- Previously thought to be Pneumocystis carinii (species that infects rats) it is now known that the human pathogen is Pneumocystis jirovecii
- Still referred to as PCP (PneumoCystis Pneumonia)
- Fungus based on genotypic homologies
- Incidence has greatly decreased since the use of ART and prophylaxis however still one of the leading OI in HIV pts
- Rare cause in HIV when CD4 >200 and when bactrim ppx is taken appropriately
- Clinical sx: Gradual onset of fever (80-100%), cough (90%) and dyspnea (95%)
- Diagnosis: Low CD4 (95% of cases below 200), elevated LDH in 90% of patients, often hypoxic as dz progresses, CXR normal in ¼ patients or may show diffuse, bilateral, interstitial or alveolar infiltrates
- Treatment: TMP-SMX preferred medication, if unable to take TMP-SMX then mild/mod can be tx with atovaquone or clinda/primaquine however if severe, tx with IV pentamadine
- Steroids are recommended for PaO2 <70, AA gradient >35 or hypoxemia on pulse ox
In the last several years, we have seen the rise of computer based cognitive training modules, colloquially referred to as “brain training.” Touted as “cognitive neuroscience-based therapy,” these services aim to increase attention, memory, social skills, reasoning ability and academic skills. Questions remain, however, regarding their effectiveness. Multiple studies are often cited by the companies behind the brain training products, claiming increased cognitive abilities in as little as 4 weeks. However, a recent statement released by the Stanford University Center on Longevity and the Berlin Max Planck Institute for Human Development suggests that there is no solid scientific evidence to support these claims. Signed by leading cognitive psychologists and neuroscientists, the statement notes:
“The strong consensus of this group is that the scientific literature does not support claims that the use of software-based ‘brain games’ alters neural functioning in ways that improve general cognitive performance in everyday life, or prevent cognitive slowing and brain disease […] The promise of a magic bullet detracts from the best evidence to date, which is that cognitive health in old age reflects the long-term effects of healthy, engaged lifestyles.”
In a recent systematic review and meta-analysis, the researchers assess whether CCT programs improve cognitive test performance in cognitively healthy older adults and identify the aspects of cognition (cognitive domains) that are responsive to CCT, and the CCT design features that are most important in improving cognitive performance.
New effective interventions to attenuate age-related cognitive decline are a global priority. Computerized cognitive training (CCT) is believed to be safe and can be inexpensive, but neither its efficacy in enhancing cognitive performance in healthy older adults nor the impact of design factors on such efficacy has been systematically analyzed. Our aim therefore was to quantitatively assess whether CCT programs can enhance cognition in healthy older adults, discriminate responsive from nonresponsive cognitive domains, and identify the most salient design factors.
Methods and Findings
We systematically searched Medline, Embase, and PsycINFO for relevant studies from the databases’ inception to 9 July 2014. Eligible studies were randomized controlled trials investigating the effects of ≥4 h of CCT on performance in neuropsychological tests in older adults without dementia or other cognitive impairment. Fifty-two studies encompassing 4,885 participants were eligible. Intervention designs varied considerably, but after removal of one outlier, heterogeneity across studies was small (I2 = 29.92%). There was no systematic evidence of publication bias. The overall effect size (Hedges’ g, random effects model) for CCT versus control was small and statistically significant, g = 0.22 (95% CI 0.15 to 0.29). Small to moderate effect sizes were found for nonverbal memory, g = 0.24 (95% CI 0.09 to 0.38); verbal memory, g = 0.08 (95% CI 0.01 to 0.15); working memory (WM), g = 0.22 (95% CI 0.09 to 0.35); processing speed, g = 0.31 (95% CI 0.11 to 0.50); and visuospatial skills, g = 0.30 (95% CI 0.07 to 0.54). No significant effects were found for executive functions and attention. Moderator analyses revealed that home-based administration was ineffective compared to group-based training, and that more than three training sessions per week was ineffective versus three or fewer. There was no evidence for the effectiveness of WM training, and only weak evidence for sessions less than 30 min. These results are limited to healthy older adults, and do not address the durability of training effects.
CCT is modestly effective at improving cognitive performance in healthy older adults, but efficacy varies across cognitive domains and is largely determined by design choices. Unsupervised at-home training and training more than three times per week are specifically ineffective. Further research is required to enhance efficacy of the intervention. These findings suggest that CCT produces small improvements in cognitive performance in cognitively healthy older adults but that the efficacy of CCT varies across cognitive domains and is largely determined by design aspects of CCT. The most important result was that “do-it-yourself” CCT at home did not produce improvements. Rather, the small improvements seen were in individuals supervised by a trainer in a center and undergoing sessions 1–3 times a week. Because only cognitively healthy older adults were enrolled in the studies considered in this systematic review and meta-analysis, these findings do not necessarily apply to cognitively impaired individuals. Moreover, because all the included studies measured cognitive function immediately after CCT, these findings provide no information about the durability of the effects of CCT or about how the effects of CCT on cognitive function translate into real-life outcomes for individuals such as independence and the long-term risk of dementia.
Lampit A, Hallock H, Valenzuela M (2014) Computerized Cognitive Training in Cognitively Healthy Older Adults: A Systematic Review and Meta-Analysis of Effect Modifiers. PLoS Med 11(11): e1001756. doi:10.1371/journal.pmed.1001756
In case you missed the email, here is the December, 2014 edition of the Internal Medicine Journal Watch, curated by the IMJW editorial board (Jan Petrasek, Nico Barros, Ragisha Gopalakrishnan, Jeremy Warshauer, Shetal Patel, Ben Jenny, Vishy Lanka, Brian Davis, Ashish Gupta, and Roma Mehta). Thank you to the board for putting together this collection of important publications in science and medicine! UTSW_IMJW_12_2014