F, Coss-Adame E, Valdovinos MA, Priego-Ranero A, Olvera-Prado H, Narváez-Chavez S, Peralta-Figueroa J, Torres-Villalobos G. Hematological indices as indicators of silent inflammation in achalasia patients: A cross-sectional study. Medicine (Baltimore) . 2020;99(9):e19326. Panza A, Fontana A, Palmieri O, Merla A, Copetti M, Cuttitta A, Biscaglia G, Gentile A, Andriulli A, Latiano A. Circulating levels of cytokines, chemokines and growth factors in patients with achalasia. Biomed Rep. 2021;15(5):92. Ma LY, Liu ZQ, Chen WF, Yao L, Zhong YS, Zhang YQ, Ma LL, Qin WZ, Hu JW, Cai MY, Zhang Z, Lin SL, Hu H, Zhou PH, Li QL. A cross-sectional study reveals a chronic low-grade inflammation in achalasia. J Gastroenterol Hepatol. 2023;38(4):598-608. Yao L, Liu Z, Chen W, Xu J, Xu X, Xu J, Ma L, Li X, Li Q, Zhou P. Imbalance of Innate and Adaptive Immunity in Esophageal Achalasia. J Neurogastroenterol Motil. 2023;30;29(4):486-500. Li XY, Xiang AY, Liu XY, Wang KH, Wang Y, Pan HT, Zhang JY, Yao L, Liu ZQ, Xu JQ, Li XQ, Zhang ZC, Chen WF, Zhou PH, Li QL. Association of circulating cytokine levels and tissue-infiltrating myeloid cells with achalasia: results from Mendelian randomization and validation through clinical characteristics and single-cell RNA sequencing. J Gastroenterol . 2024;59(12):1079-1091. Saltiel AR, Olefsky JM. Inflammatory mechanisms linking obesity and metabolic disease. J Clin Invest . 2017;127(1):1-4. Salvagno GL, Sanchis-Gomar F, Picanza A, Lippi G. Red blood cell distribution width: A simple parameter with multiple clinical applications. Crit Rev Clin Lab Sci . 2015;52(2):86-105. Li N, Zhou H, Tang Q. Red Blood Cell Distribution Width: A Novel Predictive Indicator for Cardiovascular and Cerebrovascular Diseases. Dis Markers. 2017;2017:7089493. Lee HB, Kim J, Oh SH, Kim SH, Kim HS, Kim WC, Kim S, Kim OJ. Red Blood Cell Distribution Width Is Associated with Severity of Leukoaraiosis. PLoS One . 2016;11(2):e0150308. Alghamdi M. Red Blood Cell Distribution Width: A Potential Inexpensive Marker for Disease Activity in Patients with Rheumatic Diseases; Scoping Review. Open Access Rheumatol . 2023;15:173-180. Samo S, Qayed E. Esophagogastric junction outflow obstruction: Where are we now in diagnosis and management? World J Gastroenterol . 2019;25(4):411–7. Carlson DA, Lin Z, Kahrilas PJ, Sternbach J, Hungness ES, Soper NJ, et al. High-Resolution Impedance Manometry Metrics of the Esophagogastric Junction for the Assessment of Treatment Response in Achalasia. Am J Gastroenterol . 2016;111(12):1702-1710. Torres-Villalobos G, Coss-Adame E, Furuzawa-Carballeda J, et al. Dor vs Toupet fundoplication after laparoscopic Heller myotomy: long-term randomized controlled trial evaluated by high-resolution manometry. J Gastrointest Surg 2018;22:13–22. Yunchun L, Yue W, Jun FZ, Qizhu S, Liumei D. Clinical significance of red blood cell distribution width and inflammatory factors for the disease activity in rheumatoid arthritis. Clin Lab . 2016;62(12):2327-2331. Tecer D, Sezgin M, Kanik A et al. Can mean platelet volume and red blood cell distribution width show disease activity in rheumatoid arthritis. Biomark Med . 2016;10(9):967-974. Goksugur SB, Demircioglu F. Factors affecting the levels of red cell distribution width. Eur Rev Med Pharmacol Sci . 2015;19(3):347. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5983523","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":414877751,"identity":"5834c5f2-1864-449f-aafb-cf3616ba7d2f","order_by":0,"name":"Diana Aguilar-León","email":"","orcid":"","institution":"Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"","lastName":"Aguilar-León","suffix":""},{"id":414877752,"identity":"dfa1cc73-dcdd-453a-926d-d7f19d017be9","order_by":1,"name":"Dulce P. Méndez-Hernández","email":"","orcid":"","institution":"Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán","correspondingAuthor":false,"prefix":"","firstName":"Dulce","middleName":"P.","lastName":"Méndez-Hernández","suffix":""},{"id":414877753,"identity":"59189aaa-5ab4-4bbb-9368-a91596458347","order_by":2,"name":"Miguel Moreno-Fuentes","email":"","orcid":"","institution":"Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán","correspondingAuthor":false,"prefix":"","firstName":"Miguel","middleName":"","lastName":"Moreno-Fuentes","suffix":""},{"id":414877754,"identity":"2818c05e-f646-40f3-875f-11e0b65e70b0","order_by":3,"name":"Enrique Coss-Adame","email":"","orcid":"","institution":"Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán","correspondingAuthor":false,"prefix":"","firstName":"Enrique","middleName":"","lastName":"Coss-Adame","suffix":""},{"id":414877755,"identity":"657109f3-dac9-4723-858f-1a5657ac8266","order_by":4,"name":"Luis R. 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Neutrophil-to-lymphocyte (NLR) in \u003cstrong\u003eD\u003c/strong\u003e all achalasia, GERD, and HD groups at baseline and follow-up; \u003cstrong\u003eE\u003c/strong\u003e type I and II achalasia and \u003cstrong\u003eF\u003c/strong\u003e female and male achalasia patients. Integrated relaxation pressure (IRP) in \u003cstrong\u003eG\u003c/strong\u003e all type I, type II, female, and male achalasia patients. HD: Healthy donors (n=500); GERD: gastroesophageal reflux disease (n=161); achalasia (n=161); Type I achalasia (n=60); Type II achalasia (n=101); Female achalasia patients (n=107); Male achalasia patients (n=54). The results are expressed as the mean ± 95% confidence interval. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5983523/v1/381eec81feaf7a41009695b1.png"},{"id":76298191,"identity":"d92de901-9240-4e9e-a2dd-911d99f898c6","added_by":"auto","created_at":"2025-02-14 13:33:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":194495,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Autoimmune disease, \u003cstrong\u003eB\u003c/strong\u003e Inflammatory disease, \u003cstrong\u003eC\u003c/strong\u003e Neurological disease, \u003cstrong\u003eD\u003c/strong\u003eGERD questionnaire, \u003cstrong\u003eE\u003c/strong\u003e EAT-10 questionnaire, and \u003cstrong\u003eF\u003c/strong\u003e Eckardt questionnaire in all, type I, type II, female, and male achalasia patients. HD: Healthy donors (n=500); GERD: gastroesophageal reflux disease (n=161); achalasia (n=161); Type I achalasia (n=60); Type II achalasia (n=101); Female achalasia patients (n=107); Male achalasia patients (n=54). The results are expressed as the mean ± 95% confidence interval. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5983523/v1/96135077aace903de78bca57.png"},{"id":76298190,"identity":"c81eaab6-6bef-4e1e-b52d-5b0d1982cb4d","added_by":"auto","created_at":"2025-02-14 13:33:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":316238,"visible":true,"origin":"","legend":"\u003cp\u003eHematological parameters in patients with achalasia at baseline and during follow-up. Hemoglobin in \u003cstrong\u003eA\u003c/strong\u003e all achalasia and GERD patients and controls at baseline and follow-up; \u003cstrong\u003eB\u003c/strong\u003e type I and II achalasia, and \u003cstrong\u003eC\u003c/strong\u003e female and male achalasia patients. RDW in \u003cstrong\u003eD\u003c/strong\u003e all achalasia and GERD patients and controls at baseline and follow-up; \u003cstrong\u003eE\u003c/strong\u003e type I and II achalasia, and \u003cstrong\u003eF\u003c/strong\u003e female and male achalasia patients. Platelets in \u003cstrong\u003eG\u003c/strong\u003e all achalasia and GERD patients and controls at baseline and follow-up; \u003cstrong\u003eH\u003c/strong\u003e type I and II achalasia, and \u003cstrong\u003eI\u003c/strong\u003e female and male achalasia patients. HD: Healthy donors (n=500); GERD: gastroesophageal reflux disease (n=161); achalasia (n=161); Type I achalasia (n=60); Type II achalasia (n=101); Female patients with achalasia (n=107); Male patients with achalasia (n=54). The results are expressed as the mean ± 95% confidence interval. