This retrospective cross-sectional study investigated whether a study-defined high-altitude renal-metabolic stress phenotype is associated with albuminuria-related kidney involvement among hospitalized patients with diabetes in Lhasa, Tibet. The authors aimed to test an exploratory composite score reflecting erythrocyte abnormalities, metabolic disturbance and blood pressure to determine relationships with urinary albumin excretion.
The analysis included 867 hospitalized patients with diabetes in Lhasa, Tibet. Urinary albumin-to-creatinine ratio (ACR) data were available for 724 patients, who comprised the analytic sample for albuminuria outcomes. The report is a retrospective cross-sectional study using hospital data collected in this high-altitude clinical setting.
Investigators constructed an exploratory HARS-like score composed of four study-defined components: 1) high hemoglobin, 2) high red blood cell distribution width (RDW), 3) high serum uric acid, and 4) hypertension. The score was used to represent clustering of erythrocyte abnormality, hyperuricemia and elevated blood pressure as a putative high-altitude renal-metabolic stress phenotype. The abstract reports score thresholds used for analysis (score ≥ 2 for high stress and score ≥ 3 for severe stress). Details of component cutpoints were not reported in the abstract.
Albuminuria and macroalbuminuria were defined using urinary ACR thresholds: albuminuria as ACR ≥ 30 mg/g and macroalbuminuria as ACR ≥ 300 mg/g. These definitions were applied to the 724 patients with available ACR data to estimate prevalence and to model associations with the exploratory HARS-like score.
Associations between the exploratory HARS-like score and albuminuria outcomes were estimated using modified Poisson regression to calculate adjusted prevalence ratios (PRs). Models adjusted for age, sex, diabetes duration, body mass index (BMI), HbA1c and fasting plasma glucose. The investigators additionally report sensitivity assessments that included estimated glomerular filtration rate (eGFR) adjustment, alternative score definitions, and extended confounder adjustment; precise additional covariates were not detailed in the abstract.
Among the 724 patients with ACR data, albuminuria was present in 306 patients (42.3%) and macroalbuminuria in 102 patients (14.1%). High exploratory HARS-like stress, defined as score ≥ 2, was associated with both albuminuria (adjusted PR 1.70, 95% confidence interval [CI] 1.38–2.08) and macroalbuminuria (adjusted PR 2.82, 95% CI 1.84–4.33) after the specified adjustments. A higher threshold representing more severe stress (score ≥ 3) demonstrated a stronger association with macroalbuminuria, indicating a dose–response relationship between the composite stress score and the severity of albuminuria.
Results were reported as broadly consistent after adjustment for estimated glomerular filtration rate and when alternative definitions of the score were used, as well as after extended available-confounder adjustment. The authors highlight a subgroup finding: patients with concurrent high hemoglobin and high RDW exhibited greater albuminuria burden, suggesting that specific combinations of the composite components may identify particularly affected subgroups.
In this hospitalized Tibetan population with diabetes, clustering of erythrocyte abnormality (high hemoglobin and high RDW), hyperuricemia, and hypertension—captured by an exploratory HARS-like score—was associated with higher prevalence of albuminuria and especially macroalbuminuria. The authors conclude that this composite phenotype may mark renal-metabolic stress at high altitude that relates to albuminuric kidney involvement. They explicitly note that external validation of the score and findings is needed. The abstract does not report component cutpoints, temporal data, causality assessment, or detailed confounder lists beyond those adjusted for in models; these details were not provided in the source abstract.
The study design is retrospective and cross-sectional, limiting causal inference. The authors call for external validation, which implies potential limitations in generalizability beyond this hospitalized population in Lhasa. Specific cutpoints for the exploratory score components and full covariate lists for extended adjustments were not reported in the abstract.