Many triage algorithms exist for use in mass-casualty incidents (MCIs) involving pediatric patients. Most of these algorithms have not been validated for reliability across users.

Investigators sought to compare inter-rater reliability (IRR) and agreement among five MCI algorithms used in the pediatric population.

A dataset of 253 pediatric (<14 years of age) trauma activations from a Level I trauma center was used to obtain prehospital information and demographics. Three raters were trained on five MCI triage algorithms: Simple Triage and Rapid Treatment (START) and JumpSTART, as appropriate for age (combined as J-START); Sort Assess Life-Saving Intervention Treatment (SALT); Pediatric Triage Tape (PTT); CareFlight (CF); and Sacco Triage Method (STM). Patient outcomes were collected but not available to raters. Each rater triaged the full set of patients into Green, Yellow, Red, or Black categories with each of the five MCI algorithms. The IRR was reported as weighted kappa scores with 95% confidence intervals (CI). Descriptive statistics were used to describe inter-rater and inter-MCI algorithm agreement.

Of the 253 patients, 247 had complete triage assignments among the five algorithms and were included in the study. The IRR was excellent for a majority of the algorithms; however, J-START and CF had the highest reliability with a kappa 0.94 or higher (0.9-1.0, 95% CI for overall weighted kappa). The greatest variability was in SALT among Green and Yellow patients. Overall, J-START and CF had the highest inter-rater and inter-MCI algorithm agreements.

The IRR was excellent for a majority of the algorithms. The SALT algorithm, which contains subjective components, had the lowest IRR when applied to this dataset of pediatric trauma patients. Both J-START and CF demonstrated the best overall reliability and agreement.

Family members living with relatives with severe acquired brain injury (ABI) face many challenges. Although this is recognised, service provision in the UK is poor and needs development.

In order to support innovative service delivery for family members, we reflect on the research carried out by the first author using a new perspective – a lifeworld humanising approach in order to consider (a) the dehumanising existential challenges facing family members of people living with severe ABI and (b) what family members most value in service delivery presented in humanising terms.

Following ABI, family members may enter a parallel lifeworld (feeling separate from ‘usual’ life as it flows by) and face fundamental existential challenges of isolation, loss of agency, dislocation, loss of meaning and loss of personal journey. Family members have reported that service providers who are highly valued are those who act as ‘expert companions’. This role involves supporting families in some, if not all of the following (a) reaching across into the lifeworld of the family member and appreciating and validating what they are facing, (b) helping them make sense of their situation in terms which are meaningful to them and which they can explain to others, (c) through ABI expertise, supporting their relative through knowing their interests and needs and adapting the environment to suit these to help their relative to ‘settle’ and flourish, (d) supporting family members to share their life experiences – developing safe and trusting relationships, (e) having a humane, positive, creative and for some, a humorous approach, (f) being responsive to changing situations, (g) being available to call during times of worry or crisis and (h) help link with others and helpful networks.

It is suggested that the role and approach of companion may help family members regain some sense of their own life and their well-being.

Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose.

This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients.

An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools.

A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The “modified Baxt positive and alive” outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. “Modified Baxt negative and <24 hours LOS” had the highest agreement with the COT green at 89%.

Assessment of algorithms for triaging pediatric MCI patients is complicated by the lack of a gold standard outcome tool and variability between existing measures.

The most immediate response of the research community to COVID-19 has been a focus on understanding the effects, treatment and prevention of infection. Of equal and ongoing importance is elucidating the impact of mitigation measures, such as lockdown, on the well-being of societies. Research about mental health and lockdown in the UK has predominately involved large surveys that are likely to encounter self-selection bias. Further, self-reporting does not constitute a clinical judgement.

To (a) compare the age, gender and ethnicity of patients experiencing mental health emergencies prior compared with during lockdown, (b) determine whether the nature of mental health emergencies has changed during compared with before lockdown, (c) explore the utility of emergency medical service data for identifying vulnerability to mental health emergencies in real time during a pandemic.

A total of 32 401 clinical records of ambulance paramedics attending mental health emergencies in the East Midlands of the UK between 23 March and 31 July 2020 and the same period in 2019 were analysed using binary logistic regression.

People of younger age, male gender and South Asian and Black ethnicity are particularly vulnerable to acute mental health conditions during lockdown. Patients with acute cases of anxiety have increased during lockdown whereas suicide and intentional drug overdose have decreased.

Self-reported data may underrepresent the true impact of lockdown on male mental health and ethnic minority groups. Emergency medical data can be used to identify vulnerable communities in the context of the extraordinary circumstances surrounding the current pandemic, as well as under more ordinary circumstances.

Registry-based trials have emerged as a potentially cost-saving study methodology. Early estimates of cost savings, however, conflated the benefits associated with registry utilisation and those associated with other aspects of pragmatic trial designs, which might not all be as broadly applicable. In this study, we sought to build a practical tool that investigators could use across disciplines to estimate the ranges of potential cost differences associated with implementing registry-based trials versus standard clinical trials.