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 and **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5983523/v1/ae8c28ad42d9168ce02ac608.png"},{"id":76299169,"identity":"776b0533-2ca7-471b-a09a-ad73fde7edad","added_by":"auto","created_at":"2025-02-14 13:41:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2479415,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5983523/v1/6047f329-5bc4-42cd-9a0f-af0e35664394.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Role of Red Blood Cell Distribution Width in the evaluation and follow-up of patients with achalasia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAchalasia is a primary, chronic esophageal motility disorder characterized by aperistalsis and failure of the lower esophageal sphincter to relax. The pathophysiology of achalasia seems to involve an autoimmune process and a significant inflammatory component [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The characteristic distribution of cells and cytokines that promote an inflammatory microenvironment in the lower esophageal sphincter tissue supports this theory [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFlow cytometry, immunofluorescence, and RNA sequencing analysis helped to identify that achalasia patients suffer from systemic chronic low-grade inflammation with dysregulated immune cells and mediators associated with disease duration [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The low-grade inflammation has been proposed as an underlying pathophysiological mechanism linking risk factors or metabolic disorders (e.g., oxidative stress, obesity, diabetes, dyslipidemia), to an increased risk of chronic degenerative disease as well as a common pathogenic denominator in age-related diseases. Nonetheless, in most patients, complete blood count (CBC) is unaltered, or their alterations are related to other underlying pathologies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition, no simple and clinically relevant biomarkers have been identified in the diagnostic approach and follow-up patients with achalasia. It underlines the need to strengthen research into the usefulness of clinical parameters obtained in routine laboratory tests.\u003c/p\u003e \u003cp\u003eIn this vein, beyond its widely established role in the approach to patients with anemia, the red blood cell distribution width (RDW) has been considered a promising inflammation biomarker. The red blood cells (RBCs) are non-nucleated cells characterized by having a typical oval biconcave shape, with a diameter of 6 to 8 \u0026micro;m and a thickness of 2 \u0026micro;m. The average volume of RBCs ranges from 80 to 100 femtoliter (fL), but different physiological and pathological conditions may increase the degree of anisocytosis. The RDW is a quantitative measure of variation in the size of circulating RBCs, which is receiving increasing interest as a diagnostic and prognostic marker in a vast array of human disorders, including autoimmune, inflammatory diseases, functional bowel conditions, COVID-19, various types of cancer and multiple hospital admissions in subjects with chronic conditions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The RDW is calculated automatically by hematological analyzers by dividing the standard deviation (SD) of the mean corpuscular volume (MCV) by the MCV and multiplying by 100 to yield a percentage value. An RDW value below the reference range has been considered without clinical relevance. In contrast, an increased RDW value reflects a more significant difference in the size of RBCs, which can be due to the presence of smaller or larger RBCs or both. An elevated RDW usually results from increased or ineffective production of RBCs and excessive fragmentation or destruction of RBCs [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These studies suggest that altered RDW, indicating a higher level of systemic inflammation and oxidative stress, could be associated with worse outcomes and more severe in multiple pathologies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, the purpose of this study was to explore the relationship between achalasia and RDW, to evaluate its utility in diagnosis, treatment, and follow-up, as well as to determine its association with the integrated relaxation pressure (IRP), defined as the average lowest pressure through the EGJ, a standardized manometric parameter to determine obstruction [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipant Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis ambispective study was conducted at the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, a tertiary referral center, from 2013 to 2024. It was approved by our institute's medical ethics committee (Ref. No. 1522) following the principles of the 1989 Declaration of Helsinki. All patients participated voluntarily, and only those who provided written informed consent were included.\u003c/p\u003e\n\u003cp\u003eOne hundred sixty-one achalasia, 161 gastroesophageal reflux disease (GERD) patients, and 500 healthy donors were included. The control group was matched by demographic characteristics. The diagnosis of achalasia and GERD was made with a high-resolution esophageal manometry, upper gastrointestinal endoscopy, barium esophagogram, and 24-hour pH monitoring. Patients older than 18 years were included in the study. Patients with the following diagnoses were excluded: pregnancy, Chagas disease, esophageal stricture, scleroderma, gastric cancer, esophageal cancer, peptic stricture, other esophageal motility disorders, severe hematologic, renal or hepatic disease, as well as patients on anticoagulant,\u0026nbsp;aspirin or steroid therapy. Patients' clinical records were carefully reviewed according to a pre-established protocol. The following data were collected retrospectively for each study participant from the hospital's medical records: demographic features, clinical characteristics, type of achalasia, family history of autoimmunity, and current diagnosis of organ or systemic autoimmunity. When a comorbid autoimmune diagnosis was found in patients with achalasia, all relevant data (i.e., date of diagnosis, presenting symptoms, clinical and laboratory confirmatory test results, and treatment administered) were recorded. Finally, chronic inflammatory conditions (i.e., asthma, allergic rhinitis, gout, and rosacea) were recorded in the achalasia group. CBC parameters used in the study were the latest laboratory findings recorded before and five years after surgical intervention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor comparison, 500 healthy volunteers at the blood bank were recruited as controls for the study. All included controls had not previously known cardiovascular, metabolic, inflammatory, or neoplastic disease. Demographic and laboratory variables were also collected for this group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll CBC analyses were performed with an automatic hematologic analyzer (Beckman coulter DxH 800 Hematology Analyzer). Hemoglobin (Hb), RDW, white blood cell (WBC), neutrophils, lymphocytes, monocytes, eosinophils, and platelet counts were obtained. Blood samples were collected in dipotassium ethylenediaminetetraacetic acid tubes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing a diagnosis of achalasia, patients were asked to complete three standardized and validated questionnaires: the Eckardt symptom score, the Eat Assessment Tool-10 (EAT), and the Gastroesophageal Reflux Disease-Related Quality of Life (GERD-HRQL). These instruments are designed to assess the frequency and severity of symptoms associated with esophageal disease. IRP from manometry was collected in achalasia patients to indicate disease severity [16].