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Table 2 Logistic regression analysis of clinical features for the risk of RVO in the development dataset

From: Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea

 

Univariate model*

Adjusted model†

OR (95% CI)

P-value

OR (95% CI)

P-value

Age (year, per 1 unit increase)

1.06 (1.04–1.08)

< 0.001

1.06 (1.03–1.08)

< 0.001

Sex, female

0.95 (0.62–1.44)

0.810

  

BMI (kg/m2, per 1 unit increase)

1.04 (0.98–1.10)

0.198

  

Household income

    

   Very low

Reference

   

   Low

0.55 (0.32–0.94)

0.029

  

   Moderate

0.44 (0.25–0.78)

0.005

  

   High

0.34 (0.19–0.62)

< 0.001

  

Current smoker (%)

1.02 (0.58–1.78)

0.934

1.42 (0.78–2.57)

0.252

Alcohol, ≥ 1 drink/week (%)

0.67 (0.43–1.05)

0.081

  

Blood pressure

    

SBP (mmHg, per 1 unit increase)

1.03 (1.01–1.04)

< 0.001

  

DBP (mmHg, per 1 unit increase)

1.02 (0.99–1.04)

0.147

1.03 (1.01–1.05)

0.004

Hypertension

4.07 (2.65–6.25)

< 0.001

2.78 (1.74–4.44)

< 0.001

Diabetes mellitus

0.79 (0.39–1.57)

0.505

0.47 (0.23–0.95)

0.036

Dyslipidemia

1.49 (0.95–2.35)

0.082

  

Stroke

2.95 (1.18–7.33)

0.020

  

Heart disease

2.16 (0.94–4.98)

0.069

  

Osteoarthritis

1.31 (0.76–2.25)

0.327

  

Osteoporosis

2.15 (1.21–3.82)

0.009

  

Fasting glucose (mg/dL, per 1 unit increase)

0.99 (0.98–1.01)

0.630

  

Total cholesterol (mg/dL, per 1 unit increase)

0.99 (0.98-1.00)

0.051

  

Triglyceride (mg/dL, per 1 unit increase)

0.99 (0.99-1.00)

0.226

0.99 (0.99-1.00)

0.088

AST (IU/L, per 1 unit increase)

0.99 (0.98–1.02)

0.868

  

ALT (IU/L, per 1 unit increase)

0.99 (0.98–1.01)

0.459

  

Creatinine (mg/dL, per 1 unit increase)

1.37 (0.95–1.98)

0.096

  

WBC (103cells/µL, per 1 unit increase)

1.12 (1.01–1.25)

0.039

1.10 (0.98–1.23)

0.117

Hemoglobin (mg/dL, per 1 unit increase)

1.00 (0.87–1.14)

0.999

  

Platelet (109/L, per 1 unit increase)

0.99 (0.99-1.00)

0.224

  
  1. * Univariate logistic regression analysis for each variable
  2. † Multivariable logistic regression with stepwise backward selection model