The Effect of Cluster Size Variability on Statistical Power in Cluster-Randomized Trials

The frequency of cluster-randomized trials (CRTs) in peer-reviewed literature has increased exponentially over the past two decades. CRTs are a valuable tool for studying interventions that cannot be effectively implemented or randomized at the individual level. However, some aspects of the design and analysis of data from CRTs are more complex than those for individually randomized controlled trials. One of the key components to designing a successful CRT is calculating the proper sample size (i.e. number of clusters) needed to attain an acceptable level of statistical power. In order to do this, a researcher must make assumptions about the value of several variables, including a fixed mean cluster size. In practice, cluster size can often vary dramatically. Few studies account for the effect of cluster size variation when assessing the statistical power for a given trial. We conducted a simulation study to investigate how the statistical power of CRTs changes with variable cluster sizes. In general, we observed that increases in cluster size variability lead to a decrease in power

Galactic emission at 19 GHz

We cross-correlate a 19 GHz full sky Cosmic Microwave Background (CMB) survey with other maps to quantify the foreground contribution. Correlations are detected with the Diffuse Infrared Background Experiment (DIRBE) 240, 140 and 100 micron maps at high latitudes (|b|>30degrees), and marginal correlations are detected with the Haslam 408 MHz and the Reich & Reich 1420 MHz synchrotron maps. The former agree well with extrapolations from higher frequencies probed by the COBE DMR and Saskatoon experiments and are consistent with both free-free and rotating dust grain emission.Comment: 4 pages, with 4 figures included. Accepted for publication in ApJL. Color figure and links at http://www.sns.ias.edu/~angelica/foreground.html#19 or from [email protected]

The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

Background: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. Objective: To estimate the length of the incubation period of COVID-19 and describe its public health implications. Design: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. Setting: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. Participants: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. Measurements: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. Results: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. Limitation: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. Conclusion: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases

Criteria for the diagnosis of corticobasal degeneration

Current criteria for the clinical diagnosis of pathologically confirmed corticobasal degeneration (CBD) no longer reflect the expanding understanding of this disease and its clinicopathologic correlations. An international consortium of behavioral neurology, neuropsychology, and movement disorders specialists developed new criteria based on consensus and a systematic literature review. Clinical diagnoses (early or late) were identified for 267 nonoverlapping pathologically confirmed CBD cases from published reports and brain banks. Combined with consensus, 4 CBD phenotypes emerged: corticobasal syndrome (CBS), frontal behavioral-spatial syndrome (FBS), nonfluent/agrammatic variant of primary progressive aphasia (naPPA), and progressive supranuclear palsy syndrome (PSPS). Clinical features of CBD cases were extracted from descriptions of 209 brain bank and published patients, providing a comprehensive description of CBD and correcting common misconceptions. Clinical CBD phenotypes and features were combined to create 2 sets of criteria: more specific clinical research criteria for probable CBD and broader criteria for possible CBD that are more inclusive but have a higher chance to detect other tau-based pathologies. Probable CBD criteria require insidious onset and gradual progression for at least 1 year, age at onset ≥50 years, no similar family history or known tau mutations, and a clinical phenotype of probable CBS or either FBS or naPPA with at least 1 CBS feature. The possible CBD category uses similar criteria but has no restrictions on age or family history, allows tau mutations, permits less rigorous phenotype fulfillment, and includes a PSPS phenotype. Future validation and refinement of the proposed criteria are needed

Traumatic Brain Injury and Firearm Use and Risk of Progressive Supranuclear Palsy Among Veterans

Background: Progressive supranuclear palsy (PSP) is a tauopathy that has a multifactorial etiology. Numerous studies that have investigated lead exposure and traumatic brain injury (TBI) as risk factors for other tauopathies, such as Alzheimer's disease, but not for PSP.Objective: We sought to investigate the role of firearm usage, as a possible indicator of lead exposure, and TBI as risk factors for PSP in a population of military veterans.Methods: We included participants from a larger case-control study who reported previous military service. Our sample included 67 PSP cases and 68 controls. Participants were administered a questionnaire to characterize firearm use in the military and occurrence of TBI.Results: Cases were significantly less educated than controls. In unadjusted analyses, the proportion of PSP cases (80.6%) and controls (64.7%) who reported use of firearms as part of their military job was positively associated with PSP, odds ratio (OR) 2.2 (95% CI: 1–5.0). There were no significant case-control differences in mean service duration. There was only a weak association with history of TBI, OR 1.6 (95% CI: 0.8–3.4). In multivariate models, firearm usage (OR 3.7, 95% CI: 1.5, 9.8) remained significantly associated with PSP.Conclusions: Our findings show a positive association between firearm usage and PSP and an inverse association between education and PSP. The former suggests a possible etiologic role of lead. Further studies are needed to confirm the potential etiologic effects of metals on PSP.The study was registered in clinicaltrials.gov. ClinicalTrials.gov Identifier: NCT00431301

G2019S mutation in the leucine-rich repeat kinase 2 gene is not associated with multiple system atrophy

Multiple system atrophy (MSA) is characterized clinically by Parkinsonism, cerebellar dysfunction, and autonomic impairment. Multiple mutations in the LRRK2 gene are associated with parkinsonian disorders, and the most common one, the G2019S mutation, has been found in ∼1% of sporadic cases of Parkinsonism. In a well-characterized cohort of 136 subjects with probable MSA and 110 neurologically evaluated control subjects, none carried the G2019S mutation. We conclude that the G2019S mutation in the LRRK2 gene is unlikely to be associated with MSA. © 2007 Movement Disorder SocietyPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56014/1/21343_ftp.pd

Leveraging population admixture to characterize the heritability of complex traits.

Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2)