To examine the association of co-morbidity with home-time after acute stroke and whether the association is influenced by age.

We conducted a province-wide study using linked administrative databases to identify all admissions for first acute ischemic stroke or intracerebral hemorrhage between 2007 and 2018 in Alberta, Canada. We used ischemic stroke-weighted Charlson Co-morbidity Index of 3 or more to identify those with severe co-morbidity. We used zero-inflated negative binomial models to determine the association of severe co-morbidity with 90-day and 1-year home-time, and logistic models for achieving ≥ 80 out of 90 days of home-time, assessing for effect modification by age and adjusting for sex, stroke type, comprehensive stroke center care, hypertension, atrial fibrillation, year of study, and separately adjusting for estimated stroke severity. We also evaluated individual co-morbidities.

Among 28,672 patients in our final cohort, severe co-morbidity was present in 27.7% and was associated with lower home-time, with a greater number of days lost at younger age (−13 days at age < 60 compared to −7 days at age 80+ years for 90-day home-time; −69 days at age < 60 compared to −51 days at age 80+ years for 1-year home-time). The reduction in probability of achieving ≥ 80 days of home-time was also greater at younger age (−22.7% at age < 60 years compared to −9.0% at age 80+ years). Results were attenuated but remained significant after adjusting for estimated stroke severity and excluding those who died. Myocardial infarction, diabetes, and cancer/metastases had a greater association with lower home-time at younger age, and those with dementia had the greatest reduction in home time.

Severe co-morbidity in acute stroke is associated with lower home-time, more strongly at younger age.

Incidence of first-episode psychosis (FEP) varies substantially across geographic regions. Phenotypes of subclinical psychosis (SP), such as psychotic-like experiences (PLEs) and schizotypy, present several similarities with psychosis. We aimed to examine whether SP measures varied across different sites and whether this variation was comparable with FEP incidence within the same areas. We further examined contribution of environmental and genetic factors to SP.

We used data from 1497 controls recruited in 16 different sites across 6 countries. Factor scores for several psychopathological dimensions of schizotypy and PLEs were obtained using multidimensional item response theory models. Variation of these scores was assessed using multi-level regression analysis to estimate individual and between-sites variance adjusting for age, sex, education, migrant, employment and relational status, childhood adversity, and cannabis use. In the final model we added local FEP incidence as a second-level variable. Association with genetic liability was examined separately.

Schizotypy showed a large between-sites variation with up to 15% of variance attributable to site-level characteristics. Adding local FEP incidence to the model considerably reduced the between-sites unexplained schizotypy variance. PLEs did not show as much variation. Overall, SP was associated with younger age, migrant, unmarried, unemployed and less educated individuals, cannabis use, and childhood adversity. Both phenotypes were associated with genetic liability to schizophrenia.

Schizotypy showed substantial between-sites variation, being more represented in areas where FEP incidence is higher. This supports the hypothesis that shared contextual factors shape the between-sites variation of psychosis across the spectrum.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

There is little known about the spectrum of cardiac injury in acute COVID-19 infection in children.

A single-centre, retrospective chart analysis was performed. The protocol was deemed IRB exempt. All patients under the age of 21 years admitted from 20 March, 2020 to 22 June, 2021 for acute symptomatic COVID-19 infection or clinical suspicion of multisystem inflammatory syndrome in children (MIS-C) associated with COVID-19 were included. Past medical history, lab findings, echocardiogram and electrocardiogram/telemetry findings, and clinical outcomes were reviewed.

Sixty-six patients with MIS-C and 178 with acute COVID-19 were reviewed. Patients with MIS-C had more cardiac testing than those with acute COVID-19. Inflammatory markers were more likely elevated, and function was more likely abnormal on echocardiogram in those with MIS-C with testing performed. Among patients with MIS-C, 17% had evidence of coronary dilation versus 0% in the acute COVID-19 group. One (0.6%) patient with acute COVID-19 had clinically significant electrocardiogram or telemetry findings, and this was in the setting of prior arrhythmias and CHD. Four (6%) patients with MIS-C had clinically significant findings on electrocardiogram or telemetry. Among patients with acute COVID-19, extracorporeal membrane oxygenation support was required in 0.6% of patients with acute COVID-19, and there was a 2.8% mortality. There were no deaths in the setting of MIS-C.

Patients with acute COVID-19 and clinical suspicion of cardiac injury had a lower incidence of abnormal laboratory findings, ventricular dysfunction, or significant arrhythmia than those with MIS-C.

While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis.

We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case–control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.

We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case–control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case–control status.

Controls (86.1%) and FEPp (75.63%) were most likely to report ‘because of friends’ as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: ‘to feel better’ as their RFUC (χ2 = 50.97; p < 0.001). RFUC ‘to feel better’ was associated with being a FEPp (OR 1.74; 95% CI 1.03–2.95) while RFUC ‘with friends’ was associated with being a control (OR 0.56; 95% CI 0.37–0.83). The path model indicated an association between RFUC ‘to feel better’ with heavy cannabis use and with FEPp-control status.

Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use ‘to feel better’. People who reported their reason for first using cannabis to ‘feel better’ were more likely to progress to heavy use and develop a psychotic disorder than those reporting ‘because of friends’.

To estimate the association between in situ steroids and spine surgical-site infections (SSIs), assessing spinal instrumentation as an effect modifier and adjusting for confounders.

Case–control study.

Rural academic medical center.

We identified 1,058 adults undergoing posterior fusion and laminectomy procedures as defined by the National Healthcare Safety Network without a pre-existing SSI between January 2020 and December 2021. We identified 26 SSI as cases and randomly selected 104 controls from the remaining patients without SSI.

