## [1] "LC_COLLATE=Chinese (Simplified)_China.936;LC_CTYPE=Chinese (Simplified)_China.936;LC_MONETARY=Chinese (Simplified)_China.936;LC_NUMERIC=C;LC_TIME=Chinese (Simplified)_China.936"
fit = survfit(Surv(Survtime, Death)~Arbidol, data=multi_center)
ggsurvplot(fit,linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
fit = survfit(Surv(Survtime, Death)~Kaletra, data=multi_center)
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
fit = survfit(Surv(Survtime, Death)~Oseltamivir, data=multi_center)
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
fit = survfit(Surv(Survtime, Death)~Ganciclovir, data=multi_center)
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
fit = survfit(Surv(Survtime, Death)~Glucocorticoid, data=multi_center)
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
fit = survfit(Surv(Survtime, Death)~Immunoglobin, data=multi_center)
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
fit = survfit(Surv(Survtime, Death)~Albumin, data=multi_center)
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2", risk.table = TRUE,risk.table.height = 0.3)
logistic_fit = glm(Death~Age+SPO2+Arbidol+Kaletra+Oseltamivir+DateofHosp, data=multi_center, family="binomial")
summary(logistic_fit)
##
## Call:
## glm(formula = Death ~ Age + SPO2 + Arbidol + Kaletra + Oseltamivir +
## DateofHosp, family = "binomial", data = multi_center)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2399 -0.5248 -0.3091 -0.1358 2.9398
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 7.597e+02 2.101e+02 3.615 0.000300 ***
## Age 6.226e-02 1.386e-02 4.491 7.09e-06 ***
## SPO2 -1.021e-01 2.071e-02 -4.927 8.37e-07 ***
## Arbidol -1.653e+00 3.575e-01 -4.624 3.77e-06 ***
## Kaletra -7.144e-01 3.481e-01 -2.052 0.040168 *
## Oseltamivir -1.087e+00 5.062e-01 -2.148 0.031738 *
## DateofHosp -4.773e-07 1.331e-07 -3.586 0.000335 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 390.14 on 395 degrees of freedom
## Residual deviance: 254.25 on 389 degrees of freedom
## (2 observations deleted due to missingness)
## AIC: 268.25
##
## Number of Fisher Scoring iterations: 6
coxph_fit = coxph(Surv(Survtime, Death)~ Age + SPO2 + Arbidol + Kaletra+ Oseltamivir+DateofHosp,data = multi_center)
summary(coxph_fit)
## Call:
## coxph(formula = Surv(Survtime, Death) ~ Age + SPO2 + Arbidol +
## Kaletra + Oseltamivir + DateofHosp, data = multi_center)
##
## n= 392, number of events= 77
## (6 observations deleted due to missingness)
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Age 4.283e-02 1.044e+00 1.006e-02 4.256 2.08e-05 ***
## SPO2 -2.666e-02 9.737e-01 6.142e-03 -4.341 1.42e-05 ***
## Arbidol -1.988e+00 1.370e-01 3.011e-01 -6.601 4.08e-11 ***
## Kaletra -4.826e-01 6.172e-01 2.411e-01 -2.002 0.0453 *
## Oseltamivir -7.334e-01 4.803e-01 3.999e-01 -1.834 0.0667 .
## DateofHosp 4.295e-09 1.000e+00 8.166e-08 0.053 0.9581
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Age 1.0438 0.9581 1.02337 1.0646
## SPO2 0.9737 1.0270 0.96204 0.9855
## Arbidol 0.1370 7.2983 0.07594 0.2472
## Kaletra 0.6172 1.6203 0.38476 0.9900
## Oseltamivir 0.4803 2.0822 0.21932 1.0517
## DateofHosp 1.0000 1.0000 1.00000 1.0000
##
## Concordance= 0.826 (se = 0.028 )
## Likelihood ratio test= 119.8 on 6 df, p=<2e-16
## Wald test = 118.9 on 6 df, p=<2e-16
## Score (logrank) test = 162 on 6 df, p=<2e-16