The experience of symptoms, minor to severe, prompts millions of patients to visit their healthcare providers each year. Symptoms not only create distress, but also disrupt social functioning. The management of symptoms and their resulting outcomes often become the responsibility of the patient and his or her family members. Healthcare providers have difficulty developing symptom management strategies that can be applied across acute and home-care settings because few models of symptom management have been tested empirically. To date, the majority of research on symptoms was directed toward studying a single symptom, such as pain or fatigue, or toward evaluating associated symptoms, such as depression and sleep disturbance. While this approach has advanced our understanding of some symptoms, we offer a generic symptom management model to provide direction for selecting clinical interventions, informing research, and bridging an array of symptoms associated with a variety of diseases and conditions. Finally, a broadly-based symptom management model allows the integration of science from other fields.

The findings from this study need to be replicated before definitive clinical practice recommendations can be made. Until that time, clinicians need to assess patients for the occurrence of multiple symptoms that may place them at increased risk for poorer outcomes.

The majority of clinical studies on pain, fatigue, and depression associated with cancer are focused on one symptom. Although this approach has led to some advances in our understanding of a particular symptom, patients rarely present with a single symptom. Therefore, even though research focused on single symptoms needs to continue, it is imperative that symptom management research begins to focus on evaluating multiple symptoms, using cross-sectional and longitudinal study designs. In addition, research needs to focus on evaluating the relationships among multiple symptoms, specific interventions, and patient outcomes. One of the initial challenges in research regarding multiple symptoms is the terminology that should be used to describe the concept (e.g., symptom cluster, symptom constellation). Another significant area related to this aspect of symptom management research is determining the nature of clinically significant clusters of symptoms and their associated prevalence rates. Equally important is the need to determine what types of tools/instruments will provide the most valid and reliable data for the assessment of symptom clusters. Other areas that need to be considered as related to the assessment of symptom clusters include the establishment of cut points for symptom severity that would qualify a symptom for inclusion in a cluster; the focus of the assessment; and the choice of the outcome measures that will be used to judge the effect of a symptom cluster on the patient. In the area of intervention studies for symptom clusters, research will need to build on the limited number of clinical trials with single symptoms. Additional considerations related to research on symptom clusters include the determination of the mechanisms underlying the development of symptom clusters; the timing of the measurements for symptom clusters; and statistical challenges in the evaluation of symptom clusters. Research on symptom clusters in patients with cancer is cutting-edge science and a new frontier in symptom management research, and it needs to be done in tandem with research on single symptoms.

Adult mammalian brains have largely lost neuroregeneration capability except for a few niches. Previous studies have converted glial cells into neurons, but the total number of neurons generated is limited and the therapeutic potential is unclear. Here, we demonstrate that NeuroD1-mediated in situ astrocyte-to-neuron conversion can regenerate a large number of functional new neurons after ischemic injury. Specifically, using NeuroD1 adeno-associated virus (AAV)-based gene therapy, we were able to regenerate one third of the total lost neurons caused by ischemic injury and simultaneously protect another one third of injured neurons, leading to a significant neuronal recovery. RNA sequencing and immunostaining confirmed neuronal recovery after cell conversion at both the mRNA level and protein level. Brain slice recordings found that the astrocyte-converted neurons showed robust action potentials and synaptic responses at 2 months after NeuroD1 expression. Anterograde and retrograde tracing revealed long-range axonal projections from astrocyte-converted neurons to their target regions in a time-dependent manner. Behavioral analyses showed a significant improvement of both motor and cognitive functions after cell conversion. Together, these results demonstrate that in vivo cell conversion technology through NeuroD1-based gene therapy can regenerate a large number of functional new neurons to restore lost neuronal functions after injury.

A high percentage of FCs experienced clinically meaningful levels of a variety of symptoms. These symptoms have a negative impact on the FCs' functional status and QOL.

Background-Fatigue is a significant problem associated with radiation therapy (RT).

SummaryBackgroundSurgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world.MethodsThis international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231.FindingsBetween Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p<0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p<0·001).InterpretationCountries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication.FundingDFID-MRC-Wellcome Trust Joint Global Health Trial Development Grant,...

Fatigue is the most common and distressing symptom reported by patients undergoing radiation therapy (RT). However, limited information is available on the trajectories of fatigue, as well as on the predictors of interindividual variability in fatigue. This study evaluated a sample of patients who underwent RT for prostate cancer to examine how ratings of evening and morning fatigue changed from the time of simulation to four months after the completion of RT and to investigate whether specific patient, disease, and symptom characteristics predicted the initial levels of fatigue and/or characteristics of the trajectories of evening and morning fatigue. Using hierarchical linear modeling, a large amount of interindividual variability was demonstrated in the trajectories of evening and morning fatigue. Findings from this study suggest that younger men with a higher level of fatigue at the time of the simulation visit were at increased risk for higher levels of evening and morning fatigue over the course of RT. In addition, the level of morning fatigue over the course of RT appears to depend on the patient's level of depression at the time of the simulation visit. In future studies, the use of hierarchical linear modeling as an analytic tool will assist in the identification of patients who are most at risk for prolonged fatigue trajectories. This type of analysis may lead to the identification of subgroups of patients who are at higher risk for negative outcomes and who require different types of interventions for the fatigue associated with RT.