Sex-stratified analysis of complete blood count parameters in Helicobacter pylori infection: A retrospective cohort study revealing distinct hematological mechanisms

Sex-stratified analysis of complete blood count parameters in Helicobacter pylori infection: A retrospective cohort study revealing distinct hematological mechanisms | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Sex-stratified analysis of complete blood count parameters in Helicobacter pylori infection: A retrospective cohort study revealing distinct hematological mechanisms Fuad Alanazi, Abdulhadi M Abdulwahed, Yazeed Alshuweishi, Raed Farzan, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7142446/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 Helicobacter pylori infection affects approximately 50% of the global population and is associated with hematological manifestations. Despite established associations with anemia, sex-specific effects remain unexplored, limiting our understanding of differential mechanisms and personalized treatment strategies. Methods We conducted a retrospective cohort study using electronic medical records from 2015–2024 at King Khalid University Hospital, Saudi Arabia. Among 1,895 patients with enteric infections, we identified 165 H. pylori -positive patients and 163 H. pylori -negative participants frequency-matched by age and sex from family medicine clinics. Nine complete blood count parameters were analyzed from tests performed within 10 days before or 2 days after H. pylori diagnosis. Sex-stratified analyses were performed via a two-way ANOVA to test for sex × H. pylori interactions, with Cohen's d effect sizes reported. Results Significant sex × H. pylori interactions were observed for hematocrit ( p = 0.0146) and red blood cell count ( p = 0.0122). Males demonstrated anemia with large effect sizes for hematocrit (d=-0.619, p < 0.001), hemoglobin (d=-0.512, p = 0.005), and RBC count (d=-0.407, p = 0.026). Females exhibited changes in red cell indices: reduced mean corpuscular volume (d=-0.392, p = 0.006), mean corpuscular hemoglobin (d=-0.295, p = 0.036), and elevated red cell distribution width (d = 0.337, p = 0.017). H. pylori infection significantly increased anemia rates in males (32.3% vs 11.5%, p = 0.010) but not in females (31.1% vs 24.5%, p = 0.372), with an overall rate of 27.3% vs 19.0%. Conclusions H. pylori infection affects males and females through distinct hematological mechanisms. Males experience anemia affecting hemoglobin and hematocrit, whereas females develop changes in red cell indices. These findings from our retrospective cohort study support the use of sex-specific diagnostic and treatment strategies. Health sciences/Diseases Health sciences/Gastroenterology Health sciences/Medical research Biological sciences/Microbiology Health sciences/Risk factors Helicobacter pylori sex differences complete blood count anemia iron deficiency hematological parameters sex-stratified analysis retrospective cohort study Figures Figure 1 Figure 2 Introduction Helicobacter pylori ( H. pylori ), a microaerophilic, gram-negative bacterial organism, establishes a chronic infection within the gastric mucosal environment of approximately 50% of the global population, representing one of the most prevalent bacterial infections worldwide 1 , 2 . Since its discovery by Warren and Marshall in 1984 3 H. pylori has been implicated in numerous gastrointestinal and extra-gastrointestinal manifestations 4 , 5 , with hematological disorders emerging as a significant area of clinical concern 6 . The bacterium's association with iron deficiency anemia (IDA) 7 , 8 Immune thrombocytopenic purpura 9 , and vitamin B12 deficiency 10 , 11 has been well documented. However, critical questions remain regarding the mechanisms underlying these associations and potential variations across demographic subgroups. The relationship between H. pylori infection and hematological parameters extends beyond simple iron deficiency. Multiple pathophysiological mechanisms have been proposed, including chronic gastrointestinal blood loss from gastritis or peptic ulceration, impaired iron absorption due to hypochlorhydria, increased iron uptake by the bacterium itself, and systemic inflammatory responses that affect erythropoiesis 12 – 16 . Recent systematic reviews and meta-analyses have confirmed a strong association between H. pylori infection and iron deficiency anemia. Previous meta-analyses have consistently demonstrated increased odds of IDA in H. pylori infection, with pooled ORs ranging from 1.72–2.8) 8 , 17 . However, these aggregate figures may mask underlying heterogeneity in disease pathways and clinical outcomes. A critical limitation in the current literature is the scarcity of sex-stratified analyses examining the hematological effects of H. pylori . Most published studies report only aggregate results without formal interaction testing to determine whether H. pylori effects differ between males and females 12 , 18 – 20 . This represents a significant gap in our understanding, especially considering well-established sex differences in iron metabolism 21 , 22 , baseline hematological parameters 23 , and the prevalence of H. pylori infection itself, which shows male predominance, even across diverse global populations (46.3% vs 42.7% in males vs females; 95% CI: 42.1–50.5 vs 39–46.5) 2 . Sex differences in hematological parameters are multifaceted and influenced by numerous biological factors. Women of reproductive age experience regular menstrual blood loss, leading to higher iron requirements and increased susceptibility to iron deficiency 22 . Conversely, males generally have higher baseline hemoglobin and hematocrit levels because of androgenic effects on erythropoiesis 24 . These baseline differences may modulate the hematological response to H. pylori infection; however, this hypothesis has been inadequately explored, particularly in contemporary cohorts. The importance of sex-stratified research extends beyond academic interest to clinical practice implications. Current clinical guidelines for H. pylori screening and treatment do not incorporate sex-specific considerations 25 . Even though evidence suggests sex differences in diagnostic approaches 26 . If H. pylori affects males and females through different mechanisms, sex-specific diagnostic thresholds, screening protocols, and treatment strategies may be warranted. Moreover, understanding sex-specific effects could provide insights into the underlying pathophysiology and identify novel therapeutic targets 27 . Recent advances in sex and gender medicine have highlighted the critical importance of disaggregated analyses in biomedical research 28 . NIH and major journals now mandate sex-specific reporting, recognizing that aggregated data may obscure significant biological differences and perpetuate health disparities. The Sex and Gender Equity in Research (SAGER) guidelines provide a framework for incorporating sex and gender considerations throughout the research process, from study design to data interpretation 29 , 30 . Despite these initiatives, implementation remains incomplete, particularly in the areas of infectious disease 29 , 31 , 32 . The present study addresses this critical knowledge gap. We conducted a comprehensive sex-stratified retrospective cohort analysis of complete blood count (CBC) parameters to explore potential sex-specific effects of H. pylori infection on hematological parameters. Our objectives were to characterize the overall hematological profile of H. pylori -infected patients compared to H. pylori -negative participants, to test for sex × H. pylori interactions across nine CBC parameters, and to delineate sex-specific patterns of hematological abnormalities Methods Study Design and Setting This retrospective cohort study analyzed data from King Khalid University Hospital (KKUH), a tertiary care center in Riyadh, Saudi Arabia. Participants were identified and grouped based on their confirmed H. pylori infection status to compare hematological outcomes between H. pylori -positive and H. pylori -negative groups. The study protocol was approved by the Institutional Review Board at King Saud University, Riyadh, Saudi Arabia (Research Project No. E-24-8617), and the requirement for informed consent was waived due to the study's retrospective nature. All methods were performed in accordance with the relevant guidelines and regulations, including the Declaration of Helsinki and institutional guidelines. Study Population and Data Collection Electronic medical records were systematically reviewed for the period January 2015 to December 2024 at KKUH. The following variables were collected: demographic characteristics (age, sex, nationality), anthropometric measurements (weight, body mass index), clinical diagnoses ( H. pylori status, comorbidities), and laboratory parameters. Complete blood count parameters included red blood cell count (RBC), hemoglobin (Hgb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), white blood cell count (WBC), and platelet count (PLT). BMI and weight data were unavailable for some H. pylori -negative participants due to incomplete medical records. From hospital electronic medical records, we identified 1,895 patients diagnosed with enteric infections between 2015 and 2024. Of these, 653 patients had confirmed H. pylori infection. After applying inclusion and exclusion criteria, 165 H. pylori -positive patients were included. H. pylori -negative participants were obtained from the family medicine clinic medical records within KKUH during 2023–2024. We reviewed records of individuals who had attended routine check-ups or treatment of acute, minor conditions (e.g., seasonal allergies, upper respiratory infections). H. pylori -negative status was defined as the absence of documented H. pylori infection in medical records. H. pylori -negative participants were frequency-matched to H. pylori -positive patients by age (± 5 years) and sex. After applying the same temporal criteria for CBC testing, 163 H. pylori -negative participants were included. [ Figure 1 here] The inclusion criteria for both groups were age ≥ 18 years and the availability of complete CBC data. For H. pylori -positive patients, CBC parameters were assessed from tests performed within 10 days before or 2 days after H. pylori diagnosis to ensure temporal proximity to confirmed infection status. The final analysis included 328 participants (165 H. pylori -positive, 163 H. pylori -negative), providing adequate power for sex-stratified analyses. Statistical Analysis Data were analyzed using Python 3.11.13 with pandas (v2.2.2), scipy (v1.15.3), and statsmodels (v0.14.4) libraries. Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were presented as frequencies (percentages). The cohort design was chosen because participants were selected based on H. pylori infection status, allowing comparison of hematological outcome frequencies between H. pylori -positive and H. pylori -negative groups. This design enables the calculation of relative risks and the assessment of absolute differences in hematological parameters. Group differences in continuous measures were assessed using independent samples t-tests, and categorical variables were compared using chi-square tests. The magnitude of the observed effects was determined using Cohen's d statistic, applying conventional interpretation guidelines (d = 0.2 indicating minor effects, d = 0.5 indicating moderate effects, and d = 0.8 indicating large effects). For our primary analysis examining sex-specific effects, we performed a two-way analysis of variance (ANOVA) to test for sex × H. pylori status interactions. When interactions were significant ( p < 0.05) or marginally significant ( p < 0.10), stratified analyses were conducted within each sex. To control for multiple comparisons across nine CBC parameters, we applied Bonferroni correction, setting the adjusted significance threshold at p < 0.006 for individual parameter comparisons. Clinical relevance was assessed by categorizing CBC parameters according to laboratory reference ranges (low, normal, high) and comparing distributions between groups. WHO anemia criteria were applied using sex-specific thresholds (hemoglobin < 12.0 g/dL for women, < 13.0 g/dL for men) based on the 2024 WHO guidelines 33 . All 328 participants had complete hemoglobin and sex data required for the WHO anemia classification analysis. All the statistical tests were two-tailed, with p < 0.05 considered statistically significant for main effects, except for the interaction terms, where p < 0.10 was used, given their lower statistical power. Power calculations were performed using Python's statsmodels (version 0.14.4). For sex-stratified comparisons using independent t-tests with Bonferroni correction (α = 0.006), the study achieved exceptional power (> 99%) to detect medium and large effect sizes in both males (n = 123) and females (n = 205). For detecting sex × H. pylori interactions using two-way ANOVA (α = 0.10), the study had modest power (10.2–10.5%) for the observed interaction effects. Despite conservative power for interaction detection, significant sex-specific effects were identified for the hematocrit ( p = 0.0146) and RBC count ( p = 0.0122), suggesting robust biological differences. The minimum detectable effect sizes with 80% power were d = 0.65 for males and d = 0.50 for females, confirming exceptional power to detect clinically meaningful differences in hematological parameters. Data Quality and Management Prior to analysis, the data underwent systematic quality control procedures. Outliers were identified using both statistical methods (values beyond 3 standard deviations) and clinical plausibility assessment. One extreme outlier (platelet count of 10 × 10³/µL) was removed and treated as missing data after clinical review confirmed a probable data entry error. Unit standardization was performed where necessary (hemoglobin converted from mg/dL to g/dL; MCHC from g/L to g/dL). Missing data were minimal for CBC parameters (< 1%). However, demographic variables had higher rates of missingness in the H. pylori -negative group (BMI: 11.7%, weight: 66.3%, nationality: 60.1%). The final analytical dataset comprised 328 participants with complete CBC data for all primary analyses. Results Study Population Characteristics A total of 328 participants were included, comprising 165 H. pylori -positive patients and 163 H. pylori -negative participants. The groups were well-matched for age (45.5 ± 16.6 vs. 45.9 ± 16.1 years, p = 0.828) and sex distribution (37.6% vs. 37.4% male, p = 1.000). No significant differences were observed in BMI between H. pylori -positive and H. pylori -negative participants (28.5 ± 6.8 vs. 28.8 ± 5.9 kg/m², p = 0.682). Table 1 summarizes the demographic and clinical characteristics of the study participants. Table 1 Demographic and Clinical Characteristics of Study Participants by H. pylori Status Characteristic Category H. pylori -positive (n = 165) H. pylori -negative (n = 163) p -value Sex, n (%) Male 62 (37.6) 61 (37.4) 1.000 Female 103 (62.4) 102 (62.6) Age (years), mean ± SD 45.5 ± 16.6 45.9 ± 16.1 0.828 BMI (kg/m²), mean ± SD* 1 28.5 ± 6.8 28.8 ± 5.9 0.682 BMI categories, n (%) 1 Underweight 6 (3.6) 8 (4.9) 0.167 Normal 27 (16.4) 22 (13.5) Overweight 31 (18.8) 56 (34.4) Obese 49 (29.7) 58 (35.6) Unknown 52 (31.5) 19 (11.7) Weight (kg), mean ± SD* 2 75.5 ± 19.1 76.6 ± 14.3 0.704 *1 BMI data not available for 52 H. pylori -positive and 19 H. pylori -negative participants *2 Weight data not available for 35 H. pylori -positive and 108 H. pylori -negative participants BMI = Body Mass Index; SD = Standard Deviation WHO BMI categories: Underweight (< 18.5 kg/m²), Normal (18.5–24.9 kg/m²), Overweight (25.0-29.9 kg/m²), Obese (≥ 30.0 kg/m²). [ Table 1 here] Overall CBC Parameter Comparisons Analysis of nine CBC parameters revealed four statistically significant differences between the H. pylori -positive and H. pylori -negative groups Table 2 . Compared to H. pylori -negative participants, H. pylori -positive participants exhibited significantly lower hemoglobin (12.84 ± 1.87 vs. 13.39 ± 1.88 g/dL, p = 0.008), hematocrit (39.59 ± 5.27 vs. 41.45 ± 5.19%, p = 0.001), MCV (84.31 ± 7.54 vs. 86.58 ± 7.29 fL, p = 0.006), and higher RDW (14.41 ± 2.42 vs. 13.69 ± 1.63%, p = 0.002). This hematologic profile is consistent with IDA, commonly associated with H. pylori infection. No significant differences were observed in MCH, MCHC, RBC count, WBC, or platelet count. Table 2 Complete Blood Count Parameter Comparison Between H. pylori -Positive and H. pylori -Negative Groups Parameter Hp(+) (n = 165) Hp(–) (n = 163) p -value Effect Size (Cohen's d) Direction of Change RBC (×10⁶/µL) 4.726 ± 0.709 4.822 ± 0.710 0.221 -0.136 Decreased Hgb (g/dL) 12.839 ± 1.869 13.389 ± 1.880 0.008 -0.294 Decreased Hct (%) 39.585 ± 5.270 41.451 ± 5.194 0.001 -0.356 Decreased MCV (fL) 84.314 ± 7.537 86.583 ± 7.286 0.006 -0.306 Decreased MCH (pg) 27.372 ± 3.090 27.978 ± 3.055 0.075 -0.197 Decreased MCHC (g/dL) 32.404 ± 1.307 32.253 ± 1.368 0.307 0.113 Increased RDW (%) 14.406 ± 2.416 13.688 ± 1.628 0.002 0.348 Increased WBC (×10³/µL) 7.300 ± 2.878 7.163 ± 2.422 0.641 0.052 Increased PLT (×10³/µL) 294.280 ± 90.900 303.628 ± 76.660 0.316 -0.111 Decreased Data presented as mean ± standard deviation. Bold p -values indicate statistical significance (p < 0.05). Hp(+) = H. pylori positive; Hp(–) = H. pylori negative. [ Table 2 here] Clinical Distribution of CBC Abnormalities Clinical categorization analysis showed notable hematological abnormalities among H. pylori -positive patients compared to H. pylori -negative participants (Table 3 ). The prevalence of anemia was higher among infected individuals (27.3% vs. 19.0%), with corresponding increases observed in low hematocrit (21.2% vs. 12.3%) and red blood cell count deficiencies (16.4% vs. 14.1%). Microcytosis (MCV < 80 fL), hypochromia (MCH < 27 pg), and elevated RDW were also more prevalent in patients with H. pylori-positive status. Table 3 Clinical Distribution of CBC Parameters by H. pylori Status Hp(+) Hp(–) Parameter Reference Range Low n(%) Normal n(%) High n(%) Abnormal n(%) Low n(%) Normal n(%) High n(%) Abnormal n(%) RBC (×10⁶/µL) 4.2–6.1 27 (16.4) 135 (81.8) 3 (1.8) 30 (18.2) 23 (14.1) 136 (83.4) 4 (2.5) 27 (16.6) Hgb (g/dL) 12.0–18.0 45 (27.3) 120 (72.7) 0 (0.0) 45 (27.3) 31 (19.0) 132 (81.0) 0 (0.0) 31 (19.0) Hct (%) 36–48 35 (21.2) 123 (74.5) 7 (4.2) 42 (25.5) 20 (12.3) 130 (79.8) 13 (8.0) 33 (20.2) MCV (fL) 80–95 36 (21.8) 122 (73.9) 7 (4.2) 43 (26.1) 21 (12.9) 132 (81.0) 10 (6.1) 31 (19.0) MCH (pg) 27–31 58 (35.2) 94 (57.0) 13 (7.9) 71 (43.0) 48 (29.4) 102 (62.6) 13 (8.0) 61 (37.4) MCHC (g/dL) 32.0–36.0 47 (28.5) 118 (71.5) 0 (0.0) 47 (28.5) 60 (36.8) 103 (63.2) 0 (0.0) 60 (36.8) RDW (%) 11.6–14.6 1 (0.6) 117 (70.9) 47 (28.5) 48 (29.1) 2 (1.2) 128 (78.5) 33 (20.2) 35 (21.5) WBC (×10³/µL) 4.0–11.0 6 (3.6) 150 (90.9) 9 (5.5) 15 (9.1) 10 (6.1) 141 (86.5) 12 (7.4) 22 (13.5) PLT (×10³/µL) 150–400 5 (3.0) 144 (87.3) 15 (9.1) 20 (12.1) 0 (0.0) 145 (89.0) 18 (11.0) 18 (11.0) Average abnormality rate Hp(+): 24.3%, Hp(–): 21.7%. Excess clinical burden in Hp(+): +2.7%. Data presented as the number of participants (n%). Abnormal = Low + High values. Hp(+) = H. pylori positive; Hp(–) = H. pylori negative. [ Table 3 here] Sex-Stratified Analysis Results Sex-stratified analyses revealed significant sex × H. pylori interactions for hematocrit ( p = 0.0146) and RBC count ( p = 0.0122), and a near-significant interaction for hemoglobin ( p = 0.0511), as shown in Table 4 (Figure S1 ). Table 4 Sex-Stratified Analysis of Complete Blood Count Parameters by H. pylori Status Female Male Sex×Hp Interaction Parameter Range Hp + vs Hp- p d Hp + vs Hp- p d p RBC 4.2–6.1 4.61 ± 0.56 vs 4.56 ± 0.53 0.5478 0.084 4.92 ± 0.88 vs 5.26 ± 0.76 0.0257 -0.407 0.0122 Hgb 12.0–18.0 12.38 ± 1.54 vs 12.65 ± 1.44 0.2002 -0.180 13.60 ± 2.12 vs 14.63 ± 1.88 0.0053 -0.512 0.0511 Hct 36–48 38.50 ± 4.32 vs 39.37 ± 3.91 0.1337 -0.210 41.39 ± 6.18 vs 44.93 ± 5.24 < 0.001 -0.619 0.0146 MCV 80–95 83.98 ± 7.24 vs 86.81 ± 7.16 0.0055 -0.392 84.86 ± 8.04 vs 86.21 ± 7.54 0.3395 -0.173 0.3846 MCH 27–31 27.03 ± 2.99 vs 27.91 ± 2.99 0.0358 -0.295 27.94 ± 3.19 vs 28.08 ± 3.18 0.8019 -0.045 0.2914 MCHC 32.0–36.0 32.13 ± 1.27 vs 32.10 ± 1.29 0.8579 0.025 32.86 ± 1.24 vs 32.51 ± 1.46 0.1578 0.256 0.2921 RDW 11.6–14.6 14.49 ± 2.50 vs 13.76 ± 1.78 0.0168 0.337 14.27 ± 2.29 vs 13.57 ± 1.34 0.0416 0.371 0.9430 WBC 4.0–11.0 6.97 ± 2.25 vs 7.03 ± 2.29 0.8476 -0.027 7.85 ± 3.65 vs 7.38 ± 2.63 0.4197 0.146 0.3845 PLT 150–400 298.51 ± 84.98 vs 312.18 ± 77.11 0.2303 -0.168 287.32 ± 100.22 vs 289.33 ± 74.34 0.9000 -0.023 0.5430 Mean ± SD. Bold, p < 0.05. d, Cohen's d effect size. Sex×Hp interaction p from 2-way ANOVA. Hp+/-, H. pylori -positive/negative. [ Table 4 here] Males with H. pylori infection demonstrated significant reductions in hemoglobin (d=-0.512, p = 0.005), hematocrit (d=-0.619, p < 0.001), and RBC count (d=-0.407, p = 0.026), indicating substantial anemia. Females primarily exhibited alterations in red cell indices, including decreased MCV (d=-0.392, p = 0.006), MCH (d=-0.295, p = 0.036), and increased RDW (d = 0.337, p = 0.017), without significant changes in hemoglobin or hematocrit. Figure S2 presents forest plots of sex-stratified effect sizes for all CBC parameters. The sex-specific percentage changes shown in Fig. 2 underscore these differences, with males experiencing marked decreases in hemoglobin (-7.0%), hematocrit (-7.9%), and RBC (-6.5%), and females exhibiting reductions in MCV (-3.3%), MCH (-3.2%), and an increase in RDW (+ 5.3%). [ Figure 2 here] Sex-Specific Anemia Prevalence Application of the WHO sex-specific anemia criteria revealed sex-dependent differences (Table S1 ). Among males, significantly more H. pylori -infected individuals met anemia criteria compared to H. pylori -negative participants (32.3% vs 11.5%, p = 0.010). In contrast, females showed a smaller, non-significant difference (31.1% vs 24.5%, p = 0.372), reinforcing distinct sex-specific patterns in H. pylori -associated anemia. Discussion This retrospective cohort study demonstrates that H. pylori infection affects males and females through fundamentally different hematological mechanisms. The significant sex × H. pylori interactions for hematocrit ( p = 0.0146) and red blood cell count ( p = 0.0122), with a near-significant interaction for hemoglobin ( p = 0.0511), provide statistical evidence for distinct biological responses. Males with H. pylori infection demonstrated substantial reductions in hemoglobin (d=-0.512, medium effect), hematocrit (d=-0.619, medium-large effect), and RBC count (d=-0.407, small-medium effect). At the same time, females exhibited