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Psychotic experiences are reported by 5–10% of young people, although only a minority persist and develop into psychotic disorders. It is unclear what characteristics differentiate those with transient psychotic experiences from those with persistent psychotic experiences that are more likely to be of clinical relevance.
To investigate how longitudinal profiles of psychotic experiences, created from assessments at three different time points, are influenced by early life and co-occurring factors.
Using data from 8045 individuals from a birth cohort study, longitudinal profiles of psychotic experiences based on semi-structured interviews conducted at 12, 18 and 24 years were defined. Environmental, cognitive, psychopathological and genetic determinants of these profiles were investigated, along with concurrent changes in psychopathology and cognition.
Following multiple imputations, the distribution of longitudinal profiles of psychotic experiences was none (65.7%), transient (24.1%), low-frequency persistent (8.4%) and high-frequency persistent (1.7%). Individuals with high-frequency persistent psychotic experiences were more likely to report traumatic experiences, other psychopathology, a more externalised locus of control, reduced emotional stability and conscientious personality traits in childhood, compared with those with transient psychotic experiences. These characteristics also differed between those who had any psychotic experiences and those who did not.
These findings indicate that the same risk factors are associated with incidence as with persistence of psychotic experiences. Thus, it might be that the severity of exposure, rather than the presence of specific disease-modifying factors, is most likely to determine whether psychotic experiences are transient or persist, and potentially develop into a clinical disorder over time.
The aim of this quality improvement project is to improve identification and management of mood disorder in patients over 65 years admitted to Royal Surrey County Hospital (RSCH) with hip fractures by introducing a standardised assessment tool to guide appropriate interventions.
The signs of depression in the elderly can be subtle and often go unnoticed. The multidisciplinary team (MDT) at RSCH observed that low mood could negatively impact on a patient's recovery, affecting pain thresholds and leading to poor engagement with rehabilitation. Proactive identification and management of mood disorder is an important part of Comprehensive Geriatric Assessment but not routinely performed in patients with hip fracture admitted to RSCH.
Notes and discharge summaries of patients with hip fracture admitted over a four-month period were retrospectively reviewed to establish if patients were screened for low mood. A mood screening tool was chosen and implemented prospectively over a four-month period. Occupational therapists and junior doctors completed a Cornell Score for all patinets. Those identified with depression or probable depression were issued verbal advice, an information leaflet and follow-up arranged.
Ninety-eight patients were included in the retrospective cohort. No patients were formally identified as having depression or probable depression, and there was no indication that mood was considered or assessed at any point during admission. During the four-month prospective period, 90 patients were admitted to RSCH with hip fracture and 86 patients (96%) were screened for low mood. Four patients were excluded due to a terminal prognosis. Of the patients screened, 9% had major depression and 16% probable depression. Feedback from our occupational therapists and doctors was positive, with the tool being relatively easy to use in patients with or without cognitive impairment. Much of the assessment could be incorporated into their initial assessment or in gaining collateral history from next of kin. Anecdotally, considering patients psychological well-being had a positive impact on inpatient therapy sessions guided the MDT in supporting the patient appropriately.
Implementation of a standardised and validated mood screening tool enabled us to identify that a quarter (25%) of the patients admitted following a hip fracture had, or probably had depression. This allowed us to intervene with simple measures such as verbal advice and an information leaflet and consider pharmacological intervention where appropriate.
Healthcare personnel with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection were interviewed to describe activities and practices in and outside the workplace. Among 2,625 healthcare personnel, workplace-related factors that may increase infection risk were more common among nursing-home personnel than hospital personnel, whereas selected factors outside the workplace were more common among hospital personnel.
Salt marshes are valuable but complex biophysical systems with associated ecosystems. This presents numerous challenges when trying to understand and predict their behaviour and evolution, which is essential to facilitate their continued and sustainable use, conservation and management1. Detailed understanding of the hydrodynamics, sediment dynamics, and ecology that control the system is required, as well as their numerous interactions2,3, but is complicated by spatial and temporal heterogeneity at a range of scales4,5. These complex interactions and feedbacks between the physical, biological, and chemical processes can be investigated in situ following natural, unintentional, or intentional manipulation6, but the mechanistic basis of any observations are confounded by the presence of collinear variables. Hence, laboratory investigations can be beneficial, as they provide the opportunity for systematic testing of subsets of coastal processes, mechanisms, or conditions typical of salt marsh systems, in the absence of confounding variables. With appropriate scaling, this allows a better understanding of the overall function of the salt marsh, and better predictions of their evolution.
