Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.
Skip to main content

Table 4 Logistic regression analysis of candidate variables for the model

From: A novel nomogram prediction model for postoperative atrial fibrillation in patients undergoing laparotomy

 

β

Standard error

Wald χ2

OR (95% CI)

P value

Intercept

 − 1.9119

3.5013

 − 0.55

0.1478 (0.0001–145.4922)

0.5850

CRP

0.0216

0.0108

2.00

1.0219 (1.0006–1.0445)

0.0452

NT-pro BNP

0.0001

0.0002

0.63

1.0001 (0.9998–1.0006)

0.5307

LMR

 − 0.6304

0.2205

 − 2.86

0.5324 (0.3352–0.8010)

0.0042

Ca

 − 1.3100

1.5371

 − 0.85

0.2698 (0.0120–5.1883)

0.3941

Albumin

 − 0.0209

0.0661

 − 0.32

0.9793 (0.8576–1.1147)

0.7521

BUN

0.2652

0.1292

2.05

1.3036 (1.0217–1.7057)

0.0402

Macruz index

3.0528

0.8068

3.78

21.1746 (5.0328–120.9576)

0.0002

Back to article page

Perioperative Medicine

ISSN: 2047-0525