| Title |
Intraocular lens power calculation following laser refractive surgery
|
|---|---|
| Published in |
Eye and Vision, April 2015
|
| DOI | 10.1186/s40662-015-0017-3 |
| Pubmed ID | |
| Authors |
Christopher Hodge, Colm McAlinden, Michael Lawless, Colin Chan, Gerard Sutton, Aifric Martin |
| Abstract |
Refractive outcomes following cataract surgery in patients that have previously undergone laser refractive surgery have traditionally been underwhelming. This is related to several key issues including the preoperative assessment (keratometry) and intraocular lens power calculations. Peer-reviewed literature is overwhelmed by the influx of methodology to manipulate the corneal or intraocular lens (IOL) powers following refractive surgery. This would suggest that the optimal derivative formula has yet been introduced. This review discusses the problems facing surgeons approaching IOL calculations in these post-refractive laser patients, the existing formulae and programs to address these concerns. Prior published outcomes will be reviewed. |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Postgraduate | 8 | 21% |
| Other | 7 | 18% |
| Student > Ph. D. Student | 4 | 10% |
| Student > Doctoral Student | 2 | 5% |
| Professor > Associate Professor | 2 | 5% |
| Other | 5 | 13% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 21 | 54% |
| Computer Science | 2 | 5% |
| Agricultural and Biological Sciences | 2 | 5% |
| Engineering | 2 | 5% |
| Unknown | 12 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 January 2017.
All research outputs
#7,263,304
of 22,931,367 outputs
Outputs from Eye and Vision
#35
of 239 outputs
Outputs of similar age
#86,416
of 264,061 outputs
Outputs of similar age from Eye and Vision
#3
of 3 outputs
Altmetric has tracked 22,931,367 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 239 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,061 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.