One-year prediction of cognitive decline following cognitive-stimulation from real-world data

Clinical evidence based on real-world data (RWD) is accumulating exponentially providing larger sample sizes available, which demand novel methods to deal with the enhanced heterogeneity of the data. Here, we used RWD to assess the prediction of cognitive decline in a large heterogeneous sample of participants being enrolled with cognitive stimulation, a phenomenon that is of great interest to clinicians but that is riddled with difficulties and limitations. More precisely, from a multitude of neuropsychological Training Materials (TMs), we asked whether was possible to accurately predict an individual's cognitive decline one year after being tested. In particular, we performed longitudinal modelling of the scores obtained from 215 different tests, grouped into 29 cognitive domains, a total of 124,610 instances from 7902 participants (40% male, 46% female, 14% not indicated), each performing an average of 16 tests. Employing a machine learning approach based on ROC analysis and cross-validation techniques to overcome overfitting, we show that different TMs belonging to several cognitive domains can accurately predict cognitive decline, while other domains perform poorly, suggesting that the ability to predict decline one year later is not specific to any particular domain, but is rather widely distributed across domains. Moreover, when addressing the same problem between individuals with a common diagnosed label, we found that some domains had more accurate classification for conditions such as Parkinson's disease and Down syndrome, whereas they are less accurate for Alzheimer's disease or multiple sclerosis. Future research should combine similar approaches to ours with standard neuropsychological measurements to enhance interpretability and the possibility of generalizing across different cohorts.

Optimization of the lens sizing for the second eye based on the vault obtained in the first eye in bilateral myopic collamer phakic intraocular lens surgery

PURPOSE

To assess vault and the decision-making process involved in selecting the size of the lens for the fellow eye in a series of patients who received bilateral phakic collamer intraocular lens (pIOL) implants with central hole for correction of myopia.

METHODS

The study sample included all patients who underwent bilateral insertion of a different size pIOL from a pool of 269 patients who underwent sequential bilateral insertion of a pIOL from March 2012 to May 2015 in our institution. Procedures were separated in time to assess the value of the vault and select the pIOL size in second eyes. Vault was analysed objectively using optical coherence tomography.

RESULTS

The decision to change the size of the pIOL in the fellow eye was taken in 25 patients. A smaller pIOL was implanted in the second eye in 9 patients, whereas a lens that was 1 size larger was necessary in 16 patients. Implantation of a larger lens led to a mean increase in vault of 251 ± 180 microns; implantation of a smaller size lens led to a mean decrease in vault of 542 ± 187 microns. In 5 patients, the pIOL implanted in first eye was rotated vertically to reduce lens vault. No lenses had to be explanted.

CONCLUSIONS

Vault in fellow eyes can be improved in patients receiving bilateral myopic pIOL implants by modifying the pIOL size based on the vault value obtained in the first eyes.