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were performed. The Shapiro-Wilk test was used to evaluate the normality of the data. Continuous parameters were expressed as mean ± standard deviation (SD). Continuous variables, including age, BMI, disease evolution, questionnaires, neutrophil to lymphocyte ratio (NLR), RDW, platelets, hemoglobin, and IRP, were performed using the Kruskal–Wallis one-way ANOVA on ranks. All the pairwise multiple comparison procedures were done using the Dunn or Holm–Sidak method. Qualitative parameters were expressed as numbers and percentages. Categorical variables were compared using the\u0026nbsp;𝜒2 test or Fisher's exact test. Pearson's correlation coefficient was used to assess the correlation between hematologic indices, clinical questionnaire scores, and HRM parameters\u0026nbsp;in the distribution of RDW values between all cases and controls and between achalasia subtypes. Linear regression analyses were also performed to explore the relationship between RDW and sex, the prevalence and incidence of autoimmune and inflammatory diseases, and IRP, which are closely associated with symptomatic severity. A \u003cem\u003eP\u003c/em\u003e-value \u0026lt; 0.05 was considered statistically significant for all analyses. These were performed using JASP software version 0.19 for Mac OS Sonoma 14.5.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic and clinical characteristics\u003c/h2\u003e\n \u003cp\u003eSixty-six percent of achalasia patients were female, with a mean age of 48 years and a preoperative mean body mass index of 23 kg/m\u003csup\u003e2\u003c/sup\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA-C). At diagnosis, 99% of patients had dysphagia, 92% had regurgitation, and 88% had weight loss. The prevalence of autoimmune comorbidity was 19% (Fig. 2A), inflammatory comorbidity was 22% (Fig. 2B), and neurological comorbidity was 3% (Fig. 2C) in patients with achalasia (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic and clinical characteristics and laboratory variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHealthy Donors\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGERD\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;161)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAchalasia Total\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;161)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;107)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType I\u003c/p\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType II Achalasia\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;101)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003cp\u003e18\u0026ndash;63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003cp\u003e18\u0026ndash;66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003cp\u003e22\u0026ndash;64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.2\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6\u003c/p\u003e\n \u003cp\u003e47.5\u003c/p\u003e\n \u003cp\u003e22\u0026ndash;76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.3\u003c/p\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003cp\u003e24\u0026ndash;86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e\n \u003cp\u003e49.5\u003c/p\u003e\n \u003cp\u003e24\u0026ndash;83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.4\u003c/p\u003e\n \u003cp\u003e48.0\u003c/p\u003e\n \u003cp\u003e22\u0026ndash;86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex, Female (%)\u003c/p\u003e\n \u003cp\u003eMale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e315 (63)\u003c/p\u003e\n \u003cp\u003e185 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 (66)\u003c/p\u003e\n \u003cp\u003e54 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 (66)\u003c/p\u003e\n \u003cp\u003e54 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003cp\u003e54 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 (100)\u003c/p\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (51)\u003c/p\u003e\n \u003cp\u003e29 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (75)\u003c/p\u003e\n \u003cp\u003e24 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisease evolution (mo),\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;41.5\u003c/p\u003e\n \u003cp\u003e13.0\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.0\u0026thinsp;\u0026plusmn;\u0026thinsp;53.1\u003c/p\u003e\n \u003cp\u003e13.0\u003c/p\u003e\n \u003cp\u003e2\u0026ndash;288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;34.5\u003c/p\u003e\n \u003cp\u003e13.0\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.3\u0026thinsp;\u0026plusmn;\u0026thinsp;55.3\u003c/p\u003e\n \u003cp\u003e18.0\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.2\u0026thinsp;\u0026plusmn;\u0026thinsp;30.0\u003c/p\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003cp\u003e17.0\u0026ndash;45.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e\n \u003cp\u003e22.5\u003c/p\u003e\n \u003cp\u003e14.9\u0026ndash;36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003cp\u003e16.1\u0026ndash;32.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\n \u003cp\u003e21.9\u003c/p\u003e\n \u003cp\u003e14.9\u0026thinsp;\u0026plusmn;\u0026thinsp;36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003cp\u003e14.9\u0026ndash;35.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\n \u003cp\u003e21.8\u003c/p\u003e\n \u003cp\u003e16.1\u0026ndash;36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDysphagia (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160 (99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegurgitation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148 (92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100 (93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91 (92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight loss (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e142 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94 (87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55 (91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeartburn (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104 (64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAutoimmune disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInflammatory disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurological disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestionnaires\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGERD-HQRL, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7\u003c/p\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003cp\u003e2\u0026ndash;47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7\u003c/p\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003cp\u003e2\u0026ndash;47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/p\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEAT-10, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003cp\u003e4\u0026ndash;43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e\n \u003cp\u003e32.0\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e\n \u003cp\u003e34.0\u003c/p\u003e\n \u003cp\u003e4\u0026ndash;43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eECKARDT, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003cp\u003e2\u0026ndash;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003cp\u003e2\u0026ndash;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003cp\u003e4\u0026ndash;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003cp\u003e2\u0026ndash;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003cp\u003e3\u0026ndash;12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemoglobin (g/dL), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003cp\u003e13.3\u0026ndash;18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003cp\u003e5.7\u0026ndash;19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003cp\u003e10.0\u0026ndash;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003cp\u003e13.6\u0026ndash;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003cp\u003e10.0\u0026ndash;17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003cp\u003e10.0\u0026ndash;17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003cp\u003e10.1\u0026ndash;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRDW (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003cp\u003e8.9\u0026ndash;13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e12.8\u0026ndash;15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e12.6\u0026ndash;14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e12.5\u0026ndash;16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e12.3\u0026ndash;20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003cp\u003e12.3\u0026ndash;20.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003cp\u003e12.5\u0026ndash;17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets 10^3 / \u0026micro;L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e275\u0026thinsp;\u0026plusmn;\u0026thinsp;52\u003c/p\u003e\n \u003cp\u003e271\u003c/p\u003e\n \u003cp\u003e144\u0026ndash;460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e263\u0026thinsp;\u0026plusmn;\u0026thinsp;60\u003c/p\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003cp\u003e108\u0026ndash;499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e242\u0026thinsp;\u0026plusmn;\u0026thinsp;58\u003c/p\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003cp\u003e135\u0026ndash;427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e222\u0026thinsp;\u0026plusmn;\u0026thinsp;41\u003c/p\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003cp\u003e150\u0026ndash;326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u0026thinsp;\u0026plusmn;\u0026thinsp;64\u003c/p\u003e\n \u003cp\u003e244\u003c/p\u003e\n \u003cp\u003e135\u0026ndash;427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e238\u0026thinsp;\u0026plusmn;\u0026thinsp;53\u003c/p\u003e\n \u003cp\u003e231\u003c/p\u003e\n \u003cp\u003e145\u0026ndash;392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e244\u0026thinsp;\u0026plusmn;\u0026thinsp;61\u003c/p\u003e\n \u003cp\u003e244\u003c/p\u003e\n \u003cp\u003e135\u0026ndash;427\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeukocytes 10^3 / \u0026micro;L,\u003c/p\u003e\n \u003cp\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003cp\u003e3.6\u0026ndash;11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003cp\u003e2.8\u0026ndash;23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003cp\u003e2.9\u0026ndash;12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003cp\u003e3.6\u0026ndash;11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003cp\u003e2.9\u0026ndash;12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003cp\u003e3.5\u0026ndash;12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphocytes (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\n \u003cp\u003e32.8\u003c/p\u003e\n \u003cp\u003e15.8\u0026ndash;55.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003cp\u003e2.5\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003cp\u003e5.5\u0026ndash;54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003cp\u003e10.9\u0026ndash;54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003cp\u003e5.5\u0026ndash;50.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003cp\u003e10.9\u0026ndash;47.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3\u003c/p\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003cp\u003e5.5\u0026ndash;54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonocytes (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003cp\u003e3.5\u0026ndash;14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003cp\u003e2.1\u0026ndash;28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003cp\u003e1.0\u0026ndash;13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003cp\u003e4.7\u0026ndash;11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9\u0026ndash;2.0\u003c/p\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003cp\u003e1.0\u0026ndash;13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003cp\u003e4.4\u0026ndash;13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003cp\u003e1.0\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEosinophils (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003cp\u003e0.1\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003cp\u003e0.1\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasophils (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0.2\u0026ndash;12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;2,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutrophils (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.0\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e\n \u003cp\u003e56.2\u003c/p\u003e\n \u003cp\u003e31.7\u0026ndash;77.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e\n \u003cp\u003e58.7\u003c/p\u003e\n \u003cp\u003e31\u0026ndash;91.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;92.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003cp\u003e33.0\u0026ndash;79.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;92.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e\n \u003cp\u003e58.6\u003c/p\u003e\n \u003cp\u003e37.0\u0026ndash;78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;92.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP (mg/dL), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003cp\u003e0.09\u0026ndash;3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eIn the 5-year postoperative follow-up in patients with achalasia, body mass index increased by 12%, dysphagia decreased by 67%, regurgitation by 82%, and weight loss by 83%. The prevalence of autoimmune comorbidity increased from 19 to 25%, inflammatory comorbidity from 22 to 30%, and neurological comorbidity from 3 to 6% (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic, clinical, and laboratory variables at follow-up (60 months)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGERD\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;161)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAchalasia Total\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;161)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;107)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType I\u003c/p\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType II\u003c/p\u003e\n \u003cp\u003eAchalasia\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;101)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003cp\u003e22\u0026ndash;88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5\u003c/p\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003cp\u003e19\u0026ndash;84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e\n \u003cp\u003e47.5\u003c/p\u003e\n \u003cp\u003e19\u0026ndash;84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15.2\u003c/p\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003cp\u003e21\u0026ndash;84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7\u003c/p\u003e\n \u003cp\u003e43.5\u003c/p\u003e\n \u003cp\u003e19\u0026ndash;84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.4\u003c/p\u003e\n \u003cp\u003e44.0\u003c/p\u003e\n \u003cp\u003e21\u0026ndash;81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e) mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\n \u003cp\u003e27.4\u003c/p\u003e\n \u003cp\u003e17.3\u0026ndash;45.