predominant changes in red cell indices without significant alterations in hemoglobin or hematocrit. These sex-specific patterns suggest different underlying mechanisms and challenge current uniform approaches to H. pylori -associated hematological disorders. The divergent hematological patterns observed reflect sex-specific pathophysiological mechanisms underlying H. pylori infection. Males demonstrate enhanced inflammatory responses, as evidenced by higher cyclooxygenase-2 (COX-2) expression in response to H. pylori infection, whereas females showed no COX-2 response 34 . Conversely, baseline TFF1 levels are significantly higher in women than in men, and H. pylori infection significantly reduces TFF1 in women 34 , suggesting sex-specific alterations in protective factors. Furthermore, H. pylori exhibits selective utilization of steroid hormones, which may contribute to sex-specific colonization patterns. The bacterium can absorb estrogens (which have 3-OH structures) but cannot metabolize them, while being unable to absorb testosterone or progesterone due to their 3 = O molecular structure, which prevents membrane interaction 35 . Building on these differential inflammatory responses, hormonal mechanisms provide a crucial framework for understanding the observed sex differences. The protective effect of estrogen emerges as a key factor, with estrogen treatment eliminating H. pylori -induced gastric cancer in male mice and significantly decreasing neutrophil infiltration 36 . The molecular mechanism involves the estrogen-related receptor gamma (ESRRG), which suppresses H. pylori infection by directly binding to and upregulating the tumor suppressor TFF1 37 . However, H. pylori -induced inflammation activates NF-κB signaling, which inhibits ESRRG-mediated TFF1 activation, creating a pathogenic feedback loop where infection suppresses its own protective mechanisms 37 . This hormonal regulation extends to iron metabolism, where clinical evidence demonstrates estrogen's potent effects: during IVF treatment, marked estrogen stimulation decreased median hepcidin levels from 4.85 to 1.43 ng/mL, demonstrating estrogen's regulatory role in iron homeostasis 38 . This hormonal regulation likely contributes to females' ability to buffer against full anemia, even with microcytic red cell changes; hemoglobin remains stable, explaining why females in our study maintained relatively stable hemoglobin levels despite developing microcytic changes characteristic of early iron deficiency. Our findings both confirm and extend the growing literature on sex-specific effects of H. pylori . A comprehensive meta-analysis of 244 studies found males had greater odds of H. pylori infection than females did, supporting our observation of sex-specific vulnerability 39 . However, their analysis did not examine hematological outcomes or test for formal interactions as we have done. Recent studies from diverse populations have reported variable associations between H. pylori and anemia that vary by sex. Wang et al. (2024) similarly reported that H. pylori infection was associated with IDA specifically in women ( p = 0.031) but not men, though their analysis was limited to iron markers without examining the full spectrum of CBC parameters 40 . A 2022 sub-Saharan study found complex relationships between H. pylori infection and anemia, with males showing higher susceptibility to certain hematological changes 41 . Our findings provide a mechanistic explanation for these observations by demonstrating that males and females develop different types of hematological abnormalities. Males experience reductions in hemoglobin, hematocrit, and RBC count, indicative of overt anemia, while females show changes in red cell indices, suggesting early-stage iron deficiency without frank anemia. These mechanistic insights from our cohort study have immediate clinical relevance for current practice guidelines. Current guidelines recommend H. pylori testing in patients with unexplained iron deficiency anemia, without sex-specific considerations 25 , 26 . Our findings suggest that the hematological presentation of H. pylori infection differs substantially by sex, indicating the need for tailored diagnostic approaches. For male patients, the presence of reduced hemoglobin, hematocrit, or RBC count should prompt evaluation for H. pylori , even in the absence of microcytic indices. The large effect sizes observed for hematocrit (d=-0.619) and hemoglobin (d=-0.512) indicate substantial clinical relevance for H. pylori screening in males with these abnormalities. Conversely, in females, the combination of low MCV, low MCH, and elevated RDW, even with normal hemoglobin, may indicate H. pylori -associated iron deficiency. Treatment considerations should account for potential sex-specific factors, with post-menopausal women who lose estrogen's protective effects requiring enhanced surveillance, given the potential loss of estrogen-mediated protection against H. pylori -associated complications. This retrospective cohort study has several limitations. First, the retrospective design using electronic medical records limits our ability to establish temporal relationships between H. pylori infection and hematological changes. Second, our participant selection from patients with enteric infections ensures confirmed H. pylori status with appropriate clinical context, though this may not capture asymptomatic H. pylori carriers. Third, we lacked comprehensive data on factors that could influence hematological parameters, including iron supplementation, menstrual history, and dietary patterns. Finally, our single-center study in Saudi Arabia may limit generalizability to other populations, as H. pylori strains vary geographically in virulence factors, and host genetic factors influencing iron metabolism may differ across ethnic groups. Conclusions H. pylori infection affects males and females through distinct hematological mechanisms. Males typically develop anemia characterized by reduced hemoglobin, hematocrit, and RBC count, whereas females exhibit changes in red cell indices. These sex-specific patterns from our retrospective cohort study support the need for tailored diagnostic approaches and treatment strategies in H. pylori -associated hematological disorders. Declarations Acknowledgment The authors extend their appreciation to the Ongoing Research Funding program (ORF-2025-1443), King Saud University, Riyadh, Saudi Arabia. Funding This project was funded by the Ongoing Research Funding program (ORF-2025-1443), King Saud University, Riyadh, Saudi Arabia. Conflict of interest The authors have declared that no competing interests exist. Informed Consent Statement Not applicable. Data Availability: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Author Contributions: Conceptualization, F.A., Y.A.; methodology, F.A., A.M.Abd.; software, F.A., A.A.; validation, F.A., A.M.Abd.; formal analysis, F.A., R.F.; investigation, F.A., A.M.Abd., R.F., Y.A., A.M.Alm., H.A., A.T.J., M.A.; resources, F.A.; data curation, F.A., A.M.Abd., R.F., Y.A., A.M.Alm., H.A., A.T.J., M.A., A.T.A., A.A.; writing original draft preparation, F.A.; writing, review and editing, all authors; visualization, F.A., Y.A.; supervision, F.A.; project administration, F.A.; funding acquisition, F.A. All authors have read and agreed to the published version of the manuscript. References Hooi JKY, Lai WY, Ng WK, et al. Global Prevalence of Helicobacter pylori Infection: Systematic Review and Meta-Analysis. 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Khan MI, Shah J, Ullah M, et al. Prevalence of Iron Deficiency Among Patients With Helicobacter pylori Infection at a Tertiary Care Hospital. Cureus. 2024;16(8):e68168. Ikeda Y, Tajima S, Izawa-Ishizawa Y, et al. Estrogen regulates hepcidin expression via GPR30-BMP6-dependent signaling in hepatocytes. PLoS One. 2012;7(7):e40465. Badenhorst CE, Forsyth AK, Govus AD. A contemporary understanding of iron metabolism in active premenopausal females. Front Sports Act Living. 2022;4:903937. Shaheen N, Thomas S, Almoghairi A, Alaskar A. Hematological parameters' reference intervals in apparently healthy individuals in Saudi Arabia: a systematic review and meta-analysis. Front Med (Lausanne). 2025;12:1522492. Bachman E, Feng R, Travison T, et al. Testosterone suppresses hepcidin in men: a potential mechanism for testosterone-induced erythrocytosis. J Clin Endocrinol Metab. 2010;95(10):4743–4747. Chey WD, Howden CW, Moss SF, et al. ACG Clinical Guideline: Treatment of Helicobacter pylori Infection. Am J Gastroenterol. 2024;119(9):1730–1753. Eisdorfer I, Shalev V, Goren S, Chodick G, Muhsen K. Sex differences in urea breath test results for the diagnosis of Helicobacter pylori infection: a large cross-sectional study. Biol Sex Differ. 2018;9(1):1. Dias SP, Brouwer MC, van de Beek D. Sex and Gender Differences in Bacterial Infections. Infect Immun. 2022;90(10):e0028322. Heidari S, Babor TF, De Castro P, Tort S, Curno M. Sex and Gender Equity in Research: rationale for the SAGER guidelines and recommended use. Res Integr Peer Rev. 2016;1:2. Peters SAE, Woodward M. A roadmap for sex- and gender-disaggregated health research. BMC Med. 2023;21(1):354. Haematology TL. Sex and gender reporting advances in medicine. In:2024:S2352–3026 (2324) 00074–00077. Lawry LL, Lugo-Robles R, McIver V. Overlooked sex and gender aspects of emerging infectious disease outbreaks: Lessons learned from COVID-19 to move towards health equity in pandemic response. Front Glob Womens Health. 2023;4:1141064. Clayton JA, Collins FS. Policy: NIH to balance sex in cell and animal studies. Nature. 2014;509(7500):282–283. WHO. Guideline on haemoglobin cutoffs to define anaemia in individuals and populations. In: Organization WH, ed.2024. Kato S, Matsukura N, Togashi A, et al. Sex differences in mucosal response to Helicobacter pylori infection in the stomach and variations in interleukin-8, COX-2 and trefoil factor family 1 gene expression. Aliment Pharmacol Ther. 2004;20 Suppl 1:17–24. Hosoda K, Shimomura H, Hayashi S, Yokota K, Oguma K, Hirai Y. Anabolic utilization of steroid hormones in Helicobacter pylori. FEMS Microbiol Lett. 2009;297(2):173–179. Sheh A, Ge Z, Parry NM, et al. 17beta-estradiol and tamoxifen prevent gastric cancer by modulating leukocyte recruitment and oncogenic pathways in Helicobacter pylori-infected INS-GAS male mice. Cancer Prev Res (Phila). 2011;4(9):1426–1435. Kang MH, Eyun SI, Park YY. Estrogen-related receptor-gamma influences Helicobacter pylori infection by regulating TFF1 in gastric cancer. Biochem Biophys Res Commun. 2021;563:15–22. Lehtihet M, Bonde Y, Beckman L, et al. Circulating Hepcidin-25 Is Reduced by Endogenous Estrogen in Humans. PLoS One. 2016;11(2):e0148802. Abubakar I, Morais S, Ferro A, Lunet N. Sex-differences in the prevalence of Helicobacter pylori infection in pediatric and adult populations: Systematic review and meta-analysis of 244 studies. 2017. Wang ZT, Tan WT, Meng MM, et al. The correlation between Helicobacter pylori infection and iron deficiency anemia in women. Eur Rev Med Pharmacol Sci. 2024;28(4):1541–1553. Eyoum Bille BB, Kouitcheu Mabeku LB. Relationship between active Helicobacter pylori infection and anemia, iron deficiency, iron deficiency anemia: A cross-sectional study in a sub-Saharan setting. JGH Open. 2022;6(8):554–568. