Table 2.
Analyzing routine hematological parameters and hospital mortality using multivariable logistic regression model
| Univariable | Multivariable | |||
|---|---|---|---|---|
| OR (95%CI) | P | OR (95%CI) | P | |
| Age, per 1 year | 1.03 (1.00‐1.05) | .05 | — | — |
| WBC, per 109/L | 1.18 (1.11‐1.26) | <.01 | 1.09 (1.01‐1.18) | .02 |
| Eos, per 1% | 0.40 (0.25‐0.64) | <.01 | — | — |
| Mon, per 1% | 0.79 (0.69‐0.90) | <.01 | — | — |
| NLR, per 1 | 1.10 (1.06‐1.13) | <.01 | 1.07 (1.03‐1.11) | <.01 |
| RDW, per 1% | 1.32 (1.12‐1.55) | <.01 | — | — |
| NIHSS, per 1 | 1.18 (1.10‐1.26) | <.01 | 1.17 (1.09‐1.25) | <.01 |
OR, odds ratio; WBC, white blood cell; NLR, neutrophil to lymphocyte ratio; Eos, eosinophil; Mon, monocyte; RDW, red blood cell distribution width.
Forward conditional logistic regression model was used and the variables included in model including age, gender, WBC, eosinophil, monocyte, RDW, NIHSS, hypertension, diabetes, hyperlipidemia, coronary artery disease. Age, gender, WBC, eosinophil, monocyte, RDW and NIHSS were expressed as continuous variable, and hypertension, diabetes, hyperlipidemia and coronary artery disease were expressed as categorical variable.