HIV-associated neurocognitive disorders (HANDs) are prevalent in older people living with HIV (PLWH) worldwide. HAND prevalence and incidence studies of the newly emergent population of combination antiretroviral therapy (cART)-treated older PLWH in sub-Saharan Africa are currently lacking. We aimed to estimate HAND prevalence and incidence using robust measures in stable, cART-treated older adults under long-term follow-up in Tanzania and report cognitive comorbidities.

Longitudinal study

A systematic sample of consenting HIV-positive adults aged ≥50 years attending routine clinical care at an HIV Care and Treatment Centre during March–May 2016 and followed up March–May 2017.

HAND by consensus panel Frascati criteria based on detailed locally normed low-literacy neuropsychological battery, structured neuropsychiatric clinical assessment, and collateral history. Demographic and etiological factors by self-report and clinical records.

In this cohort (n = 253, 72.3% female, median age 57), HAND prevalence was 47.0% (95% CI 40.9–53.2, n = 119) despite well-managed HIV disease (Mn CD4 516 (98-1719), 95.5% on cART). Of these, 64 (25.3%) were asymptomatic neurocognitive impairment, 46 (18.2%) mild neurocognitive disorder, and 9 (3.6%) HIV-associated dementia. One-year incidence was high (37.2%, 95% CI 25.9 to 51.8), but some reversibility (17.6%, 95% CI 10.0–28.6 n = 16) was observed.

HAND appear highly prevalent in older PLWH in this setting, where demographic profile differs markedly to high-income cohorts, and comorbidities are frequent. Incidence and reversibility also appear high. Future studies should focus on etiologies and potentially reversible factors in this setting.

There is global interest in the reconfiguration of community mental health services, including primary care, to improve clinical and cost effectiveness.

This study seeks to describe patterns of service use, continuity of care, health risks, physical healthcare monitoring and the balance between primary and secondary mental healthcare for people with severe mental illness in receipt of secondary mental healthcare in the UK.

We conducted an epidemiological medical records review in three UK sites. We identified 297 cases randomly selected from the three participating mental health services. Data were manually extracted from electronic patient medical records from both secondary and primary care, for a 2-year period (2012–2014). Continuous data were summarised by mean and s.d. or median and interquartile range (IQR). Categorical data were summarised as percentages.

The majority of care was from secondary care practitioners: of the 18 210 direct contacts recorded, 76% were from secondary care (median, 36.5; IQR, 14–68) and 24% were from primary care (median, 10; IQR, 5–20). There was evidence of poor longitudinal continuity: in primary care, 31% of people had poor longitudinal continuity (Modified Modified Continuity Index ≤0.5), and 43% had a single named care coordinator in secondary care services over the 2 years.

The study indicates scope for improvement in supporting mental health service delivery in primary care. Greater knowledge of how care is organised presents an opportunity to ensure some rebalancing of the care that all people with severe mental illness receive, when they need it. A future publication will examine differences between the three sites that participated in this study.

Emotional cognition and effective interpretation of affective information is an important factor in social interactions and everyday functioning, and difficulties in these areas may contribute to aetiology and maintenance of mental health conditions. In younger people with depression and anxiety, research suggests significant alterations in behavioural and brain activation aspects of emotion processing, with a tendency to appraise neutral stimuli as negative and attend preferentially to negative stimuli. However, in ageing, research suggests that emotion processing becomes subject to a ‘positivity effect’, whereby older people attend more to positive than negative stimuli.

This review examines data from studies of emotion processing in Late-Life Depression and Late-Life Anxiety to attempt to understand the significance of emotion processing variations in these conditions, and their interaction with changes in emotion processing that occur with ageing.

We conducted a systematic review following PRISMA guidelines. Articles that used an emotion-based processing task, examined older persons with depression or an anxiety disorder and included a healthy control group were included.

In Late-Life Depression, there is little consistent behavioural evidence of impaired emotion processing, but there is evidence of altered brain circuitry during these processes. In Late-Life Anxiety and Post-Traumatic Stress disorder, there is evidence of interference with processing of negative or threat-related words.

How these findings fit with the positivity bias of ageing is not clear. Future research is required in larger groups, further examining the interaction between illness and age and the significance of age at disease onset.

To determine whether the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA) Clostridioides difficile infection (CDI) severity criteria adequately predicts poor outcomes.

Retrospective validation study.

Patients with CDI in the Veterans’ Affairs Health System from January 1, 2006, to December 31, 2016.

For the 2010 criteria, patients with leukocytosis or a serum creatinine (SCr) value ≥1.5 times the baseline were classified as severe. For the 2018 criteria, patients with leukocytosis or a SCr value ≥1.5 mg/dL were classified as severe. Poor outcomes were defined as hospital or intensive care admission within 7 days of diagnosis, colectomy within 14 days, or 30-day all-cause mortality; they were modeled as a function of the 2010 and 2018 criteria separately using logistic regression.

We analyzed data from 86,112 episodes of CDI. Severity was unclassifiable in a large proportion of episodes diagnosed in subacute care (2010, 58.8%; 2018, 49.2%). Sensitivity ranged from 0.48 for subacute care using 2010 criteria to 0.73 for acute care using 2018 criteria. Areas under the curve were poor and similar (0.60 for subacute care and 0.57 for acute care) for both versions, but negative predictive values were >0.80.