Rock debris covers ~30% of glacier ablation areas in the Central Himalaya and modifies the impact of atmospheric conditions on mass balance. The thermal properties of supraglacial debris are diurnally variable but remain poorly constrained for monsoon-influenced glaciers over the timescale of the ablation season. We measured vertical debris profile temperatures at 12 sites on four glaciers in the Everest region with debris thickness ranging from 0.08 to 2.8 m. Typically, the length of the ice ablation season beneath supraglacial debris was 160 days (15 May to 22 October)—a month longer than the monsoon season. Debris temperature gradients were approximately linear (r2 > 0.83), measured as −40°C m–1 where debris was up to 0.1 m thick, −20°C m–1 for debris 0.1–0.5 m thick, and −4°C m–1 for debris greater than 0.5 m thick. Our results demonstrate that the influence of supraglacial debris on the temperature of the underlying ice surface, and therefore melt, is stable at a seasonal timescale and can be estimated from near-surface temperature. These results have the potential to greatly improve the representation of ablation in calculations of debris-covered glacier mass balance and projections of their response to climate change.
Background: Pneumonia (PNA) is an important cause of morbidity and mortality among nursing home residents. The McGeer surveillance definitions were revised in 2012 to help NHs better monitor infections for quality improvement purposes. However, the concordance between surveillance definitions and clinically diagnosed PNA has not been well studied. Our objectives were to identify nursing home residents who met the revised McGeer PNA definition, to compare them with residents with clinician documented PNA, and determine whether modifications to the surveillance criteria could increase concordance. Methods: We analyzed respiratory tract infection (RTI) data from 161 nursing homes in 10 states that participated in a 1-day healthcare-associated infection point-prevalence survey in 2017. Trained surveillance officers from the CDC Emerging Infections Program collected data on residents with clinician documentation, signs, symptoms, and diagnostic testing potentially indicating an RTI. Clinician-documented pneumonia was defined as any resident with a diagnosis of pneumonia identified in the medical chart. We identified the proportion of residents with clinician documented PNA who met the revised McGeer PNA definition. We evaluated the criteria reported to develop 3 modified PNA surveillance definitions (Box), and we compared them to residents with clinician documented PNA.
Results: Among the 15,296 NH residents surveyed, 353 (2%) had >1 signs and/or symptoms potentially indicating RTI. Among the 353 residents, the average age was 76 years, 105 (30%) were admitted to postacute care or rehabilitation, and 108 (31%) had clinician-documented PNA. Among those with PNA, 28 (26%) met the Revised McGeer definition. Among 81 residents who did not meet the definition, 39 (48%) were missing the chest x-ray requirement, and among the remaining 42, only 3 (7%) met the constitutional criteria requirement (Fig. 1). Modification of the constitutional criteria requirement increased the detection of clinically documented PNA from 28 (26%) to 36 (33%) using modified definition 1; to 51 (47%) for modified definition 2; and to 55 (51%) for modified definition 3. Conclusions: Tracking PNA among nursing home residents using a standard definition is essential to improving detection and, therefore, informing prevention efforts. Modifying the PNA criteria increased the identification of clinically diagnosed PNA. Better concordance with clinically diagnosed PNA may improve provider acceptance and adoption of the surveillance definition, but additional research is needed to test its validity.
