Patients refusing transportation is common EMS practice with potentially fatal outcomes. Determining which patients are at high risk for poor outcomes is poorly defined. This study described patients who experienced an out-of-hospital cardiac arrest (OHCA) within 24 hours of refusing transportation.

This is a retrospective, descriptive study of patients who had an OHCA within 24 hours of refusing EMS transportation between 2019 to 2021. Data was obtained from a large, urban medical control authority seeing 175,000 EMS calls annually. We reviewed patient demographics, EMS events when transportation was refused, and cardiac arrest outcome.

There were 6, 30, and 28 EMS refusals resulting in OHCA in 2019, 2020, and 2021. Patients who had OHCA were 65.7 (range 28-103) years old, and African American (54/64). Patients had HTN (36/64), diabetes (19/64), COPD (11/64), and CHF (7/64). Common complaints included breathing problems (17/64), near syncope (8/64) however chest pain was uncommon (4/64). One (28/64) or two (13/64) abnormal vital signs were present and missing vital signs (28/64) were common. Tachycardia (32.8%, 21/64), HTN (29.7%, 19/64), and hypotension (17.2%, 11/64) were more prevalent in the OHCA population compared to all refusal patients (Tachycardia 0.33% [1,978/598,416], HTN 2.27% [13,601/598,416], and hypotension 0.04% [218/598,416]). Patients were seen by both ALS (29/64) and BLS (35/64) providers. Most providers documented risk including death (38/64) though few contacted medical control (14/64). Return encounter for OHCA resulted in obvious deaths (23/64) or field termination (20/64). Few patients achieved ROSC (7/64).

Patients who had an OHCA within 24 hours of refusing transport had underlying comorbidities and abnormal or missing vital signs. The patients experienced tachycardia, hypertension, and hypotension at a higher rate than the overall refusal population. Few patients obtained ROSC. Further research is needed to determine methods to mitigate poor outcomes and decrease refusals.

To examine the costs and cost-effectiveness of mirtazapine compared to placebo over 12-week follow-up.

Economic evaluation in a double-blind randomized controlled trial of mirtazapine vs. placebo.

Community settings and care homes in 26 UK centers.

People with probable or possible Alzheimer’s disease and agitation.

Primary outcome included incremental cost of participants’ health and social care per 6-point difference in CMAI score at 12 weeks. Secondary cost-utility analyses examined participants’ and unpaid carers’ gain in quality-adjusted life years (derived from EQ-5D-5L, DEMQOL-Proxy-U, and DEMQOL-U) from the health and social care and societal perspectives.

One hundred and two participants were allocated to each group; 81 mirtazapine and 90 placebo participants completed a 12-week assessment (87 and 95, respectively, completed a 6-week assessment). Mirtazapine and placebo groups did not differ on mean CMAI scores or health and social care costs over the study period, before or after adjustment for center and living arrangement (independent living/care home). On the primary outcome, neither mirtazapine nor placebo could be considered a cost-effective strategy with a high level of confidence. Groups did not differ in terms of participant self- or proxy-rated or carer self-rated quality of life scores, health and social care or societal costs, before or after adjustment.

On cost-effectiveness grounds, the use of mirtazapine cannot be recommended for agitated behaviors in people living with dementia. Effective and cost-effective medications for agitation in dementia remain to be identified in cases where non-pharmacological strategies for managing agitation have been unsuccessful.

Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).

A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.

In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.

Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.

To investigate factors associated with suicidal ideation (SI) around the time of dementia diagnosis. We hypothesised relatively preserved cognition, co-occurring physical and psychiatric disorders, functional impairments, and dementia diagnosis subtype would be associated with a higher risk of SI.

Cross-sectional study using routinely collected electronic mental healthcare records.

National Health Service secondary mental healthcare services in South London, UK, serving a population of over 1.36 million residents.

Patients who received a diagnosis of dementia (Alzheimer’s, vascular, mixed Alzheimer’s/vascular, or dementia with Lewy bodies) between 1 Nov 2007–31 Oct 2021: 18,252 people were identified during the observation period.

A natural language processing algorithm was used to identify recorded clinician recording of SI around the time of dementia diagnosis. Sociodemographic and clinical characteristics were also measured around the time of diagnosis. We compared people diagnosed with non-Alzheimer’s dementia to those with Alzheimer’s and used statistical models to adjust for putative confounders.