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterialSexstratifiedanalysisHPV1.docx 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. 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09:13:06","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":144807,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7142446/v1/1be7c73372dd30b96130cbe5.html"},{"id":93574968,"identity":"c76506a0-a178-4725-a8a9-223ca8581d39","added_by":"auto","created_at":"2025-10-15 09:21:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86429,"visible":true,"origin":"","legend":"\u003cp\u003ePatient selection flow diagram for retrospective cohort study. Among 1,895 patients with enteric infections, 653 were identified as \u003cem\u003eH. pylori \u003c/em\u003epositive. After applying inclusion criteria and age/sex matching, the final analysis included 165 H. pylori-positive and 163 \u003cem\u003eH. pylori\u003c/em\u003e-negative participants (n=328).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7142446/v1/f02ef7e7e8402e79f7345bd5.jpg"},{"id":93573828,"identity":"70db7c53-3a07-4846-9561-b19e5ca53b82","added_by":"auto","created_at":"2025-10-15 09:13:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57329,"visible":true,"origin":"","legend":"\u003cp\u003eSex-specific percentage changes in complete blood count parameters in \u003cem\u003eH. pylori\u003c/em\u003einfection. Values represent percentage change from \u003cem\u003eH. pylori\u003c/em\u003e-negative to \u003cem\u003eH. pylori\u003c/em\u003e-positive participants. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7142446/v1/a9c1b83244038450bd9d541c.jpg"},{"id":101860216,"identity":"ab8d844e-1d64-46fe-88fe-0718c653fba1","added_by":"auto","created_at":"2026-02-04 11:28:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1239641,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7142446/v1/b7b9fe0b-de26-42fb-bca4-5006a86fb7d4.pdf"},{"id":93573841,"identity":"008daee2-8c62-4ec7-9928-fe50f240484a","added_by":"auto","created_at":"2025-10-15 09:13:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":197783,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialSexstratifiedanalysisHPV1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7142446/v1/4c279aec7acb5e6faa21f253.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sex-stratified analysis of complete blood count parameters in Helicobacter pylori infection: A retrospective cohort study revealing distinct hematological mechanisms","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eHelicobacter pylori\u003c/em\u003e (\u003cem\u003eH. pylori\u003c/em\u003e), a microaerophilic, gram-negative bacterial organism, establishes a chronic infection within the gastric mucosal environment of approximately 50% of the global population, representing one of the most prevalent bacterial infections worldwide \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Since its discovery by Warren and Marshall in 1984 \u003csup\u003e3\u003c/sup\u003e \u003cem\u003eH. pylori\u003c/em\u003e has been implicated in numerous gastrointestinal and extra-gastrointestinal manifestations \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, with hematological disorders emerging as a significant area of clinical concern \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The bacterium's association with iron deficiency anemia (IDA) \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Immune thrombocytopenic purpura \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, and vitamin B12 deficiency \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e has been well documented. However, critical questions remain regarding the mechanisms underlying these associations and potential variations across demographic subgroups.\u003c/p\u003e\u003cp\u003eThe relationship between \u003cem\u003eH. pylori\u003c/em\u003e infection and hematological parameters extends beyond simple iron deficiency. Multiple pathophysiological mechanisms have been proposed, including chronic gastrointestinal blood loss from gastritis or peptic ulceration, impaired iron absorption due to hypochlorhydria, increased iron uptake by the bacterium itself, and systemic inflammatory responses that affect erythropoiesis \u003csup\u003e\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e–\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Recent systematic reviews and meta-analyses have confirmed a strong association between \u003cem\u003eH. pylori\u003c/em\u003e infection and iron deficiency anemia. Previous meta-analyses have consistently demonstrated increased odds of IDA in \u003cem\u003eH. pylori\u003c/em\u003e infection, with pooled ORs ranging from 1.72–2.8) \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, these aggregate figures may mask underlying heterogeneity in disease pathways and clinical outcomes.\u003c/p\u003e\u003cp\u003eA critical limitation in the current literature is the scarcity of sex-stratified analyses examining the hematological effects of \u003cem\u003eH. pylori\u003c/em\u003e. Most published studies report only aggregate results without formal interaction testing to determine whether \u003cem\u003eH. pylori\u003c/em\u003e effects differ between males and females \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This represents a significant gap in our understanding, especially considering well-established sex differences in iron metabolism \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, baseline hematological parameters \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, and the prevalence of \u003cem\u003eH. pylori\u003c/em\u003e infection itself, which shows male predominance, even across diverse global populations (46.3% vs 42.7% in males vs females; 95% CI: 42.1–50.5 vs 39–46.5) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSex differences in hematological parameters are multifaceted and influenced by numerous biological factors. Women of reproductive age experience regular menstrual blood loss, leading to higher iron requirements and increased susceptibility to iron deficiency \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Conversely, males generally have higher baseline hemoglobin and hematocrit levels because of androgenic effects on erythropoiesis \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. These baseline differences may modulate the hematological response to \u003cem\u003eH. pylori\u003c/em\u003e infection; however, this hypothesis has been inadequately explored, particularly in contemporary cohorts.\u003c/p\u003e\u003cp\u003eThe importance of sex-stratified research extends beyond academic interest to clinical practice implications. Current clinical guidelines for \u003cem\u003eH. pylori\u003c/em\u003e screening and treatment do not incorporate sex-specific considerations \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Even though evidence suggests sex differences in diagnostic approaches \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. If \u003cem\u003eH. pylori\u003c/em\u003e affects males and females through different mechanisms, sex-specific diagnostic thresholds, screening protocols, and treatment strategies may be warranted. Moreover, understanding sex-specific effects could provide insights into the underlying pathophysiology and identify novel therapeutic targets \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecent advances in sex and gender medicine have highlighted the critical importance of disaggregated analyses in biomedical research \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. NIH and major journals now mandate sex-specific reporting, recognizing that aggregated data may obscure significant biological differences and perpetuate health disparities. The Sex and Gender Equity in Research (SAGER) guidelines provide a framework for incorporating sex and gender considerations throughout the research process, from study design to data interpretation \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Despite these initiatives, implementation remains incomplete, particularly in the areas of infectious disease \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe present study addresses this critical knowledge gap. We conducted a comprehensive sex-stratified retrospective cohort analysis of complete blood count (CBC) parameters to explore potential sex-specific effects of \u003cem\u003eH. pylori\u003c/em\u003e infection on hematological parameters. Our objectives were to characterize the overall hematological profile of \u003cem\u003eH. pylori\u003c/em\u003e-infected patients compared to \u003cem\u003eH. pylori\u003c/em\u003e-negative participants, to test for sex × \u003cem\u003eH. pylori\u003c/em\u003e interactions across nine CBC parameters, and to delineate sex-specific patterns of hematological abnormalities\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design and Setting\u003c/b\u003e\u003c/p\u003e\u003cp\u003e This retrospective cohort study analyzed data from King Khalid University Hospital (KKUH), a tertiary care center in Riyadh, Saudi Arabia. Participants were identified and grouped based on their confirmed \u003cem\u003eH. pylori\u003c/em\u003e infection status to compare hematological outcomes between \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative groups. The study protocol was approved by the Institutional Review Board at King Saud University, Riyadh, Saudi Arabia (Research Project No. E-24-8617), and the requirement for informed consent was waived due to the study's retrospective nature. All methods were performed in accordance with the relevant guidelines and regulations, including the Declaration of Helsinki and institutional guidelines.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Population and Data Collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eElectronic medical records were systematically reviewed for the period January 2015 to December 2024 at KKUH. The following variables were collected: demographic characteristics (age, sex, nationality), anthropometric measurements (weight, body mass index), clinical diagnoses (\u003cem\u003eH. pylori\u003c/em\u003e status, comorbidities), and laboratory parameters. Complete blood count parameters included red blood cell count (RBC), hemoglobin (Hgb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), white blood cell count (WBC), and platelet count (PLT). BMI and weight data were unavailable for some \u003cem\u003eH. pylori\u003c/em\u003e-negative participants due to incomplete medical records.\u003c/p\u003e\u003cp\u003eFrom hospital electronic medical records, we identified 1,895 patients diagnosed with enteric infections between 2015 and 2024. Of these, 653 patients had confirmed \u003cem\u003eH. pylori\u003c/em\u003e infection. After applying inclusion and exclusion criteria, 165 \u003cem\u003eH. pylori\u003c/em\u003e-positive patients were included. \u003cem\u003eH. pylori\u003c/em\u003e-negative participants were obtained from the family medicine clinic medical records within KKUH during 2023–2024. We reviewed records of individuals who had attended routine check-ups or treatment of acute, minor conditions (e.g., seasonal allergies, upper respiratory infections). \u003cem\u003eH. pylori\u003c/em\u003e-negative status was defined as the absence of documented \u003cem\u003eH. pylori\u003c/em\u003e infection in medical records. \u003cem\u003eH. pylori\u003c/em\u003e-negative participants were frequency-matched to \u003cem\u003eH. pylori\u003c/em\u003e-positive patients by age (± 5 years) and sex. After applying the same temporal criteria for CBC testing, 163 \u003cem\u003eH. pylori\u003c/em\u003e-negative participants were included.