The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25–50%) than euchromatic reference regions (3–11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11–27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4–3.6 vs. 8.4–8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu.

The purpose of our scoping review was to describe the current use of mHealth technology for long-term assessment of patient-reported outcomes in community-dwelling individuals with acquired brain injury (ABI). Following PRISMA guidelines, we conducted a scoping review of literature meeting these criteria: (1) civilians or military veterans, all ages; (2) self-reported or caregiver-reported outcomes assessed via mobile device in the community (not exclusively clinic/hospital); (3) published in English; (4) published in 2015–2019. We searched Ovid MEDLINE(R) < 1946 to 16 August 2019, MEDLINE InProcess, EPub, Embase, and PsycINFO databases for articles. Thirteen manuscripts representing 12 distinct studies were organized by type of ABI [traumatic brain injury (TBI) and stroke] to extract outcomes, mHealth technology used, design, and inclusion of ecological momentary assessment (EMA). Outcomes included post-concussive, depressive, and affective symptoms, fatigue, daily activities, stroke risk factors, and cognitive exertion. Overall, collecting patient-reported outcomes via mHealth was feasible and acceptable in the chronic ABI population. Studies consistently showed advantage for using EMA despite variability in EMA timing/schedules. To ensure best clinical measurement, research on post-ABI outcomes should consider EMA designs (versus single time-point assessments) that provide the best timing schedules for their respective aims and outcomes and that leverage mHealth for data collection.

This study aimed to empirically evaluate the hierarchical structure of the Coma Recovery Scale-Revised (CRS-R) rating scale categories and their alignment with the Aspen consensus criteria for determining disorders of consciousness (DoC) following a severe brain injury. CRS-R data from 262 patients with DoC following a severe brain injury were analyzed applying the partial credit Rasch Measurement Model. Rasch Analysis produced logit calibrations for each rating scale category. Twenty-eight of the 29 CRS-R rating scale categories were operationalized to the Aspen consensus criteria. We expected the hierarchical order of the calibrations to reflect Aspen consensus criteria. We also examined the association between the CRS-R Rasch person measures (indicative of performance ability) and states of consciousness as determined by the Aspen consensus criteria. Overall, the order of the 29 rating scale category calibrations reflected current literature regarding the continuum of neurobehavioral function: category 6 “Functional Object Use” of the Motor item was hardest for patients to achieve; category 0 “None” of the Oromotor/Verbal item was easiest to achieve. Of the 29 rating scale categories, six were not ordered as expected. Four rating scale categories reflecting the Vegetative State (VS)/Unresponsive Wakefulness Syndrome (UWS) had higher calibrations (reflecting greater neurobehavioral function) than the easiest Minimally Conscious State (MCS) item (category 2 “Fixation” of the Visual item). Two rating scale categories, one reflecting MCS and one not operationalized to the Aspen consensus criteria, had higher calibrations than the easiest eMCS item (category 2 “Functional: Accurate” of the Communication item). CRS-R person measures (indicating amount of neurobehavioral function) and states of consciousness, based on Aspen consensus criteria, showed a strong correlation (r _s = 0.86; p < 0.01). Our study provides empirical evidence for revising the diagnostic criteria for MCS to also include category 2 “Localization to Sound” of the Auditory item and for Emerged from Minimally Conscious State (eMCS) to include category 4 “Consistent Movement to Command” of the Auditory item.

Medicare payment models for postacute care (PAC) services are shifting from a model based on volume of services provided, such as amount of therapy (occupational, physical, and speech/language) or length of stay (LOS), to one of value based on patients’ clinical characteristics. Historically, the amount of therapy provided in PAC facilities has been driven by reimbursement requirements rather than patient need as determined by clinical teams. This change from volume to value is intended to encourage health care professionals to optimize functional gains for patients while minimizing costs and lessen the financial incentives to provide more therapy than necessary.¹ Under a value-based system, rehabilitation teams will need to make evidence-informed decisions about the amount of therapy per day and LOS to maximize patients’ functional improvement.

The purpose of this study was to differentiate clinically meaningful improvement or deterioration from normal fluctuations in patients with disorders of consciousness (DoC) following severe brain injury. We computed indices of responsiveness for the Coma Recovery Scale-Revised (CRS-R) using data from a clinical trial of 180 participants with DoC. We used CRS-R scores from baseline (enrollment in a clinical trial) and a 4-week follow-up assessment period for these calculations. To improve precision, we transformed ordinal CRS-R total scores (0–23 points) to equal-interval measures on a 0–100 unit scale using Rasch Measurement theory. Using the 0–100 unit total Rasch measures, we calculated distribution-based 0.5 standard deviation (SD) minimal clinically important difference, minimal detectable change using 95% confidence intervals, and conditional minimal detectable change using 95% confidence intervals. The distribution-based minimal clinically important difference evaluates group-level changes, whereas the minimal detectable change values evaluate individual-level changes. The minimal clinically important difference and minimal detectable change are derived using the overall variability across total measures at baseline and 4 weeks. The conditional minimal detectable change is generated for each possible pair of CRS-R Rasch person measures and accounts for variation in standard error across the scale. We applied these indices to determine the proportions of participants who made a change beyond measurement error within each of the two subgroups, based on treatment arm (amantadine hydrochloride or placebo) or categorization of baseline Rasch person measure to states of consciousness (i.e., unresponsive wakefulness syndrome and minimally conscious state). We compared the proportion of participants in each treatment arm who made a change according to the minimal detectable change and determined whether they also changed to another state of consciousness. CRS-R indices of responsiveness (using the 0–100 transformed scale) were as follows: 0.5SD minimal clinically important difference = 9 units, minimal detectable change = 11 units, and the conditional minimal detectable change ranged from 11 to 42 units. For the amantadine and placebo groups, 70% and 58% of participants showed change beyond measurement error using the minimal detectable change, respectively. For the unresponsive wakefulness syndrome and minimally conscious state groups, 54% and 69% of participants changed beyond measurement error using the minimal detectable change, respectively. Among 115 participants (64% of the total sample) who made a change beyond measurement error, 29 participants (25%) did not change state of consciousness. CRS-R indices of responsiveness can support clinicians and researchers in discerning when behavioral changes in patients with DoC exceed measurement error. Notably, the minimal detectable change can support the detection of patients who make a “true” change within or across states of consciousness. Our findings highlight that the continued use of ordinal scores may result in incorrect inferences about the degree and relevance of a change score.

The purpose of this study is to describe the clinical lifeworld of rehabilitation practitioners who work with patients in disordered states of consciousness (DoC) after severe traumatic brain injury (TBI). We interviewed 21 practitioners using narrative interviewing methods from two specialty health systems that admit patients in DoC to inpatient rehabilitation. The overarching theme arising from the interview data is “Experiencing ambiguity and uncertainty in clinical reasoning about consciousness” when treating persons in DoC. We describe practitioners’ practices of looking for consistency, making sense of ambiguous and hard to explain patient responses, and using trial and error or “tinkering” to care for patients. Due to scientific uncertainty about diagnosis and prognosis in DoC and ambiguity about interpretation of patient responses, working in the field of DoC disrupts the canonical meaning-making processes that practitioners have been trained in. Studying the lifeworld of rehabilitation practitioners through their story-making and story-telling uncovers taken-for-granted assumptions and normative structures that may exist in rehabilitation medical and scientific culture, including practitioner training. We are interested in understanding these canonical breaches in order to make visible how practitioners make meaning while treating patients.