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003cp\u003e16.5\u0026ndash;66.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e\n \u003cp\u003e25.5\u003c/p\u003e\n \u003cp\u003e16.5\u0026ndash;66.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003cp\u003e16.7\u0026ndash;45.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003cp\u003e16.5\u0026ndash;36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003cp\u003e17.5\u0026ndash;66.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDysphagia (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegurgitation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight loss (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight gain (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeartburn (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAutoimmune disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInflammatory disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurological disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestionnaires\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGERD-HQRL, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1\u003c/p\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEAT-10, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eECKARDT, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemoglobin (g/dL), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003cp\u003e5.7\u0026ndash;19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003cp\u003e16.0\u003c/p\u003e\n \u003cp\u003e12.4\u0026ndash;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;18.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003cp\u003e6.1\u0026ndash;17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRDW (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003cp\u003e12.7\u0026ndash;14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003cp\u003e13.9\u003c/p\u003e\n \u003cp\u003e12.6\u0026ndash;26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e12.3\u0026ndash;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003cp\u003e12.3\u0026ndash;26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003cp\u003e12.7\u0026ndash;26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003cp\u003e12.3\u0026ndash;25.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelets 10^3 / \u0026micro;L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e254\u0026thinsp;\u0026plusmn;\u0026thinsp;62\u003c/p\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003cp\u003e108\u0026ndash;476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e245\u0026thinsp;\u0026plusmn;\u0026thinsp;58\u003c/p\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003cp\u003e128\u0026ndash;433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;47\u003c/p\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003cp\u003e150\u0026ndash;348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e251\u0026thinsp;\u0026plusmn;\u0026thinsp;61\u003c/p\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003cp\u003e128\u0026ndash;433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e241\u0026thinsp;\u0026plusmn;\u0026thinsp;63\u003c/p\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003cp\u003e129\u0026ndash;433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e248\u0026thinsp;\u0026plusmn;\u0026thinsp;56\u003c/p\u003e\n \u003cp\u003e243\u003c/p\u003e\n \u003cp\u003e128\u0026ndash;372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeukocytes 10^3 / \u0026micro;L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003cp\u003e2.8\u0026ndash;23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e3.0\u0026ndash;21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003cp\u003e3.7\u0026ndash;21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003cp\u003e3\u0026ndash;13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003cp\u003e3.4\u0026ndash;13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003cp\u003e3.0\u0026ndash;21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphocytes (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003cp\u003e2.5\u0026ndash;50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003cp\u003e3.0\u0026ndash;54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003cp\u003e3.0\u0026ndash;54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003cp\u003e7\u0026ndash;47.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003cp\u003e5.1\u0026ndash;54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1\u003c/p\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003cp\u003e3.0\u0026ndash;43.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonocytes (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e3.6\u0026ndash;28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003cp\u003e2.0\u0026ndash;22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003cp\u003e4.5\u0026ndash;12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003cp\u003e2.0\u0026ndash;22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e\n \u003cp\u003e7.7\u003c/p\u003e\n \u003cp\u003e2.0\u0026ndash;12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003cp\u003e4.0\u0026ndash;22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEosinophils (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003cp\u003e0- 12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;75.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003cp\u003e0.0 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;75.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasophils (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.1\u0026ndash;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003cp\u003e0.0\u0026ndash;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutrophils (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e\n \u003cp\u003e57.6\u003c/p\u003e\n \u003cp\u003e3.6\u0026ndash;91.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e\n \u003cp\u003e58.8\u003c/p\u003e\n \u003cp\u003e8.1\u0026ndash;90.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e\n \u003cp\u003e58.9\u003c/p\u003e\n \u003cp\u003e8.1\u0026ndash;90.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e\n \u003cp\u003e58.7\u003c/p\u003e\n \u003cp\u003e12\u0026ndash;85.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.6\u003c/p\u003e\n \u003cp\u003e58.7\u003c/p\u003e\n \u003cp\u003e8.1\u0026ndash;90.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e\n \u003cp\u003e59.1\u003c/p\u003e\n \u003cp\u003e43.0\u0026ndash;81.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRP (mg/dL), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026ndash;1.0\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003cp\u003e0.05\u0026ndash;4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e0.02\u0026ndash;4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e0.03\u0026ndash;3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eAchalasia patients increase body mass index after myotomy.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAchalasia patients, regardless of type and sex, have a significantly lower preoperative body mass index than the GERD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA-C). However, this difference disappears during follow-up (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA-C).