To understand which anthropometric diagnostic criteria best discriminate higher from lower risk of death in children and explore programme implications.

A multiple cohort individual data meta-analysis of mortality risk (within 6 months of measurement) by anthropometric case definitions. Sensitivity, specificity, informedness and inclusivity in predicting mortality, face validity and compatibility with current standards and practice were assessed and operational consequences were modelled.

Community-based cohort studies in twelve low-income countries between 1977 and 2013 in settings where treatment of wasting was not widespread.

Children aged 6 to 59 months.

Of the twelve anthropometric case definitions examined, four (weight-for-age Z-score (WAZ) <−2), (mid-upper arm circumference (MUAC) <125 mm), (MUAC < 115 mm or WAZ < −3) and (WAZ < −3) had the highest informedness in predicting mortality. A combined case definition (MUAC < 115 mm or WAZ < −3) was better at predicting deaths associated with weight-for-height Z-score <−3 and concurrent wasting and stunting (WaSt) than the single WAZ < −3 case definition. After the assessment of all criteria, the combined case definition performed best. The simulated workload for programmes admitting based on MUAC < 115 mm or WAZ < −3, when adjusted with a proxy for required intensity and/or duration of treatment, was 1·87 times larger than programmes admitting on MUAC < 115 mm alone.

A combined case definition detects nearly all deaths associated with severe anthropometric deficits suggesting that therapeutic feeding programmes may achieve higher impact (prevent mortality and improve coverage) by using it. There remain operational questions to examine further before wide-scale adoption can be recommended.

To compare the prognostic value of mid-upper arm circumference (MUAC), weight-for-height Z-score (WHZ) and weight-for-age Z-score (WAZ) for predicting death over periods of 1, 3 and 6 months follow-up in children.

Pooled analysis of twelve prospective studies examining survival after anthropometric assessment. Sensitivity and false-positive ratios to predict death within 1, 3 and 6 months were compared for three individual anthropometric indices and their combinations.

Community-based, prospective studies from twelve countries in Africa and Asia.

Children aged 6–59 months living in the study areas.

For all anthropometric indices, the receiver operating characteristic curves were higher for shorter than for longer durations of follow-up. Sensitivity was higher for death with 1-month follow-up compared with 6 months by 49 % (95 % CI (30, 69)) for MUAC < 115 mm (P < 0·001), 48 % (95 % CI (9·4, 87)) for WHZ < -3 (P < 0·01) and 28 % (95 % CI (7·6, 42)) for WAZ < -3 (P < 0·005). This was accompanied by an increase in false positives of only 3 % or less. For all durations of follow-up, WAZ < -3 identified more children who died and were not identified by WHZ < -3 or by MUAC < 115 mm, 120 mm or 125 mm, but the use of WAZ < -3 led to an increased false-positive ratio up to 16·4 % (95 % CI (12·0, 20·9)) compared with 3·5 % (95 % CI (0·4, 6·5)) for MUAC < 115 mm alone.

Frequent anthropometric measurements significantly improve the identification of malnourished children with a high risk of death without markedly increasing false positives. Combining two indices increases sensitivity but also increases false positives among children meeting case definitions.

The number of people over the age of 65 attending Emergency Departments (ED) in the United Kingdom (UK) is increasing. Those who attend with a mental health related problem may be referred to liaison psychiatry for assessment. Improving responsiveness and integration of liaison psychiatry in general hospital settings is a national priority. To do this psychiatry teams must be adequately resourced and organised. However, it is unknown how trends in the number of referrals of older people to liaison psychiatry teams by EDs are changing, making this difficult.

We performed a national multi-centre retrospective service evaluation, analysing existing psychiatry referral data from EDs of people over 65. Sites were selected from a convenience sample of older peoples liaison psychiatry departments. Departments from all regions of the UK were invited to participate via the RCPsych liaison and older peoples faculty email distribution lists. From departments who returned data, we combined the date and described trends in the number and rate of referrals over a 7 year period.

Referral data from up to 28 EDs across England and Scotland over a 7 year period were analysed (n = 18828 referrals). There is a general trend towards increasing numbers of older people referred to liaison psychiatry year on year. Rates rose year on year from 1.4 referrals per 1000 ED attenders (>65 years) in 2011 to 4.5 in 2019 . There is inter and intra site variability in referral numbers per 1000 ED attendances between different departments, ranging from 0.1 - 24.3.