\u003c/p\u003e\u003cp\u003e\u003cem\u003e[\u003c/em\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cem\u003ehere]\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe inclusion criteria for both groups were age ≥ 18 years and the availability of complete CBC data. For \u003cem\u003eH. pylori\u003c/em\u003e-positive patients, CBC parameters were assessed from tests performed within 10 days before or 2 days after \u003cem\u003eH. pylori\u003c/em\u003e diagnosis to ensure temporal proximity to confirmed infection status. The final analysis included 328 participants (165 \u003cem\u003eH. pylori\u003c/em\u003e-positive, 163 \u003cem\u003eH. pylori\u003c/em\u003e-negative), providing adequate power for sex-stratified analyses.\u003c/p\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eData were analyzed using Python 3.11.13 with pandas (v2.2.2), scipy (v1.15.3), and statsmodels (v0.14.4) libraries. Continuous variables were expressed as mean ± standard deviation (SD), while categorical variables were presented as frequencies (percentages).\u003c/p\u003e\u003cp\u003eThe cohort design was chosen because participants were selected based on \u003cem\u003eH. pylori\u003c/em\u003e infection status, allowing comparison of hematological outcome frequencies between \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative groups. This design enables the calculation of relative risks and the assessment of absolute differences in hematological parameters.\u003c/p\u003e\u003cp\u003eGroup differences in continuous measures were assessed using independent samples t-tests, and categorical variables were compared using chi-square tests. The magnitude of the observed effects was determined using Cohen's d statistic, applying conventional interpretation guidelines (d = 0.2 indicating minor effects, d = 0.5 indicating moderate effects, and d = 0.8 indicating large effects).\u003c/p\u003e\u003cp\u003eFor our primary analysis examining sex-specific effects, we performed a two-way analysis of variance (ANOVA) to test for sex × \u003cem\u003eH. pylori\u003c/em\u003e status interactions. When interactions were significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) or marginally significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.10), stratified analyses were conducted within each sex. To control for multiple comparisons across nine CBC parameters, we applied Bonferroni correction, setting the adjusted significance threshold at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.006 for individual parameter comparisons.\u003c/p\u003e\u003cp\u003eClinical relevance was assessed by categorizing CBC parameters according to laboratory reference ranges (low, normal, high) and comparing distributions between groups. WHO anemia criteria were applied using sex-specific thresholds (hemoglobin \u0026lt; 12.0 g/dL for women, \u0026lt; 13.0 g/dL for men) based on the 2024 WHO guidelines \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. All 328 participants had complete hemoglobin and sex data required for the WHO anemia classification analysis.\u003c/p\u003e\u003cp\u003eAll the statistical tests were two-tailed, with \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 considered statistically significant for main effects, except for the interaction terms, where \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.10 was used, given their lower statistical power.\u003c/p\u003e\u003cp\u003ePower calculations were performed using Python's statsmodels (version 0.14.4). For sex-stratified comparisons using independent t-tests with Bonferroni correction (α = 0.006), the study achieved exceptional power (\u0026gt; 99%) to detect medium and large effect sizes in both males (n = 123) and females (n = 205). For detecting sex × \u003cem\u003eH. pylori\u003c/em\u003e interactions using two-way ANOVA (α = 0.10), the study had modest power (10.2–10.5%) for the observed interaction effects. Despite conservative power for interaction detection, significant sex-specific effects were identified for the hematocrit (\u003cem\u003ep\u003c/em\u003e = 0.0146) and RBC count (\u003cem\u003ep\u003c/em\u003e = 0.0122), suggesting robust biological differences. The minimum detectable effect sizes with 80% power were d = 0.65 for males and d = 0.50 for females, confirming exceptional power to detect clinically meaningful differences in hematological parameters.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Quality and Management\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrior to analysis, the data underwent systematic quality control procedures. Outliers were identified using both statistical methods (values beyond 3 standard deviations) and clinical plausibility assessment. One extreme outlier (platelet count of 10 × 10³/µL) was removed and treated as missing data after clinical review confirmed a probable data entry error. Unit standardization was performed where necessary (hemoglobin converted from mg/dL to g/dL; MCHC from g/L to g/dL).\u003c/p\u003e\u003cp\u003eMissing data were minimal for CBC parameters (\u0026lt; 1%). However, demographic variables had higher rates of missingness in the \u003cem\u003eH. pylori\u003c/em\u003e-negative group (BMI: 11.7%, weight: 66.3%, nationality: 60.1%). The final analytical dataset comprised 328 participants with complete CBC data for all primary analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eStudy Population Characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 328 participants were included, comprising 165 \u003cem\u003eH. pylori\u003c/em\u003e-positive patients and 163 \u003cem\u003eH. pylori\u003c/em\u003e-negative participants. The groups were well-matched for age (45.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.6 vs. 45.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1 years, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.828) and sex distribution (37.6% vs. 37.4% male, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.000). No significant differences were observed in BMI between \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative participants (28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 vs. 28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9 kg/m\u0026sup2;, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.682). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the demographic and clinical characteristics of the study participants.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic and Clinical Characteristics of Study Participants by \u003cem\u003eH. pylori\u003c/em\u003e Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e-positive (n\u0026thinsp;=\u0026thinsp;165)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e-negative (n\u0026thinsp;=\u0026thinsp;163)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62 (37.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e61 (37.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e103 (62.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e102 (62.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.828\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u0026sup2;), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD*\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.682\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI categories, n (%)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27 (16.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22 (13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31 (18.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56 (34.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49 (29.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e58 (35.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52 (31.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19 (11.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (kg), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD*\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e75.5\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e76.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*1 BMI data not available for 52 \u003cem\u003eH. pylori\u003c/em\u003e-positive and 19 \u003cem\u003eH. pylori\u003c/em\u003e-negative participants\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*2 Weight data not available for 35 \u003cem\u003eH. pylori\u003c/em\u003e-positive and 108 \u003cem\u003eH. pylori\u003c/em\u003e-negative participants\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMI\u0026thinsp;=\u0026thinsp;Body Mass Index; SD\u0026thinsp;=\u0026thinsp;Standard Deviation\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eWHO BMI categories: Underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), Normal (18.5\u0026ndash;24.9 kg/m\u0026sup2;), Overweight (25.0-29.9 kg/m\u0026sup2;), Obese (\u0026ge;\u0026thinsp;30.0 kg/m\u0026sup2;).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e[\u003c/em\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cem\u003ehere]\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOverall CBC Parameter Comparisons\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnalysis of nine CBC parameters revealed four statistically significant differences between the \u003cem\u003eH. pylori\u003c/em\u003e-positive and \u003cem\u003eH. pylori\u003c/em\u003e-negative groups Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Compared to \u003cem\u003eH. pylori\u003c/em\u003e-negative participants, \u003cem\u003eH. pylori\u003c/em\u003e-positive participants exhibited significantly lower hemoglobin (12.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87 vs. 13.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88 g/dL, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), hematocrit (39.59\u0026thinsp;\u0026plusmn;\u0026thinsp;5.27 vs. 41.45\u0026thinsp;\u0026plusmn;\u0026thinsp;5.19%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), MCV (84.31\u0026thinsp;\u0026plusmn;\u0026thinsp;7.54 vs. 86.58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.29 fL, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), and higher RDW (14.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42 vs. 13.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). This hematologic profile is consistent with IDA, commonly associated with \u003cem\u003eH. pylori\u003c/em\u003e infection. No significant differences were observed in MCH, MCHC, RBC count, WBC, or platelet count.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComplete Blood Count Parameter Comparison Between \u003cem\u003eH. pylori\u003c/em\u003e-Positive and \u003cem\u003eH. pylori\u003c/em\u003e-Negative Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHp(+)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;165)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHp(\u0026ndash;)\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;163)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEffect Size\u003c/p\u003e\u003cp\u003e(Cohen's d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDirection of Change\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBC (\u0026times;10⁶/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.726\u0026thinsp;\u0026plusmn;\u0026thinsp;0.709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.822\u0026thinsp;\u0026plusmn;\u0026thinsp;0.710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHgb (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e12.839\u0026thinsp;\u0026plusmn;\u0026thinsp;1.