I'm not sure if these considerations would change how aging research looks from an EA perspective. It's one of the many "rounding errors" that could be considered as side effects, besides the main purpose of buying QALYs and freedom. Moreover, all of these additional considerations, both positive and negative, might be made irrelevant by new disrupting tech and societal/political/organisational change. Examples: cognitive enhancements, AI, research funding management.
I'm not sure if there's a definite answer about how much cognitive decline influences this kind of stuff, but I wouldn't be surprised if "being stuck in old ways" or not being able to understand new developments and innovate are symptoms of neurological old age more than accumulated bias.
There are also other factors that are less related to aging (but which could still benefit from rejuvenation) that play into how superstar researchers hinder the careers of younger scientists (see Gavintaylor's comment). These problems, though, don't need people to die in order to be solved. Organisational improvements would be sufficient.
Putting aside the really bad consequences of a world without life extension (people dying all the time, even when they don't want to), how might a world with life-extension technology redefine the meaning of "too long"?
The classic archetype of an "aging star scientist" shows someone getting older and "stuck in their ways", not coming up with brilliant new ideas or collaborating well with younger researchers. But if new technology increases the length of a person's academic career overall, is it not also likely to increase the length of their productive career? To increase their healthspan (intellect included), rather than only their lifespan? Getting more years out of a brilliant mind seems very valuable.
Is intellect healthspan the problem? Would increasing neuroplasticity help?
People develop biases over their lives which will affect their work. You might call some of these biases wisdom or expertise or crystallized intelligence. Researchers develop tools and intuitions that will come to serve them well, so they'll learn to rely on them. And then they start to rely on them too much. Is this a failure of neuroplasticity, or just something that happens when people work in a given field for a long time?
I think a lot of this comes down to social factors rather than star scientist's productivity decreasing with age.
At least in neuroscience, and probably in the life sciences more broadly, PIs who are very influential in a subfield (or who start a new one) tend to be the go to people for a topic and often become the gatekeepers, so work on that topic is generally done in collaboration with them. Junior scientists (even ones trained by that PI) will usually try to establish a unique research focus that avoids conflict with the exisiting star PIs, even if that means they end up working in a less promising area.
I haven't read the linked paper, but I assume that one factor leading to increase in productivity is simply an increase in good people working in a promising research field where the gatekeeper was removed. In principle, this doesn't need the death of a star scientist to achieve.