15.1% of patients had recorded SI, which was more common in dementia with Lewy bodies compared to other dementia diagnoses studied. After adjusting for sociodemographic and clinical factors, SI was more frequent in those with depression and dementia with Lewy bodies and less common in those with impaired activities of daily living and in vascular dementia. Agitated behavior and hallucinations were not associated with SI in the final model.

Our findings highlight the importance of identifying and treating depressive symptoms in people with dementia and the need for further research into under-researched dementia subtypes.

The rate of normal birth outcomes (i.e. full-term births without intervention) for women with severe mental illness (SMI – psychotic and bipolar disorders) is not known. We examined rates of birth without intervention (spontaneous labour onset, spontaneous vaginal delivery without instruments, no episiotomy and no indication of pre- or post-delivery anaesthesia) in women with SMI (584 pregnancies) compared with a control population (70 942 pregnancies). Outcome ratios were calculated standardising for age. Women with SMI were less likely to have a birth without intervention (29.5%) relative to the control population (36.8%) (standardised outcome ratio 0.74, 95% CI 0.63–0.87).

Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan.

This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample.

32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables.

Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.

To describe the epidemiology of patients with nonintestinal carbapenem-resistant Enterobacterales (CRE) colonization and to compare clinical outcomes of these patients to those with CRE infection.

A secondary analysis of Consortium on Resistance Against Carbapenems in Klebsiella and other Enterobacteriaceae 2 (CRACKLE-2), a prospective observational cohort.

A total of 49 US short-term acute-care hospitals.

Patients hospitalized with CRE isolated from clinical cultures, April, 30, 2016, through August 31, 2017.

We described characteristics of patients in CRACKLE-2 with nonintestinal CRE colonization and assessed the impact of site of colonization on clinical outcomes. We then compared outcomes of patients defined as having nonintestinal CRE colonization to all those defined as having infection. The primary outcome was a desirability of outcome ranking (DOOR) at 30 days. Secondary outcomes were 30-day mortality and 90-day readmission.

Of 547 patients with nonintestinal CRE colonization, 275 (50%) were from the urinary tract, 201 (37%) were from the respiratory tract, and 71 (13%) were from a wound. Patients with urinary tract colonization were more likely to have a more desirable clinical outcome at 30 days than those with respiratory tract colonization, with a DOOR probability of better outcome of 61% (95% confidence interval [CI], 53%–71%). When compared to 255 patients with CRE infection, patients with CRE colonization had a similar overall clinical outcome, as well as 30-day mortality and 90-day readmission rates when analyzed in aggregate or by culture site. Sensitivity analyses demonstrated similar results using different definitions of infection.

Patients with nonintestinal CRE colonization had outcomes similar to those with CRE infection. Clinical outcomes may be influenced more by culture site than classification as “colonized” or “infected.”

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Individuals present in lower Manhattan during the 9/11 World Trade Center (WTC) disaster suffered from significant physical and psychological trauma. Studies of longitudinal psychological distress among those exposed to trauma have been limited to relatively short durations of follow-up among smaller samples.

The current study longitudinally assessed heterogeneity in trajectories of psychological distress among WTC Health Registry enrollees – a prospective cohort health study of responders, students, employees, passersby, and residents in the affected area (N = 30 839) – throughout a 15-year period following the WTC disaster. Rescue/recovery status and exposure to traumatic events of 9/11, as well as sociodemographic factors and health status, were assessed as risk factors for trajectories of psychological distress.

Five psychological distress trajectory groups were found: none-stable, low-stable, moderate-increasing, moderate-decreasing, and high-stable. Of the study sample, 78.2% were classified as belonging to the none-stable or low-stable groups. Female sex, being younger at the time of 9/11, lower education and income were associated with a higher probability of being in a greater distress trajectory group relative to the none-stable group. Greater exposure to traumatic events of 9/11 was associated with a higher probability of a greater distress trajectory, and community members (passerby, residents, and employees) were more likely to be in greater distress trajectory groups – especially in the moderate-increasing [odds ratios (OR) 2.31 (1.97–2.72)] and high-stable groups [OR 2.37 (1.81–3.09)] – compared to the none-stable group.

The current study illustrated the heterogeneity in psychological distress trajectories following the 9/11 WTC disaster, and identified potential avenues for intervention in future disasters.

Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction.

Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction.

Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback.

All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction.

The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.