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A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level
Published on: January 19, 2024
Altitude-Related Laboratory Changes and a Novel Hemoglobin Estimation Model: A Retrospective Analysis in Children and
1Department of Emergency Medicine, Harakani State Hospital, Kars, Turkey.
Introduction:
Hypobaric hypoxia at higher residential altitudes may modify routine laboratory parameters and complicate their interpretation in emergency care. We examined associations between altitude (0-2500 m) and laboratory findings and developed a hemoglobin estimation model.
Methods:
This single-center, retrospective cross-sectional study included 2302 patients aged ≥ 1 year admitted to the Emergency Department of Kars Harakani State Hospital on January 1-3 and July 1-3, 2024. Patients were categorized as children (1-17 years) or adults (≥ 18 years). Hematological and biochemical results were retrieved from electronic records. Altitude-laboratory associations were analyzed using correlation and linear regression. A multivariable regression model was constructed to identify determinants of hemoglobin variation.
Results:
Among 2302 admissions, 30.8% were pediatric. Hemoglobin, hematocrit, erythrocyte indices, pO2, and SaO2 demonstrated the most consistent altitude-related patterns. In adults, altitude showed positive associations with glucose, urea, creatinine, COHb, MetHb, calcium, ALT, AST, bilirubin, and selected erythrocyte and platelet indices, and negative associations with SaO2, pO2, PLT, PCT, GFR, and HCO3 (all p < 0.05). Most parameters were not significantly associated with altitude in children. SaO2 and pO2 were lower in summer than winter (p < 0.05). The final model explained 83% of hemoglobin variability, incorporating altitude, age, sex, smoking, pregnancy, malignancy, and chronic disease.
Conclusion:
Residential altitude was associated with measurable variation in hematological, biochemical, and oxygenation parameters among emergency department patients. Altitude should be considered when interpreting laboratory results in clinical practice. The proposed hemoglobin model integrates altitude and clinical variables to characterize hemoglobin variability within this cohort.
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