Background: With the emergence of antibiotic resistant threats and the need for appropriate antibiotic use, laboratory microbiology information is important to guide clinical decision making in nursing homes, where access to such data can be limited. Susceptibility data are necessary to inform antibiotic selection and to monitor changes in resistance patterns over time. To contribute to existing data that describe antibiotic resistance among nursing home residents, we summarized antibiotic susceptibility data from organisms commonly isolated from urine cultures collected as part of the CDC multistate, Emerging Infections Program (EIP) nursing home prevalence survey. Methods: In 2017, urine culture and antibiotic susceptibility data for selected organisms were retrospectively collected from nursing home residents’ medical records by trained EIP staff. Urine culture results reported as negative (no growth) or contaminated were excluded. Susceptibility results were recorded as susceptible, non-susceptible (resistant or intermediate), or not tested. The pooled mean percentage tested and percentage non-susceptible were calculated for selected antibiotic agents and classes using available data. Susceptibility data were analyzed for organisms with ≥20 isolates. The definition for multidrug-resistance (MDR) was based on the CDC and European Centre for Disease Prevention and Control’s interim standard definitions. Data were analyzed using SAS v 9.4 software. Results: Among 161 participating nursing homes and 15,276 residents, 300 residents (2.0%) had documentation of a urine culture at the time of the survey, and 229 (76.3%) were positive. Escherichia coli, Proteus mirabilis, Klebsiella spp, and Enterococcus spp represented 73.0% of all urine isolates (N = 278). There were 215 (77.3%) isolates with reported susceptibility data (Fig. 1). Of these, data were analyzed for 187 (87.0%) (Fig. 2). All isolates tested for carbapenems were susceptible. Fluoroquinolone non-susceptibility was most prevalent among E. coli (42.9%) and P. mirabilis (55.9%). Among Klebsiella spp, the highest percentages of non-susceptibility were observed for extended-spectrum cephalosporins and folate pathway inhibitors (25.0% each). Glycopeptide non-susceptibility was 10.0% for Enterococcus spp. The percentage of isolates classified as MDR ranged from 10.1% for E. coli to 14.7% for P. mirabilis. Conclusions: Substantial levels of non-susceptibility were observed for nursing home residents’ urine isolates, with 10% to 56% reported as non-susceptible to the antibiotics assessed. Non-susceptibility was highest for fluoroquinolones, an antibiotic class commonly used in nursing homes, and ≥ 10% of selected isolates were MDR. Our findings reinforce the importance of nursing homes using susceptibility data from laboratory service providers to guide antibiotic prescribing and to monitor levels of resistance.
Background: With an aging population, increasingly complex care, and frequent re-admissions, prevention of healthcare-associated infections (HAIs) in nursing homes (NHs) is a federal priority. However, few contemporary sources of HAI data exist to inform surveillance, prevention, and policy. Prevalence surveys (PSs) are an efficient approach to generating data to measure the burden and describe the types of HAI. In 2017, the Centers for Disease Control and Prevention (CDC) performed its first large-scale HAI PS through the Emerging Infections Program (EIP) to measure the prevalence and describe the epidemiology of HAI in NH residents. Methods: NHs from several states (CA, CO, CT, GA, MD, MN, NM, NY, OR, & TN) were randomly selected and asked to participate in a 1-day HAI PS between April and October 2017; participation was voluntary. EIP staff reviewed available medical records for NH residents present on the survey date to collect demographic and basic clinical information and infection signs and symptoms. HAIs with onset on or after NH day 3 were identified using revised McGeer infection definitions applied to data collected by EIP staff and were reported to the CDC through a web-based system. Data were reviewed by CDC staff for potential errors and to validate HAI classifications prior to analysis. HAI prevalence, number of residents with >1 HAI per number of surveyed residents ×100, and 95% CIs were calculated overall (pooled mean) and for selected resident characteristics. Data were analyzed using SAS v9.4 software. Results: Among 15,296 residents in 161 NHs, 358 residents with 375 HAIs were identified. The most common HAI sites were skin (32%), respiratory tract (29%), and urinary tract (20%). Cellulitis, soft-tissue or wound infection, symptomatic UTI, and cold or pharyngitis were the most common individual HAIs (Fig. 1). Overall HAI prevalence was 2.3 per 100 residents (95% CI, 2.1–2.6); at the NH level, the median HAI prevalence was 1.8 and ranged from 0 to 14.3 (interquartile range, 0–3.1). At the resident level (Fig. 2), HAI prevalence was significantly higher in persons admitted for postacute care with diabetes, with a pressure ulcer, receiving wound care, or with a device. Conclusions: In this large-scale survey, 1 in 43 NH residents had an HAI on a given day. Three HAI types comprised >80% of infections. In addition to identifying characteristics that place residents at higher risk for HAIs, these findings provide important data on HAI epidemiology in NHs that can be used to expand HAI surveillance and inform prevention policies and practices.