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.

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.

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Pharmacogenomic testing has emerged to aid medication selection for patients with major depressive disorder (MDD) by identifying potential gene-drug interactions (GDI). Many pharmacogenomic tests are available with varying levels of supporting evidence, including direct-to-consumer and physician-ordered tests. We retrospectively evaluated the safety of using a physician-ordered combinatorial pharmacogenomic test (GeneSight) to guide medication selection for patients with MDD in a large, randomized, controlled trial (GUIDED).

Patients diagnosed with MDD who had an inadequate response to ≥1 psychotropic medication were randomized to treatment as usual (TAU) or combinatorial pharmacogenomic test-guided care (guided-care). All received combinatorial pharmacogenomic testing and medications were categorized by predicted GDI (no, moderate, or significant GDI). Patients and raters were blinded to study arm, and physicians were blinded to test results for patients in TAU, through week 8. Measures included adverse events (AEs, present/absent), worsening suicidal ideation (increase of ≥1 on the corresponding HAM-D17 question), or symptom worsening (HAM-D17 increase of ≥1). These measures were evaluated based on medication changes [add only, drop only, switch (add and drop), any, and none] and study arm, as well as baseline medication GDI.

Most patients had a medication change between baseline and week 8 (938/1,166; 80.5%), including 269 (23.1%) who added only, 80 (6.9%) who dropped only, and 589 (50.5%) who switched medications. In the full cohort, changing medications resulted in an increased relative risk (RR) of experiencing AEs at both week 4 and 8 [RR 2.00 (95% CI 1.41–2.83) and RR 2.25 (95% CI 1.39–3.65), respectively]. This was true regardless of arm, with no significant difference observed between guided-care and TAU, though the RRs for guided-care were lower than for TAU. Medication change was not associated with increased suicidal ideation or symptom worsening, regardless of study arm or type of medication change. Special attention was focused on patients who entered the study taking medications identified by pharmacogenomic testing as likely having significant GDI; those who were only taking medications subject to no or moderate GDI at week 8 were significantly less likely to experience AEs than those who were still taking at least one medication subject to significant GDI (RR 0.39, 95% CI 0.15–0.99, p=0.048). No other significant differences in risk were observed at week 8.

These data indicate that patient safety in the combinatorial pharmacogenomic test-guided care arm was no worse than TAU in the GUIDED trial. Moreover, combinatorial pharmacogenomic-guided medication selection may reduce some safety concerns. Collectively, these data demonstrate that combinatorial pharmacogenomic testing can be adopted safely into clinical practice without risking symptom degradation among patients.

Myriad Neuroscience/Assurex Health