Model performances across care settings and criteria versions were generally poor but had reasonably high negative predictive value. Many patients in the subacute-care setting, an increasing fraction of CDI cases, could not be classified. More work is needed to develop criteria to identify patients at risk of poor outcomes.

Connectedness is a central dimension of personal recovery from severe mental illness (SMI). Research reports that people with SMI have lower social capital and poorer-quality social networks compared to the general population.

To identify personal well-being network (PWN) types and explore additional insights from mapping connections to places and activities alongside social ties.

We carried out 150 interviews with individuals with SMI and mapped social ties, places and activities and their impact on well-being. PWN types were developed using social network analysis and hierarchical k-means clustering of this data.

Three PWN types were identified: formal and sparse; family and stable; and diverse and active. Well-being and social capital varied within and among types. Place and activity data indicated important contextual differences within social connections that were not found by mapping social networks alone.

Place locations and meaningful activities are important aspects of people's social worlds. Mapped alongside social networks, PWNs have important implications for person-centred recovery approaches through providing a broader understanding of individual's lives and resources.

None.

The purpose of this study was to quantify the effect of multidrug-resistant (MDR) gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA) healthcare-associated infections (HAIs) on mortality following infection, regardless of patient location.

We conducted a retrospective cohort study of patients with an inpatient admission in the US Department of Veterans Affairs (VA) system between October 1, 2007, and November 30, 2010. We constructed multivariate log-binomial regressions to assess the impact of a positive culture on mortality in the 30- and 90-day periods following the first positive culture, using a propensity-score–matched subsample.

Patients identified with positive cultures due to MDR Acinetobacter (n=218), MDR Pseudomonas aeruginosa (n=1,026), and MDR Enterobacteriaceae (n=3,498) were propensity-score matched to 14,591 patients without positive cultures due to these organisms. In addition, 3,471 patients with positive cultures due to MRSA were propensity-score matched to 12,499 patients without positive MRSA cultures. Multidrug-resistant gram-negative bacteria were associated with a significantly elevated risk of mortality both for invasive (RR, 2.32; 95% CI, 1.85–2.92) and noninvasive cultures (RR, 1.33; 95% CI, 1.22–1.44) during the 30-day period. Similarly, patients with MRSA HAIs (RR, 2.77; 95% CI, 2.39–3.21) and colonizations (RR, 1.32; 95% CI, 1.22–1.50) had an increased risk of death at 30 days.

We found that HAIs due to gram-negative bacteria and MRSA conferred significantly elevated 30- and 90-day risks of mortality. This finding held true both for invasive cultures, which are likely to be true infections, and noninvasive infections, which are possibly colonizations.

Infect Control Hosp Epidemiol 2017;38:848–856

Estimates of the excess length of stay (LOS) attributable to healthcare-associated infections (HAIs) in which total LOS of patients with and without HAIs are biased because of failure to account for the timing of infection. Alternate methods that appropriately treat HAI as a time-varying exposure are multistate models and cohort studies, which match regarding the time of infection. We examined the magnitude of this time-dependent bias in published studies that compared different methodological approaches.

We conducted a systematic review of the published literature to identify studies that report attributable LOS estimates using both total LOS (time-fixed) methods and either multistate models or matching patients with and without HAIs using the timing of infection.

Of the 7 studies that compared time-fixed methods to multistate models, conventional methods resulted in estimates of the LOS to HAIs that were, on average, 9.4 days longer or 238% greater than those generated using multistate models. Of the 5 studies that compared time-fixed methods to matching on timing of infection, conventional methods resulted in estimates of the LOS to HAIs that were, on average, 12.6 days longer or 139% greater than those generated by matching on timing of infection.

Our results suggest that estimates of the attributable LOS due to HAIs depend heavily on the methods used to generate those estimates. Overestimation of this effect can lead to incorrect assumptions of the likely cost savings from HAI prevention measures.

Infect. Control Hosp. Epidemiol. 2015;36(9):1089–1094

Standard estimates of the impact of Clostridium difficile infections (CDI) on inpatient lengths of stay (LOS) may overstate inpatient care costs attributable to CDI. In this study, we used multistate modeling (MSM) of CDI timing to reduce bias in estimates of excess LOS.

A retrospective cohort study of all hospitalizations at any of 120 acute care facilities within the US Department of Veterans Affairs (VA) between 2005 and 2012 was conducted. We estimated the excess LOS attributable to CDI using an MSM to address time-dependent bias. Bootstrapping was used to generate 95% confidence intervals (CI). These estimates were compared to unadjusted differences in mean LOS for hospitalizations with and without CDI.

During the study period, there were 3.96 million hospitalizations and 43,540 CDIs. A comparison of unadjusted means suggested an excess LOS of 14.0 days (19.4 vs 5.4 days). In contrast, the MSM estimated an attributable LOS of only 2.27 days (95% CI, 2.14–2.40). The excess LOS for mild-to-moderate CDI was 0.75 days (95% CI, 0.59–0.89), and for severe CDI, it was 4.11 days (95% CI, 3.90–4.32). Substantial variation across the Veteran Integrated Services Networks (VISN) was observed.

CDI significantly contributes to LOS, but the magnitude of its estimated impact is smaller when methods are used that account for the time-varying nature of infection. The greatest impact on LOS occurred among patients with severe CDI. Significant geographic variability was observed. MSM is a useful tool for obtaining more accurate estimates of the inpatient care costs of CDI.

Infect. Control Hosp. Epidemiol. 2015;36(9):1024–1030