The primary exposure was the intraoperative administration of methylprednisolone in situ (ie, either in the wound bed or as an epidural injection). The primary outcome was a clinical diagnosis of SSI within 6 months of a patient’s first spine surgery at our facility. We quantified the association between the exposure and outcome using logistic regression, using a product term to assess for effect modification by spinal instrumentation and the change-in-estimate approach to select significant confounders.

Adjusting for Charlson comorbidity index and malignancy, in situ steroids were significantly associated with spine SSI relative to no in situ steroids for instrumented procedures (adjusted odds ratio [aOR], 9.93; 95% confidence interval [CI], 1.54–64.0), but they were not associated with spine SSIs among noninstrumented procedures (aOR, 0.86; 95% CI, 0.15–4.93).

In situ steroids were significantly associated with spine SSI among instrumented procedures. The benefits of in situ steroids for pain management following spine surgery should be weighed against the risk of SSI, especially for instrumented procedures.

Despite the public health burden of traumatic brain injury (TBI) across broader society, most TBI studies have been isolated to a distinct subpopulation. The TBI research literature is fragmented further because often studies of distinct populations have used different assessment procedures and instruments. Addressing calls to harmonize the literature will require tools to link data collected from different instruments that measure the same construct, such as civilian mild traumatic brain injury (mTBI) and sports concussion symptom inventories.

We used item response theory (IRT) to link scores from the Rivermead Post Concussion Symptoms Questionnaire (RPQ) and the Sport Concussion Assessment Tool (SCAT) symptom checklist, widely used instruments for assessing civilian and sport-related mTBI symptoms, respectively. The sample included data from n = 397 patients who suffered a sports-related concussion, civilian mTBI, orthopedic injury control, or non-athlete control and completed the SCAT and/or RPQ.

The results of several analyses supported sufficient unidimensionality to treat the RPQ + SCAT combined item set as measuring a single construct. Fixed-parameter IRT was used to create a cross-walk table that maps RPQ total scores to SCAT symptom severity scores. Linked and observed scores were highly correlated (r = .92). Standard errors of the IRT scores were slightly higher for civilian mTBI patients and orthopedic controls, particularly for RPQ scores linked from the SCAT.

By linking the RPQ to the SCAT we facilitated efforts to effectively combine samples and harmonize data relating to mTBI.

The Passive Surveillance Stroke Severity (PaSSV) Indicator was derived to estimate stroke severity from variables in administrative datasets but has not been externally validated.

We used linked administrative datasets to identify patients with first hospitalization for acute stroke between 2007-2018 in Alberta, Canada. We used the PaSSV indicator to estimate stroke severity. We used Cox proportional hazard models and evaluated the change in hazard ratios and model discrimination for 30-day and 1-year case fatality with and without PaSSV. Similar comparisons were made for 90-day home time thresholds using logistic regression. We also linked with a clinical registry to obtain National Institutes of Health Stroke Scale (NIHSS) and compared estimates from models without stroke severity, with PaSSV, and with NIHSS.

There were 28,672 patients with acute stroke in the full sample. In comparison to no stroke severity, addition of PaSSV to the 30-day case fatality models resulted in improvement in model discrimination (C-statistic 0.72 [95%CI 0.71–0.73] to 0.80 [0.79–0.80]). After adjustment for PaSSV, admission to a comprehensive stroke center was associated with lower 30-day case fatality (adjusted hazard ratio changed from 1.03 [0.96–1.10] to 0.72 [0.67–0.77]). In the registry sample (N = 1328), model discrimination for 30-day case fatality improved with the inclusion of stroke severity. Results were similar for 1-year case fatality and home time outcomes.

Addition of PaSSV improved model discrimination for case fatality and home time outcomes. The validity of PASSV in two Canadian provinces suggests that it is a useful tool for baseline risk adjustment in acute stroke.

As part of a quality improvement project beginning in October 2011, our centre introduced changes to reduce radiation exposure during paediatric cardiac catheterisations. This led to significant initial decreases in radiation to patients. Starting in April 2016, we sought to determine whether these initial reductions were sustained.

After a 30-day trial period, we implemented (1) weight-based reductions in preset frame rates for fluoroscopy and angiography, (2) increased use of collimators and safety shields, (3) utilisation of stored fluoroscopy and virtual magnification, and (4) hiring of a devoted radiation technician. We collected patient weight (kg), total fluoroscopy time (min), and procedure radiation dosage (cGy-cm2) for cardiac catheterisations between October, 2011 and September, 2019.

A total of 1889 procedures were evaluated (196 pre-intervention, 303 in the post-intervention time period, and 1400 in the long-term group). Fluoroscopy times (18.3 ± 13.6 pre; 19.8 ± 14.1 post; 17.11 ± 15.06 long-term, p = 0.782) were not significantly different between the three groups. Patient mean radiation dose per kilogram decreased significantly after the initial quality improvement intervention (39.7% reduction, p = 0.039) and was sustained over the long term (p = 0.043). Provider radiation exposure was also significantly decreased from the onset of this project through the long-term period (overall decrease of 73%, p < 0.01) despite several changes in the interventional cardiologists who made up the team over this time period.

Introduction of technical and clinical practice changes can result in a significant reduction in radiation exposure for patients and providers in a paediatric cardiac catheterisation laboratory. These reductions can be maintained over the long term.

Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case–control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD).

Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons.

In case–control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case–case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54–0.92] and PRS-D (OR = 1.31, 95% CI 1.06–1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23–3.74).

Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases.

We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.

A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.

How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.