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e13.389\u0026thinsp;\u0026plusmn;\u0026thinsp;1.880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHct (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e39.585\u0026thinsp;\u0026plusmn;\u0026thinsp;5.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e41.451\u0026thinsp;\u0026plusmn;\u0026thinsp;5.194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCV (fL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e84.314\u0026thinsp;\u0026plusmn;\u0026thinsp;7.537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e86.583\u0026thinsp;\u0026plusmn;\u0026thinsp;7.286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.306\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCH (pg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e27.372\u0026thinsp;\u0026plusmn;\u0026thinsp;3.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e27.978\u0026thinsp;\u0026plusmn;\u0026thinsp;3.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCHC (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e32.404\u0026thinsp;\u0026plusmn;\u0026thinsp;1.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e32.253\u0026thinsp;\u0026plusmn;\u0026thinsp;1.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIncreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRDW (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e14.406\u0026thinsp;\u0026plusmn;\u0026thinsp;2.416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e13.688\u0026thinsp;\u0026plusmn;\u0026thinsp;1.628\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIncreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC (\u0026times;10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e7.300\u0026thinsp;\u0026plusmn;\u0026thinsp;2.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e7.163\u0026thinsp;\u0026plusmn;\u0026thinsp;2.422\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.641\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIncreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT (\u0026times;10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e294.280\u0026thinsp;\u0026plusmn;\u0026thinsp;90.900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e303.628\u0026thinsp;\u0026plusmn;\u0026thinsp;76.660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecreased\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eData presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Bold \u003cem\u003ep\u003c/em\u003e-values indicate statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Hp(+)\u0026thinsp;=\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e positive; Hp(\u0026ndash;)\u0026thinsp;=\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e negative.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e[\u003c/em\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cem\u003ehere]\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical Distribution of CBC Abnormalities\u003c/b\u003e\u003c/p\u003e\u003cp\u003eClinical categorization analysis showed notable hematological abnormalities among \u003cem\u003eH. pylori\u003c/em\u003e-positive patients compared to \u003cem\u003eH. pylori\u003c/em\u003e-negative participants (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The prevalence of anemia was higher among infected individuals (27.3% vs. 19.0%), with corresponding increases observed in low hematocrit (21.2% vs. 12.3%) and red blood cell count deficiencies (16.4% vs. 14.1%). Microcytosis (MCV\u0026thinsp;\u0026lt;\u0026thinsp;80 fL), hypochromia (MCH\u0026thinsp;\u0026lt;\u0026thinsp;27 pg), and elevated RDW were also more prevalent in patients with \u003cem\u003eH. pylori-positive\u003c/em\u003e status.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical Distribution of CBC Parameters by \u003cem\u003eH. pylori\u003c/em\u003e Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e\u003cp\u003eHp(+)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e\u003cp\u003eHp(\u0026ndash;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNormal n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAbnormal n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLow n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNormal n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHigh n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAbnormal n(%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBC (\u0026times;10⁶/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.2\u0026ndash;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27 (16.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e135 (81.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3 (1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e30 (18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e23 (14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e136 (83.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e4 (2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e27 (16.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHgb (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.0\u0026ndash;18.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e120 (72.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e45 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e31 (19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e132 (81.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e31 (19.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHct (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u0026ndash;48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35 (21.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e123 (74.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42 (25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e20 (12.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e130 (79.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e13 (8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e33 (20.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCV (fL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80\u0026ndash;95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36 (21.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e122 (73.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7 (4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e43 (26.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e21 (12.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e132 (81.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e10 (6.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e31 (19.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCH (pg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27\u0026ndash;31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58 (35.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e94 (57.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13 (7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e71 (43.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48 (29.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e102 (62.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e13 (8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e61 (37.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCHC (g/dL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.0\u0026ndash;36.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47 (28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e118 (71.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e47 (28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e60 (36.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e103 (63.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e60 (36.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRDW (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.6\u0026ndash;14.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e117 (70.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e47 (28.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e48 (29.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2 (1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e128 (78.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e33 (20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e35 (21.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC (\u0026times;10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0\u0026ndash;11.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (3.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e150 (90.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9 (5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15 (9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10 (6.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e141 (86.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e12 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e22 (13.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT (\u0026times;10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150\u0026ndash;400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5 (3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e144 (87.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15 (9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20 (12.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e145 (89.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e18 (11.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e18 (11.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eAverage abnormality rate Hp(+): 24.3%, Hp(\u0026ndash;): 21.7%. Excess clinical burden in Hp(+): +2.7%.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003eData presented as the number of participants (n%). Abnormal\u0026thinsp;=\u0026thinsp;Low\u0026thinsp;+\u0026thinsp;High values. Hp(+)\u0026thinsp;=\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e positive; Hp(\u0026ndash;)\u0026thinsp;=\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e negative.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e[\u003c/em\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cem\u003ehere]\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSex-Stratified Analysis Results\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSex-stratified analyses revealed significant sex \u0026times; \u003cem\u003eH. pylori\u003c/em\u003e interactions for hematocrit (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0146) and RBC count (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0122), and a near-significant interaction for hemoglobin (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0511), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSex-Stratified Analysis of Complete Blood Count Parameters by \u003cem\u003eH. pylori\u003c/em\u003e Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSex\u0026times;Hp Interaction\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHp\u0026thinsp;+\u0026thinsp;vs Hp-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHp\u0026thinsp;+\u0026thinsp;vs Hp-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ed\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.2\u0026ndash;6.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e4.