SVM performance not consistent with AUC score

Question

I have a dataset that contains information about patients. It includes several variables and their clinical status (0 if they are healthy, 1 if they are sick). I have tried to implement an SVM model to predict patient status based on these variables.

library(e1071)

Index <- 
  order(Ytrain, decreasing = FALSE)

SVMfit_Var <- 
  svm(Xtrain[Index, ], Ytrain[Index],
      type = "C-classification", gamma = 0.005, probability = TRUE, cost = 0.001, epsilon = 0.1)


preds1 <- 
  predict(SVMfit_Var, Xtest, probability = TRUE)
preds1 <- 
  attr(preds1, "probabilities")[,1]

samples <- !is.na(Ytest)
  pred <- prediction(preds1[samples],Ytest[samples])
  AUC<-performance(pred,"auc")@y.values[[1]]


prediction <- predict(SVMfit_Var, Xtest)
xtab <- table(Ytest, prediction)

To test the performance of the model, I have calculated the ROC AUC, and with the validation set I obtain an AUC = 0.997. But when I view the predictions, all the patients have been assigned as healthy.

AUC = 0.997
> xtab
     prediction
Ytest  0  1
    0 72  0
    1 52  0

Can anyone help me with this problem?