diff --git a/README.md b/README.md
index d7a3161..77b909f 100755
--- a/README.md
+++ b/README.md
@@ -553,7 +553,7 @@ To create an index, use `datastore.ensureIndex(options, cb)`, where callback is
 * **fieldName** (required): name of the field to index. Use the dot notation to index a field in a nested document.
 * **unique** (optional, defaults to `false`): enforce field uniqueness. Note that a unique index will raise an error if you try to index two documents for which the field is not defined.
 * **sparse** (optional, defaults to `false`): don't index documents for which the field is not defined. Use this option along with "unique" if you want to accept multiple documents for which it is not defined.
-* **expireAfterSeconds** (number of seconds, optional): if set, the created index is a TTL (time to live) index, that will automatically remove documents when the system date becomes larger than the date on the indexed field plus `expireAfterSeconds`
+* **expireAfterSeconds** (number of seconds, optional): if set, the created index is a TTL (time to live) index, that will automatically remove documents when the system date becomes larger than the date on the indexed field plus `expireAfterSeconds`. Documents where the indexed field is not specified or not a `Date` object are ignored
 
 Note: the `_id` is automatically indexed with a unique constraint, no need to call `ensureIndex` on it.
 
@@ -593,6 +593,13 @@ db.removeIndex('somefield', function (err) {
 // after their creation (db's timestampData option is true here)
 db.ensureIndex({ fieldName: 'createdAt', expireAfterSeconds: 3600 }, function (err) {
 });
+
+// You can also use the option to set an expiration date like so
+db.ensureIndex({ fieldName: 'expirationDate', expireAfterSeconds: 0 }, function (err) {
+  // Now all documents will expire when system time reaches the date in their
+  // expirationDate field
+});
+
 ```
 
 **Note:** the `ensureIndex` function creates the index synchronously, so it's best to use it at application startup. It's quite fast so it doesn't increase startup time much (35 ms for a collection containing 10,000 documents).