Table 3:

Results of the multivariable logistic regression analysis displaying the best parsimonious model (dependent variable: 30-day mortality)

CovariateCoefficient estimateOdds ratio95% CIP-value
(Intercept)−6.3500.0020.001–0.003<0.001
Age0.0471.0481.042–1.054<0.001
Male gender0.8892.4332.133–2.774<0.001
BMI−0.0550.9470.935–0.958<0.001
ppoFEV 1−0.0100.9900.988–0.992<0.001
Thoracotomy0.8922.4412.086–2.854<0.001
Pneumonectomy0.9832.6722.371–3.012<0.001
CovariateCoefficient estimateOdds ratio95% CIP-value
(Intercept)−6.3500.0020.001–0.003<0.001
Age0.0471.0481.042–1.054<0.001
Male gender0.8892.4332.133–2.774<0.001
BMI−0.0550.9470.935–0.958<0.001
ppoFEV 1−0.0100.9900.988–0.992<0.001
Thoracotomy0.8922.4412.086–2.854<0.001
Pneumonectomy0.9832.6722.371–3.012<0.001

BMI: body mass index; CI: confidence interval; ppoFEV1: predicted postoperative forced expiratory volume in 1 s.

Table 3:

Results of the multivariable logistic regression analysis displaying the best parsimonious model (dependent variable: 30-day mortality)

CovariateCoefficient estimateOdds ratio95% CIP-value
(Intercept)−6.3500.0020.001–0.003<0.001
Age0.0471.0481.042–1.054<0.001
Male gender0.8892.4332.133–2.774<0.001
BMI−0.0550.9470.935–0.958<0.001
ppoFEV 1−0.0100.9900.988–0.992<0.001
Thoracotomy0.8922.4412.086–2.854<0.001
Pneumonectomy0.9832.6722.371–3.012<0.001
CovariateCoefficient estimateOdds ratio95% CIP-value
(Intercept)−6.3500.0020.001–0.003<0.001
Age0.0471.0481.042–1.054<0.001
Male gender0.8892.4332.133–2.774<0.001
BMI−0.0550.9470.935–0.958<0.001
ppoFEV 1−0.0100.9900.988–0.992<0.001
Thoracotomy0.8922.4412.086–2.854<0.001
Pneumonectomy0.9832.6722.371–3.012<0.001

BMI: body mass index; CI: confidence interval; ppoFEV1: predicted postoperative forced expiratory volume in 1 s.

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