To plan an effective healthcare system we need to understand the population it serves, and have appropriate structures and processes within it. The overarching message of this study is clear; older peoples mental health emergencies presenting in ED are common and appear to be increasingly so. Without appropriate investment either in EDs or community mental health services, this is unlikely to improve.

The data also suggest very variable inter-departmental referral rates. It is not possible to establish why rates from one department to another are so different, or whether outcomes for the population they serve are better or worse. The data does however highlight the importance of asking further questions about why the departments are different, and what impact that has on the patients they serve.

Recently the NHS has expanded the provision of liaison mental health services (LMHS) to ensure that every acute hospital with an emergency department in England has a liaison psychiatry service. Little work has been undertaken to explore first-hand experiences of these services. The aim of this study was to capture service users’ experiences of LMHS in both emergency departments and acute inpatient wards in the UK, with a view to adapt services to better meet the needs of its users.

This cross-sectional internet survey was initially advertised from May-July 2017 using the social media platform Facebook. Due to a paucity of male respondents, it was re-run from November 2017-February 2018, specifically targeting this demographic group. 184 people responded to the survey, of which 147 were service users and 37 were service users’ accompanying partners, friends or family members. The survey featured a structured questionnaire divided into three categories: the profile of the respondent, perceived professionalism of LMHS, and overall opinion of the service. Space was available for free-text comments in each section. Descriptive analysis of quantitative data was undertaken with R statistical software V.3.2.2. Qualitative data from free-text comments were transcribed and interpreted independently by three researchers using framework analysis; familiarisation with the data was followed by identification of a thematic framework, indexing, charting, mapping and interpretation.

Opinions of the service were mixed but predominantly negative. 31% of service users and 27% of their loved ones found their overall contact with LMHS useful. Features most frequently identified as important were the provision of a 24/7 service, assessment by a variety of healthcare professionals and national standardisation of services. Respondents indicated that the least important feature was the provision of a separate service for older people. They also expressed that a desirable LMHS would include faster assessments following referral from the parent team, clearer communication about next steps and greater knowledge of local services and third sector organisations.

Our survey identified mixed responses, however service users and their loved ones perceived LMHS more frequently as negative than positive. This may be attributed to the recent governmental drive to assess, treat and discharge 95% of all patients seen in emergency departments within four hours of initial attendance. Additionally, dissatisfied service users are more likely to volunteer their opinions. The evaluation and adaptation of LMHS should be prioritised to enhance their inherent therapeutic value and improve engagement with treatment and future psychiatric care.

The effect of minor orthopaedic day surgery (MiODS) on patient’s mood.

A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study – Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively.

The mean physical component score of SF-36 before surgery was 45.3 (SD = ±10.1) and 8 weeks following surgery was 44.9 (SD = ±11.04) [n = 148, p = 0.51, 95% CI = (−1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov = 69.44) corresponded to a correlation coefficient, r = 0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with χ2 (df = 1) = 0.86 for which p = 0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected.

MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.

An estimated 293,300 healthcare-associated cases of Clostridium difficile infection (CDI) occur annually in the United States. To date, research has focused on developing risk prediction models for CDI that work well across institutions. However, this one-size-fits-all approach ignores important hospital-specific factors. We focus on a generalizable method for building facility-specific models. We demonstrate the applicability of the approach using electronic health records (EHR) from the University of Michigan Hospitals (UM) and the Massachusetts General Hospital (MGH).

We utilized EHR data from 191,014 adult admissions to UM and 65,718 adult admissions to MGH. We extracted patient demographics, admission details, patient history, and daily hospitalization details, resulting in 4,836 features from patients at UM and 1,837 from patients at MGH. We used L2 regularized logistic regression to learn the models, and we measured the discriminative performance of the models on held-out data from each hospital.

Using the UM and MGH test data, the models achieved area under the receiver operating characteristic curve (AUROC) values of 0.82 (95% confidence interval [CI], 0.80–0.84) and 0.75 ( 95% CI, 0.73–0.78), respectively. Some predictive factors were shared between the 2 models, but many of the top predictive factors differed between facilities.

A data-driven approach to building models for estimating daily patient risk for CDI was used to build institution-specific models at 2 large hospitals with different patient populations and EHR systems. In contrast to traditional approaches that focus on developing models that apply across hospitals, our generalizable approach yields risk-stratification models tailored to an institution. These hospital-specific models allow for earlier and more accurate identification of high-risk patients and better targeting of infection prevention strategies.

Infect Control Hosp Epidemiol 2018;39:425–433