i suggest you contact the author to know the reasons for dropout , you ask him how he managed the dropped out patients. if no response of the author for binary outcomes you can assume a best and a worst case scenario and then do a senstivity analysis to see the effect of data estimation ,, enjoy yassin :D  

Drop-outs in clinical trials assume importance if they are due to lack of efficacy and/or adverse events. The general principle is that each and every patient included in a clinical trial should be accounted for. In the case referred to, it is mentioned that No. of participants randomized. Does it mean all were treated?

Intention to treat  (ITT) analysis may be used if the dataset includes some patients for whom there are incomplete data. ITT analysis allows inclusion of such patients provided they have received at least one dose of the drug and there is at least one post-treatment observation/value which can be carried forward.

I'm not keen on last observation carried forward. There are quite a few situations when it's entirely inappropriate, e.g. if you expect the outcome to change over time. If you can't get the outcomes on everyone because some are lost to follow-up, then that's a weakness of the study. It doesn't, in my view, mean that you can make up some of that data based on some very strong assumptions. Sensitivity analysis may be one way forward, but if the trial had dropouts, it had dropouts, and the meta-analysis is only as good as the studies included within it. That's one reason for assessing risk of bias. I'd be happy for a trials statistician to bring some more up-to-date advice on this.