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.0257\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.0122\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHgb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.0\u0026ndash;18.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54 vs 12.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.2002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e13.60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e14.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.0053\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.512\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.0511\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHct\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u0026ndash;48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4.32 vs 39.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.1337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.39\u0026thinsp;\u0026plusmn;\u0026thinsp;6.18\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e44.93\u0026thinsp;\u0026plusmn;\u0026thinsp;5.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.0146\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80\u0026ndash;95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.98\u0026thinsp;\u0026plusmn;\u0026thinsp;7.24 vs 86.81\u0026thinsp;\u0026plusmn;\u0026thinsp;7.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.0055\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e84.86\u0026thinsp;\u0026plusmn;\u0026thinsp;8.04\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e86.21\u0026thinsp;\u0026plusmn;\u0026thinsp;7.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.3395\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.3846\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27\u0026ndash;31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99 vs 27.91\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.0358\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e28.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.8019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.2914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.0\u0026ndash;36.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27 vs 32.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e32.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.1578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.2921\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRDW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.6\u0026ndash;14.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50 vs 13.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.0168\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14.27\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e13.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.0416\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.9430\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.0\u0026ndash;11.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.97\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e7.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8476\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.85\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003c/p\u003e\u003cp\u003evs\u003c/p\u003e\u003cp\u003e7.38\u0026thinsp;\u0026plusmn;\u0026thinsp;2.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.4197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.3845\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150\u0026ndash;400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e298.51\u0026thinsp;\u0026plusmn;\u0026thinsp;84.98 vs 312.18\u0026thinsp;\u0026plusmn;\u0026thinsp;77.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.2303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e287.32\u0026thinsp;\u0026plusmn;\u0026thinsp;100.22 vs 289.33\u0026thinsp;\u0026plusmn;\u0026thinsp;74.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.9000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.5430\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Bold, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. d, Cohen's d effect size. Sex\u0026times;Hp interaction \u003cem\u003ep\u003c/em\u003e from 2-way ANOVA. Hp+/-, \u003cem\u003eH. pylori\u003c/em\u003e-positive/negative.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e[\u003c/em\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cem\u003ehere]\u003c/em\u003e\u003c/p\u003e\u003cp\u003eMales with \u003cem\u003eH. pylori\u003c/em\u003e infection demonstrated significant reductions in hemoglobin (d=-0.512, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), hematocrit (d=-0.619, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and RBC count (d=-0.407, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026), indicating substantial anemia. Females primarily exhibited alterations in red cell indices, including decreased MCV (d=-0.392, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), MCH (d=-0.295, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), and increased RDW (d\u0026thinsp;=\u0026thinsp;0.337, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), without significant changes in hemoglobin or hematocrit. Figure S2 presents forest plots of sex-stratified effect sizes for all CBC parameters.\u003c/p\u003e\u003cp\u003eThe sex-specific percentage changes shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e underscore these differences, with males experiencing marked decreases in hemoglobin (-7.0%), hematocrit (-7.9%), and RBC (-6.5%), and females exhibiting reductions in MCV (-3.3%), MCH (-3.2%), and an increase in RDW (+\u0026thinsp;5.3%).\u003c/p\u003e\u003cp\u003e\u003cem\u003e[\u003c/em\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cem\u003ehere]\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSex-Specific Anemia Prevalence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eApplication of the WHO sex-specific anemia criteria revealed sex-dependent differences (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Among males, significantly more \u003cem\u003eH. pylori\u003c/em\u003e-infected individuals met anemia criteria compared to \u003cem\u003eH. pylori\u003c/em\u003e-negative participants (32.3% vs 11.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010). In contrast, females showed a smaller, non-significant difference (31.1% vs 24.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.372), reinforcing distinct sex-specific patterns in \u003cem\u003eH. pylori\u003c/em\u003e-associated anemia.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective cohort study demonstrates that \u003cem\u003eH. pylori\u003c/em\u003e infection affects males and females through fundamentally different hematological mechanisms. The significant sex \u0026times; \u003cem\u003eH. pylori\u003c/em\u003e interactions for hematocrit (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0146) and red blood cell count (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0122), with a near-significant interaction for hemoglobin (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0511), provide statistical evidence for distinct biological responses. Males with \u003cem\u003eH. pylori\u003c/em\u003e infection demonstrated substantial reductions in hemoglobin (d=-0.512, medium effect), hematocrit (d=-0.619, medium-large effect), and RBC count (d=-0.407, small-medium effect). At the same time, females exhibited predominant changes in red cell indices without significant alterations in hemoglobin or hematocrit. These sex-specific patterns suggest different underlying mechanisms and challenge current uniform approaches to \u003cem\u003eH. pylori\u003c/em\u003e-associated hematological disorders.\u003c/p\u003e\u003cp\u003eThe divergent hematological patterns observed reflect sex-specific pathophysiological mechanisms underlying \u003cem\u003eH. pylori\u003c/em\u003e infection. Males demonstrate enhanced inflammatory responses, as evidenced by higher cyclooxygenase-2 (COX-2) expression in response to \u003cem\u003eH. pylori\u003c/em\u003e infection, whereas females showed no COX-2 response \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Conversely, baseline TFF1 levels are significantly higher in women than in men, and \u003cem\u003eH. pylori\u003c/em\u003e infection significantly reduces TFF1 in women \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, suggesting sex-specific alterations in protective factors. Furthermore, \u003cem\u003eH. pylori\u003c/em\u003e exhibits selective utilization of steroid hormones, which may contribute to sex-specific colonization patterns. The bacterium can absorb estrogens (which have 3-OH structures) but cannot metabolize them, while being unable to absorb testosterone or progesterone due to their 3\u0026thinsp;=\u0026thinsp;O molecular structure, which prevents membrane interaction \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBuilding on these differential inflammatory responses, hormonal mechanisms provide a crucial framework for understanding the observed sex differences. The protective effect of estrogen emerges as a key factor, with estrogen treatment eliminating \u003cem\u003eH. pylori\u003c/em\u003e-induced gastric cancer in male mice and significantly decreasing neutrophil infiltration \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The molecular mechanism involves the estrogen-related receptor gamma (ESRRG), which suppresses \u003cem\u003eH. pylori\u003c/em\u003e infection by directly binding to and upregulating the tumor suppressor TFF1 \u003csup\u003e37\u003c/sup\u003e. However, \u003cem\u003eH. pylori\u003c/em\u003e-induced inflammation activates NF-κB signaling, which inhibits ESRRG-mediated TFF1 activation, creating a pathogenic feedback loop where infection suppresses its own protective mechanisms \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This hormonal regulation extends to iron metabolism, where clinical evidence demonstrates estrogen's potent effects: during IVF treatment, marked estrogen stimulation decreased median hepcidin levels from 4.85 to 1.43 ng/mL, demonstrating estrogen's regulatory role in iron homeostasis \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This hormonal regulation likely contributes to females' ability to buffer against full anemia, even with microcytic red cell changes; hemoglobin remains stable, explaining why females in our study maintained relatively stable hemoglobin levels despite developing microcytic changes characteristic of early iron deficiency.