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eThe integrated relaxation pressure in patients with achalasia during the 5-year follow-up is within normal parameters regardless of the type of achalasia and the patient sex after surgical intervention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAchalasia patients showed abnormal IRP at baseline. Type II achalasia had a higher IPR than type I (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eG). At 5-year follow-up, notwithstanding the achalasia type or patient sex, the IRP decreased to normal parameters after surgical intervention (IRP\u0026thinsp;\u0026lt;\u0026thinsp;15 mmHg; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eG).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eAchalasia is associated with a higher neutrophil-to-lymphocyte ratio than healthy individuals\u003c/h3\u003e\n\u003cp\u003ePatients with achalasia (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD), regardless of type (type I: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047; and type II: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005; Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE) and sex (Female: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006; and Male: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.040; Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eF), had a higher neutrophil-to-lymphocyte ratio than healthy individuals. NLR ratio increased slightly during follow-up (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD-F). No differences were determined with the GERD group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe prevalence of autoimmune, inflammatory, and neurological diseases increases in patients with achalasia during 5-year follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of autoimmune diseases in the achalasia group was 25%, in type I achalasia 19%, in type II 31%, in the female group 30%, and in the male group 16%. The most significant increases occurred in type II achalasia and female patients (Fig.\u0026nbsp;2A).\u003c/p\u003e\n\u003cp\u003eRegarding inflammatory diseases, the prevalence in the achalasia group was 30%, in type I 30%, in type II 31%, in women 33%, and in men 30%. The most significant increase occurred in type I achalasia patients (Fig.\u0026nbsp;2B).\u003c/p\u003e\n\u003cp\u003eFinally, neurological diseases increased from 3 to 6% (basal vs 5-year follow-up) in the achalasia group, and this was subrogated to patients with achalasia type II and female gender (Fig.\u0026nbsp;2C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSymptom assessment in achalasia patients at five years of follow-up post-myotomy decreases to clinically significant scores\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the international standardized and validated questionnaires, the Eckardt score, used for the evaluation of symptoms and efficacy of the treatment, the EAT-10 measures swallowing difficulties, and the GERD-HRQL, which measures GERD symptoms, at five years after myotomy, patients with achalasia had a significant improvement compared to baseline (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, (Fig.\u0026nbsp;2CD-F). More remarkable recovery was determined in the GERD-HRQL score in type I compared to type II achalasia (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005, Fig.\u0026nbsp;2D) and in the male vs. female group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05, (Fig. 2D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAchalasia patients have alterations in RDW, hemoglobin, and platelets, which are persistent during follow-up.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline hemoglobin concentration in achalasia and GERD patients was decreased compared to healthy individuals (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA), and it was associated with a decrease in females (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC) and type II achalasia (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB) but not in males or type I achalasia. The decrease in hemoglobin became even higher during follow-up compared to baseline in female patients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC) and type II achalasia (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB). Meanwhile, in men, hemoglobin remained within normal parameters (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\n\u003cp\u003eThe RDW at baseline was significantly higher in the GERD and achalasia patient groups than in healthy donors (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD). Achalasia Type I and II and female and male groups had a significantly higher erythrocyte distribution width than healthy donors (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e\n\u003cp\u003eDuring follow-up, the RDW increased significantly in achalasia type I (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.006; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE), type II (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE), and in the female group (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.006; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eF) concerning their respective baseline value. In the male group, the RDW remained unchanged during the follow-up (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eF). This increase suggests that RDW changes over time in response to the natural evolution of the disease, which affects only the female group, regardless of the type of achalasia.\u003c/p\u003e\n\u003cp\u003eIn contrast, RDW in GERD patients showed no significant differences between the time of diagnosis and follow-up, indicating that RDW in this population remains stable.\u003c/p\u003e\n\u003cp\u003eThe baseline platelet cell number in the GERD and achalasia types I and II, male and female patient groups, was significantly lower than in the healthy individual group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG).\u003c/p\u003e\n\u003ch3\u003ePredictive value of clinical characteristics\u003c/h3\u003e\n\u003cp\u003eA 5-year linear regression analysis was performed to examine the influence of sex and autoimmune disease on RDW alterations. In achalasia patients, both sex and autoimmune comorbidities influenced the increase in erythrocyte distribution width (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLinear Regression\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eModel Summary- RDW Achalasia at follow-up (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRMSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e Change\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edf1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edf2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eSex \u0026ndash; Follow-up\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eNote.\u003c/strong\u003e M\u003csub\u003e1\u003c/sub\u003e includes Sex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutoimmune disease \u0026ndash; Follow-up\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted R\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e \u003cstrong\u003eChange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003edf1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003edf2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eNote.\u003c/strong\u003e M\u003csub\u003e1\u003c/sub\u003e includes Autoimmune disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHowever, the strongest association was determined between IRP and RDW in achalasia patients. It was statistically significant between baseline and follow-up, with a coefficient of determination (R\u0026sup2;) of 0.762 and a \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The coefficient of IRP was 0.384 (\u0026plusmn;\u0026thinsp;0.020), indicating that a high IRP is associated with a higher RDW. This finding reinforces the relevance of IRP as a tangible parameter to assess the severity of achalasia, closely associated with the patient\u0026apos;s symptoms.