We built simulation Markov models to compare unique costs associated with data acquisition, cleaning, and linkage under a registry-based trial design versus a standard clinical trial. We conducted one-way, two-way, and probabilistic sensitivity analyses, varying study characteristics over broad ranges, to determine thresholds at which investigators might optimally select each trial design.

Registry-based trials were more cost effective than standard clinical trials 98.6% of the time. Data-related cost savings ranged from $4300 to $600,000 with variation in study characteristics. Cost differences were most reactive to the number of patients in a study, the number of data elements per patient available in a registry, and the speed with which research coordinators could manually abstract data. Registry incorporation resulted in cost savings when as few as 3768 independent data elements were available and when manual data abstraction took as little as 3.4 seconds per data field.

Registries offer important resources for investigators. When available, their broad incorporation may help the scientific community reduce the costs of clinical investigation. We offer here a practical tool for investigators to assess potential costs savings.

The Sort, Access, Life-saving interventions, Treatment and/or Triage (SALT) mass-casualty incident (MCI) algorithm is unique in that it includes two subjective questions during the triage process: “Is the victim likely to survive given the resources?” and “Is the injury minor?”

Given this subjectivity, it was hypothesized that as casualties increase, the inter-rater reliability (IRR) of the tool would decline, due to an increase in the number of patients triaged as Minor and Expectant.

A pre-collected dataset of pediatric trauma patients age <14 years from a single Level 1 trauma center was used to generate “patients.” Three trained raters triaged each patient using SALT as if they were in each of the following scenarios: 10, 100, and 1,000 victim MCIs. Cohen’s kappa test was used to evaluate IRR between the raters in each of the scenarios.

A total of 247 patients were available for triage. The kappas were consistently “poor” to “fair:” 0.37 to 0.59 in the 10-victim scenario; 0.13 to 0.36 in the 100-victim scenario; and 0.05 to 0.36 in the 1,000-victim scenario. There was an increasing percentage of subjects triaged Minor as the number of estimated victims increased: 27.8% increase from 10- to 100-victim scenario and 7.0% increase from 100- to 1,000-victim scenario. Expectant triage categorization of patients remained stable as victim numbers increased.

Overall, SALT demonstrated poor IRR in this study of increasing casualty counts while triaging pediatric patients. Increased casualty counts in the scenarios did lead to increased Minor but not Expectant categorizations.

Major depressive disorder and neuroticism (Neu) share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression.

We analysed summary statistics from genome-wide association studies (GWAS) of depression (from the Psychiatric Genomics Consortium, 23andMe and UK Biobank) and compared them with GWAS of Neu (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only Neu or with both. Second, we estimated partial genetic correlations to test whether the depression's genetic link with other phenotypes was explained by shared overlap with Neu.

We found evidence that most genomic regions (25/37) associated with depression are likely to be shared with Neu. The overlapping common genetic variance of depression and Neu was genetically correlated primarily with psychiatric disorders. We found that the genetic contributions to depression, that were not shared with Neu, were positively correlated with metabolic phenotypes and cardiovascular disease, and negatively correlated with the personality trait conscientiousness. After removing shared genetic overlap with Neu, depression still had a specific association with schizophrenia, bipolar disorder, coronary artery disease and age of first birth. Independent of depression, Neu had specific genetic correlates in ulcerative colitis, pubertal growth, anorexia and education.

Our findings demonstrate that, while genetic risk factors for depression are largely shared with Neu, there are also non-Neu-related features of depression that may be useful for further patient or phenotypic stratification.

While echocardiographic parameters are used to quantify ventricular function in infants with single ventricle physiology, there are few data comparing these to invasive measurements. This study correlates echocardiographic measures of diastolic function with ventricular end-diastolic pressure in infants with single ventricle physiology prior to superior cavopulmonary anastomosis.

Data from 173 patients enrolled in the Pediatric Heart Network Infant Single Ventricle enalapril trial were analysed. Those with mixed ventricular types (n = 17) and one outlier (end-diastolic pressure = 32 mmHg) were excluded from the analysis, leaving a total sample size of 155 patients. Echocardiographic measurements were correlated to end-diastolic pressure using Spearman’s test.

Median age at echocardiogram was 4.6 (range 2.5–7.4) months. Median ventricular end-diastolic pressure was 7 (range 3–19) mmHg. Median time difference between the echocardiogram and catheterisation was 0 days (range −35 to 59 days). Examining the entire cohort of 155 patients, no echocardiographic diastolic function variable correlated with ventricular end-diastolic pressure. When the analysis was limited to the 86 patients who had similar sedation for both studies, the systolic:diastolic duration ratio had a significant but weak negative correlation with end-diastolic pressure (r = −0.3, p = 0.004). The remaining echocardiographic variables did not correlate with ventricular end-diastolic pressure.

In this cohort of infants with single ventricle physiology prior to superior cavopulmonary anastomosis, most conventional echocardiographic measures of diastolic function did not correlate with ventricular end-diastolic pressure at cardiac catheterisation. These limitations should be factored into the interpretation of quantitative echo data in this patient population.