\u003c/p\u003e\u003cp\u003eOur findings both confirm and extend the growing literature on sex-specific effects of \u003cem\u003eH. pylori\u003c/em\u003e. A comprehensive meta-analysis of 244 studies found males had greater odds of \u003cem\u003eH. pylori\u003c/em\u003e infection than females did, supporting our observation of sex-specific vulnerability \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. However, their analysis did not examine hematological outcomes or test for formal interactions as we have done. Recent studies from diverse populations have reported variable associations between \u003cem\u003eH. pylori\u003c/em\u003e and anemia that vary by sex. Wang et al. (2024) similarly reported that \u003cem\u003eH. pylori\u003c/em\u003e infection was associated with IDA specifically in women (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031) but not men, though their analysis was limited to iron markers without examining the full spectrum of CBC parameters \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. A 2022 sub-Saharan study found complex relationships between \u003cem\u003eH. pylori\u003c/em\u003e infection and anemia, with males showing higher susceptibility to certain hematological changes \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Our findings provide a mechanistic explanation for these observations by demonstrating that males and females develop different types of hematological abnormalities. Males experience reductions in hemoglobin, hematocrit, and RBC count, indicative of overt anemia, while females show changes in red cell indices, suggesting early-stage iron deficiency without frank anemia.\u003c/p\u003e\u003cp\u003e These mechanistic insights from our cohort study have immediate clinical relevance for current practice guidelines. Current guidelines recommend \u003cem\u003eH. pylori\u003c/em\u003e testing in patients with unexplained iron deficiency anemia, without sex-specific considerations \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Our findings suggest that the hematological presentation of \u003cem\u003eH. pylori\u003c/em\u003e infection differs substantially by sex, indicating the need for tailored diagnostic approaches. For male patients, the presence of reduced hemoglobin, hematocrit, or RBC count should prompt evaluation for \u003cem\u003eH. pylori\u003c/em\u003e, even in the absence of microcytic indices. The large effect sizes observed for hematocrit (d=-0.619) and hemoglobin (d=-0.512) indicate substantial clinical relevance for \u003cem\u003eH. pylori\u003c/em\u003e screening in males with these abnormalities. Conversely, in females, the combination of low MCV, low MCH, and elevated RDW, even with normal hemoglobin, may indicate \u003cem\u003eH. pylori\u003c/em\u003e-associated iron deficiency. Treatment considerations should account for potential sex-specific factors, with post-menopausal women who lose estrogen's protective effects requiring enhanced surveillance, given the potential loss of estrogen-mediated protection against \u003cem\u003eH. pylori\u003c/em\u003e-associated complications.\u003c/p\u003e\u003cp\u003eThis retrospective cohort study has several limitations. First, the retrospective design using electronic medical records limits our ability to establish temporal relationships between \u003cem\u003eH. pylori\u003c/em\u003e infection and hematological changes. Second, our participant selection from patients with enteric infections ensures confirmed \u003cem\u003eH. pylori\u003c/em\u003e status with appropriate clinical context, though this may not capture asymptomatic \u003cem\u003eH. pylori\u003c/em\u003e carriers. Third, we lacked comprehensive data on factors that could influence hematological parameters, including iron supplementation, menstrual history, and dietary patterns.\u003c/p\u003e\u003cp\u003eFinally, our single-center study in Saudi Arabia may limit generalizability to other populations, as \u003cem\u003eH. pylori\u003c/em\u003e strains vary geographically in virulence factors, and host genetic factors influencing iron metabolism may differ across ethnic groups.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e infection affects males and females through distinct hematological mechanisms. Males typically develop anemia characterized by reduced hemoglobin, hematocrit, and RBC count, whereas females exhibit changes in red cell indices. These sex-specific patterns from our retrospective cohort study support the need for tailored diagnostic approaches and treatment strategies in \u003cem\u003eH. pylori\u003c/em\u003e-associated hematological disorders.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their appreciation to the Ongoing Research Funding program (ORF-2025-1443), King Saud University, Riyadh, Saudi Arabia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by the Ongoing Research Funding program (ORF-2025-1443), King Saud University, Riyadh, Saudi Arabia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interests exist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, F.A., Y.A.; methodology, F.A., A.M.Abd.; software, F.A., A.A.; validation, F.A., A.M.Abd.; formal analysis, F.A., R.F.; investigation, F.A., A.M.Abd., R.F., Y.A., A.M.Alm., H.A., A.T.J., M.A.; resources, F.A.; data curation, F.A., A.M.Abd., R.F., Y.A., A.M.Alm., H.A., A.T.J., M.A., A.T.A., A.A.; writing original draft preparation, F.A.; writing, review and editing, all authors; visualization, F.A., Y.A.; supervision, F.A.; project administration, F.A.; funding acquisition, F.A. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHooi JKY, Lai WY, Ng WK, et al. Global Prevalence of Helicobacter pylori Infection: Systematic Review and Meta-Analysis. \u003cem\u003eGastroenterology. \u003c/em\u003e2017;153(2):420\u0026ndash;429.\u003c/li\u003e\n\u003cli\u003eZamani M, Ebrahimtabar F, Zamani V, et al. Systematic review with meta-analysis: the worldwide prevalence of Helicobacter pylori infection. \u003cem\u003eAliment Pharmacol Ther. \u003c/em\u003e2018;47(7):868\u0026ndash;876.\u003c/li\u003e\n\u003cli\u003eMarshall BJ, Warren JR. Unidentified curved bacilli in the stomach of patients with gastritis and peptic ulceration. \u003cem\u003eLancet. \u003c/em\u003e1984;1(8390):1311\u0026ndash;1315.\u003c/li\u003e\n\u003cli\u003eMalfertheiner P, Megraud F, O\u0026apos;Morain CA, et al. 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Anabolic utilization of steroid hormones in Helicobacter pylori. \u003cem\u003eFEMS Microbiol Lett. \u003c/em\u003e2009;297(2):173\u0026ndash;179.\u003c/li\u003e\n\u003cli\u003eSheh A, Ge Z, Parry NM, et al. 17beta-estradiol and tamoxifen prevent gastric cancer by modulating leukocyte recruitment and oncogenic pathways in Helicobacter pylori-infected INS-GAS male mice. \u003cem\u003eCancer Prev Res (Phila). \u003c/em\u003e2011;4(9):1426\u0026ndash;1435.\u003c/li\u003e\n\u003cli\u003eKang MH, Eyun SI, Park YY. Estrogen-related receptor-gamma influences Helicobacter pylori infection by regulating TFF1 in gastric cancer. \u003cem\u003eBiochem Biophys Res Commun. \u003c/em\u003e2021;563:15\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eLehtihet M, Bonde Y, Beckman L, et al. Circulating Hepcidin-25 Is Reduced by Endogenous Estrogen in Humans. \u003cem\u003ePLoS One. \u003c/em\u003e2016;11(2):e0148802.\u003c/li\u003e\n\u003cli\u003eAbubakar I, Morais S, Ferro A, Lunet N. Sex-differences in the prevalence of Helicobacter pylori infection in pediatric and adult populations: Systematic review and meta-analysis of 244 studies. 2017.\u003c/li\u003e\n\u003cli\u003eWang ZT, Tan WT, Meng MM, et al. The correlation between Helicobacter pylori infection and iron deficiency anemia in women. \u003cem\u003eEur Rev Med Pharmacol Sci. \u003c/em\u003e2024;28(4):1541\u0026ndash;1553.\u003c/li\u003e\n\u003cli\u003eEyoum Bille BB, Kouitcheu Mabeku LB. Relationship between active Helicobacter pylori infection and anemia, iron deficiency, iron deficiency anemia: A cross-sectional study in a sub-Saharan setting. \u003cem\u003eJGH Open. \u003c/em\u003e2022;6(8):554\u0026ndash;568.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Helicobacter pylori, sex differences, complete blood count, anemia, iron deficiency, hematological parameters, sex-stratified analysis, retrospective cohort study","lastPublishedDoi":"10.21203/rs.3.rs-7142446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7142446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003e\u003cem\u003eHelicobacter pylori\u003c/em\u003e infection affects approximately 50% of the global population and is associated with hematological manifestations. Despite established associations with anemia, sex-specific effects remain unexplored, limiting our understanding of differential mechanisms and personalized treatment strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective cohort study using electronic medical records from 2015\u0026ndash;2024 at King Khalid University Hospital, Saudi Arabia. Among 1,895 patients with enteric infections, we identified 165 \u003cem\u003eH. pylori\u003c/em\u003e-positive patients and 163 \u003cem\u003eH. pylori\u003c/em\u003e-negative participants frequency-matched by age and sex from family medicine clinics. Nine complete blood count parameters were analyzed from tests performed within 10 days before or 2 days after \u003cem\u003eH. pylori\u003c/em\u003e diagnosis. Sex-stratified analyses were performed via a two-way ANOVA to test for sex \u0026times; \u003cem\u003eH. pylori\u003c/em\u003e interactions, with Cohen's d effect sizes reported.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eSignificant sex \u0026times; \u003cem\u003eH. pylori\u003c/em\u003e interactions were observed for hematocrit (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0146) and red blood cell count (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0122). Males demonstrated anemia with large effect sizes for hematocrit (d=-0.619, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hemoglobin (d=-0.512, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), and RBC count (d=-0.407, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026). Females exhibited changes in red cell indices: reduced mean corpuscular volume (d=-0.392, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), mean corpuscular hemoglobin (d=-0.295, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), and elevated red cell distribution width (d\u0026thinsp;=\u0026thinsp;0.337, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017). \u003cem\u003eH. pylori\u003c/em\u003e infection significantly increased anemia rates in males (32.3% vs 11.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) but not in females (31.1% vs 24.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.372), with an overall rate of 27.3% vs 19.0%.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003e\u003cem\u003eH. pylori\u003c/em\u003e infection affects males and females through distinct hematological mechanisms. Males experience anemia affecting hemoglobin and hematocrit, whereas females develop changes in red cell indices. These findings from our retrospective cohort study support the use of sex-specific diagnostic and treatment strategies.\u003c/p\u003e","manuscriptTitle":"Sex-stratified analysis of complete blood count parameters in Helicobacter pylori infection: A retrospective cohort study revealing distinct hematological mechanisms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 09:13:01","doi":"10.21203/rs.3.rs-7142446/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":"cdd44c77-f310-4a82-b051-ffd1a454423e","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56141330,"name":"Health sciences/Diseases"},{"id":56141331,"name":"Health sciences/Gastroenterology"},{"id":56141332,"name":"Health sciences/Medical research"},{"id":56141333,"name":"Biological sciences/Microbiology"},{"id":56141334,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-02-04T11:26:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 09:13:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7142446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7142446","identity":"rs-7142446","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}