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLinear Regression \u0026ndash; IRP \u0026ndash; Baseline\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eModel Summary- RDW Achalasia at baseline (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted R\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e \u003cstrong\u003eChange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003edf1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003edf2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003cstrong\u003eNote.\u003c/strong\u003e M\u003csub\u003e1\u003c/sub\u003e includes IRP at baseline.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eRDW is a simple and inexpensive clinical test that can be performed in any laboratory. However, clinicians barely use it when analyzing hemograms, maybe because physicians are not used to these meaningful parameters. Anisocytosis could be due to inflammation, nutritional status, iron deficiency, inadequate erythropoietin production, or even oxidative stress. It can lead to tiredness, shortness of breath, dizziness, headache, cold hands and feet, pale skin, and chest pain [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRDW seems to be a surrogate parameter of the inflammatory process, like the erythrocyte sedimentation rate. In our view, the mechanism by which inflammation may increase RDW in patients with achalasia is through ineffective erythropoiesis mediated by cytokines, as has been demonstrated in the pathophysiology of other diseases, where TNF-α, IL-6, and IL-1β impair erythrocyte maturation. These cytokines could modulate erythropoiesis through the following pathways: (i) inhibiting erythropoietin (EPO) gene transcription, (ii) blocking antiapoptotic and maturation effects of EPO, and iii) decreased renal EPO synthesis by inflammatory cytokines desensitization of EPO erythroid progenitors in bone marrow [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Even more, these cytokines could directly inhibit the mean lifespan of erythrocytes and their membrane deformity. Therefore, inflammation could contribute to anisocytosis through damage in erythrocyte maturation induced by EPO and immature erythrocyte release to peripheral blood, thus increasing RDW. In the sera of achalasia patients, we have determined increased levels of TNF-α and IL-6 compared with healthy donors (\u003cem\u003edata not shown\u003c/em\u003e), suggesting that this systemic inflammation could contribute to the increase in RDW.\u003c/p\u003e \u003cp\u003eIn this study, RDW was positively correlated with ultrasensitive CRP, and it predicted an increase in RDW level in a multivariate analysis independent of age, gender, and hemoglobin (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). It was also determined that female patients had higher levels of RDW and that these were associated with a higher IRP. At the same time, a linear analysis demonstrated the influence of sex and autoimmune disease on RDW alterations.\u003c/p\u003e \u003cp\u003eThe results highlight the importance of RDW as a relevant marker in evaluating women with diagnosis of achalasia and type II achalasia patients, showing significant variation over time. This finding contrasts clearly with the stability of RDW observed in patients with GERD. The variation between baseline RDW and after follow-up in achalasia suggests that the RDW may reflect changes in disease activity and its natural evolution. However, it is essential to consider each patient's characteristics and comorbidities.\u003c/p\u003e \u003cp\u003eThe stability of RDW in patients with GERD may be due to differences in pathophysiology between achalasia and GERD.\u003c/p\u003e \u003cp\u003eFurthermore, the association between RDW and IRP underlines the usefulness of RDW as a potential indicator of disease severity. Therefore, the positive correlation with IRP suggests that RDW could be a complementary tool in the assessment of achalasia patients. This relationship also indicates that alterations in red blood cells associated with systemic inflammation could offer additional insight into the progression and prognosis of patients with achalasia.\u003c/p\u003e \u003cp\u003eMoreover, having a low-cost biomarker might allow the determination of low-grade inflammation, which has been demonstrated to contribute to the development of metabolic disorders (e.g. obesity, diabetes, dyslipidemia), and an increased risk of chronic degenerative disease as well as a common pathogenic denominator in age-related diseases. This could influence the design of therapeutic strategies that allow long-term control of inflammation and thus avoid a worse disease prognosis.\u003c/p\u003e \u003cp\u003eThe advantages of using RDW are that it does not represent an additional charge and seems unaltered by infectious processes in the short term, as may occur with ESR and CRP. On the other hand, limitations to be considered when interpreting RDW are that it is equipment- and laboratory-dependent; that is, each piece of equipment is calibrated with a different frequency histogram, and each lab defines its standard rate. Moreover, RDW could be modified by many medical conditions, including hepatic disease, anemia, and deficiencies of folate and vitamin B12 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study determined that RDW is a marker associated with the underlying inflammation in patients with achalasia. Additionally, the positive correlation between RDW and IRP suggests its usefulness in clinical assessment as a valuable and easily determined tool for the follow-up of patients with achalasia. However, future prospective studies are required to consolidate its role as a prognostic marker in achalasia.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest relevant to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003eThis is an observational study. This study was approved by the Institutional Review Board of the Instituto Nacional de Ciencias M\u0026eacute;dicas y Nutrici\u0026oacute;n Salvador Zubir\u0026aacute;n (Ref. No. 1522).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eD.A.-L., D.P.M.-H., M.M.-F., J.F.-C., G.T.-V. Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, E.C.-A., L.R.V.-G., M.A.V. Data curation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available on request from the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFuruzawa-Carballeda J, Aguilar-Le\u0026oacute;n D, Gamboa-Dom\u0026iacute;nguez A, Valdovinos MA, Nu\u0026ntilde;ez-\u0026Aacute;lvarez C, Mart\u0026iacute;n-del-Campo LA, Enr\u0026iacute;quez AB, Coss-Adame E, Svarch AE, Flores-N\u0026aacute;jera A, Villa-Ba\u0026ntilde;os A, Ceballos JC, Torres-Villalobos G. Achalasia--An Autoimmune Inflammatory Disease: A Cross-Sectional Study. \u003cem\u003eJ Immunol Res\u003c/em\u003e. 2015;2015:729217.\u003c/li\u003e\n \u003cli\u003eGoyal RK, Rattan S. Role of mechanoregulation in mast cell-mediated immune inflammation of the smooth muscle in the pathophysiology of esophageal motility disorders. \u003cem\u003eAm J Physiol Gastrointest Liver Physiol.\u0026nbsp;\u003c/em\u003e2024;326(4):G398-G410.\u003c/li\u003e\n \u003cli\u003eRomero-Hern\u0026aacute;ndez F, Furuzawa-Carballeda J, Hern\u0026aacute;ndez-Molina G, Alejandro-Medrano E, N\u0026uacute;\u0026ntilde;ez-\u0026Aacute;lvarez CA, Hern\u0026aacute;ndez-Ram\u0026iacute;rez DF, Azamar-Llamas D, Olivares-Mart\u0026iacute;nez E, Bre\u0026ntilde;a B, Palacios A, Valdovinos MA, Coss-Adame E, Ramos-\u0026Aacute;valos B, Torres-Landa S, Hern\u0026aacute;ndez-\u0026Aacute;vila AA, Flores-N\u0026aacute;jera A, Torres-Villalobos G. Autoimmune comorbidity in achalasia patients. \u003cem\u003eJ Gastroenterol Hepatol.\u003c/em\u003e 2018;33(1):203-208.\u003c/li\u003e\n \u003cli\u003eL\u0026oacute;pez-Verdugo F, Furuzawa-Carballeda J, Romero-Hern\u0026aacute;ndez F, Coss-Adame E, Valdovinos MA, Priego-Ranero A, Olvera-Prado H, Narv\u0026aacute;ez-Chavez S, Peralta-Figueroa J, Torres-Villalobos G. Hematological indices as indicators of silent inflammation in achalasia patients: A cross-sectional study. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e. 2020;99(9):e19326.\u003c/li\u003e\n \u003cli\u003ePanza A, Fontana A, Palmieri O, Merla A, Copetti M, Cuttitta A, Biscaglia G, Gentile A, Andriulli A, Latiano A. Circulating levels of cytokines, chemokines and growth factors in patients with achalasia. \u003cem\u003eBiomed Rep.\u003c/em\u003e 2021;15(5):92.\u003c/li\u003e\n \u003cli\u003eMa LY, Liu ZQ, Chen WF, Yao L, Zhong YS, Zhang YQ, Ma LL, Qin WZ, Hu JW, Cai MY, Zhang Z, Lin SL, Hu H, Zhou PH, Li QL. A cross-sectional study reveals a chronic low-grade inflammation in achalasia. \u003cem\u003eJ Gastroenterol Hepatol.\u003c/em\u003e 2023;38(4):598-608.\u003c/li\u003e\n \u003cli\u003eYao L, Liu Z, Chen W, Xu J, Xu X, Xu J, Ma L, Li X, Li Q, Zhou P. Imbalance of Innate and Adaptive Immunity in Esophageal Achalasia. \u003cem\u003eJ Neurogastroenterol Motil.\u003c/em\u003e 2023;30;29(4):486-500.\u003c/li\u003e\n \u003cli\u003eLi XY, Xiang AY, Liu XY, Wang KH, Wang Y, Pan HT, Zhang JY, Yao L, Liu ZQ, Xu JQ, Li XQ, Zhang ZC, Chen WF, Zhou PH, Li QL. Association of circulating cytokine levels and tissue-infiltrating myeloid cells with achalasia: results from Mendelian randomization and validation through clinical characteristics and single-cell RNA sequencing. \u003cem\u003eJ Gastroenterol\u003c/em\u003e. 2024;59(12):1079-1091.\u003c/li\u003e\n \u003cli\u003eSaltiel AR, Olefsky JM. Inflammatory mechanisms linking obesity and metabolic disease. \u003cem\u003eJ Clin Invest\u003c/em\u003e. 2017;127(1):1-4.\u003c/li\u003e\n \u003cli\u003eSalvagno GL, Sanchis-Gomar F, Picanza A, Lippi G. Red blood cell distribution width: A simple parameter with multiple clinical applications. \u003cem\u003eCrit Rev Clin Lab Sci\u003c/em\u003e. 2015;52(2):86-105.\u003c/li\u003e\n \u003cli\u003eLi N, Zhou H, Tang Q. Red Blood Cell Distribution Width: A Novel Predictive Indicator for Cardiovascular and Cerebrovascular Diseases. \u003cem\u003eDis Markers.\u003c/em\u003e 2017;2017:7089493.\u003c/li\u003e\n \u003cli\u003eLee HB, Kim J, Oh SH, Kim SH, Kim HS, Kim WC, Kim S, Kim OJ. Red Blood Cell Distribution Width Is Associated with Severity of Leukoaraiosis. \u003cem\u003ePLoS One\u003c/em\u003e. 2016;11(2):e0150308.\u003c/li\u003e\n \u003cli\u003eAlghamdi M. Red Blood Cell Distribution Width: A Potential Inexpensive Marker for Disease Activity in Patients with Rheumatic Diseases; Scoping Review. \u003cem\u003eOpen Access Rheumatol\u003c/em\u003e. 2023;15:173-180.\u003c/li\u003e\n \u003cli\u003eSamo S, Qayed E. Esophagogastric junction outflow obstruction: Where are we now in diagnosis and management? \u003cem\u003eWorld J Gastroenterol\u003c/em\u003e. 2019;25(4):411\u0026ndash;7.\u003c/li\u003e\n \u003cli\u003eCarlson DA, Lin Z, Kahrilas PJ, Sternbach J, Hungness ES, Soper NJ, et al. High-Resolution Impedance Manometry Metrics of the Esophagogastric Junction for the Assessment of Treatment Response in Achalasia. \u003cem\u003eAm J Gastroenterol\u003c/em\u003e. 2016;111(12):1702-1710.\u003c/li\u003e\n \u003cli\u003eTorres-Villalobos G, Coss-Adame E, Furuzawa-Carballeda J, et al. Dor vs Toupet fundoplication after laparoscopic Heller myotomy: long-term randomized controlled trial evaluated by high-resolution manometry. \u003cem\u003eJ Gastrointest Surg\u003c/em\u003e 2018;22:13\u0026ndash;22.\u003c/li\u003e\n \u003cli\u003eYunchun L, Yue W, Jun FZ, Qizhu S, Liumei D. Clinical significance of red blood cell distribution width and inflammatory factors for the disease activity in rheumatoid arthritis. \u003cem\u003eClin Lab\u003c/em\u003e. 2016;62(12):2327-2331.\u003c/li\u003e\n \u003cli\u003eTecer D, Sezgin M, Kanik A et al. Can mean platelet volume and red blood cell distribution width show disease activity in rheumatoid arthritis. \u003cem\u003eBiomark Med\u003c/em\u003e. 2016;10(9):967-974.\u003c/li\u003e\n \u003cli\u003eGoksugur SB, Demircioglu F. Factors affecting the levels of red cell distribution width. \u003cem\u003eEur Rev Med Pharmacol Sci\u003c/em\u003e. 2015;19(3):347.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Achalasia, Red Cell Distribution Width (RDW), inflammatory disease, integrated relaxation pressure (IRP) ","lastPublishedDoi":"10.21203/rs.3.rs-5983523/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5983523/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground. \u003c/strong\u003eCurrent studies demonstrate red blood cell distribution width (RDW) as a possible surrogate inflammation biomarker.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim.\u003c/strong\u003e To determine RDW in achalasia patients, compare it to GERD and healthy donor groups, and evaluate its clinical relevance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e. It was an ambispective study. One hundred sixty-one achalasia, 161 gastroesophageal reflux disease (GERD) patients, and 500 healthy donors (HD) were included and followed up 5 years. The achalasia and GERD patient groups were matched with the HD control groups by demographic characteristics and laboratory variables. The achalasia and GERD diagnosis were made with high-resolution esophageal manometry, upper gastrointestinal endoscopy, barium esophagogram, and 24-hour pH monitoring. For the achalasia group, correlation between RDW and clinical characteristics, Eckardt, EAT-10, GERD-HRQL questionnaire scores, achalasia types, gender, comorbidities, and integrated relaxation pressure were evaluated by logistic regression analysis between patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults. \u003c/strong\u003eThe RDW values at baseline differed significantly between patients (achalasia versus GERD) and these versus HD (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). During follow-up, the achalasia group had significantly higher RDW values than the GERD (\u003cem\u003eP\u003c/em\u003e=0.031). The achalasia patients sustained increased RDW during follow-up compared to its baseline value (All: \u003cem\u003eP\u003c/em\u003e=0.010; type I: \u003cem\u003eP\u003c/em\u003e=0.006; type II: \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001; female: \u003cem\u003eP\u003c/em\u003e=0.003; men: \u003cem\u003eP\u003c/em\u003e= 0.948).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion.\u003c/strong\u003e The results highlight the importance of RDW as an inflammatory marker, showing significant variation over time. This finding contrasts sharply with the stability of RDW observed in patients with GERD.\u003c/p\u003e","manuscriptTitle":"Role of Red Blood Cell Distribution Width in the evaluation and follow-up of patients with achalasia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-14 13:25:20","doi":"10.21203/rs.3.rs-5983523/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e962966e-2f7e-45a4-aaa7-516af0b37d0d","owner":[],"postedDate":"February 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-14T13:25:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-14 13:25:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5983523","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5983523","identity":"rs-5983523","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}