Zolpidem is a nonbenzodiazepine, which acts as a sedative- hypnotic that binds to GABA (A) receptors at the same location as benzodiazepines and increases GABA effects in the central nervous system (Kovacic et al. Oxidative medicine and cellular longevity 2009, 2(1), 52–57). Literature shows that behavioral changes including amnesia, hallucinations, and other neurocognitive effects are some of the known side effects (Edinoff et al. Health psychology research 2021, 9(1), 24927). We present a case about Ms. A, a female in her sixties with a history of major depressive disorder with psychotic symptoms who was brought into the hospital by the EMS under police custody after stabbing her granddaughter with a knife. During the evaluation she was dissociating with impaired memory of the circumstances of her presentation. Collateral information about Ms. A revealed that she had no history of being violent, or any history of psychoactive substance use. Ms. A’s home psychiatric medications consisted of Sertraline 100mg, Bupropion 150 mg, Zolpidem 5mg.

To better understand the potential risks with prescribing zolpidem in patient with insomnia.

In depth literature review about zolpidem. In addition, observation of Ms. A in the emergency with a full medical workup including but not limited to urine drug screen, brain imaging, lumbar puncture, etc.

Ms.A medical workup was positive for a urinalysis revealing asymptomatic bacteriuria and she was treated empirically with cefdinir. Her medication regimen consisted of Bupropion 150 mg and Sertraline 100m, both daily. Zolpidem was discontinued and changed to Clonazepam 0.5mg for insomnia. She was also started on Olanzapine 5mg in the AM and 10mg in the PM. Her mental status was noted to have improved after discontinuation of Zolpidem. Patient received one dose in the hospital but after two days since discontinuation her mental status improved. Upon literature review previous reports have been published citing cases of patients on Zolpidem physically acting out while sleeping in a parasomnia-like behavior, with no recollection of memories upon awakening. (Inagaki et al. Primary care companion to the Journal of clinical psychiatry 2010, 12(6)). There are case reports of Zolpidem associated homicide (Paradis et al.The primary care companion for CNS disorders 2012, 14(4).

One limitation of our study is the patient was noted to have a sudden change in behavior with altered mental status which may be attributed to an underlying asymptomatic bacteriuria. It should be noted that this may have been an incidental finding. This does not exclude the possibility of Zolpidem as the primary cause of the change of her altered mental status or further exacerbating the change in her mental status. Though Zolpidem can be therapeutic and safe, we as clinicians have to be aware of the potential side effects of Zolpidem when prescribing medications.

None Declared

Workplace sugar-sweetened beverage (SSB) sales bans can reduce SSB consumption. Because stress and anxiety can promote sugar consumption, we examined whether anxiety among hospital employees during the COVID-19 pandemic was associated with changes in SSB consumption and explored whether this relationship varied by exposure to a workplace SSB sales ban.

In a prospective, controlled trial of workplace SSB sales bans, we examined self-reported anxiety (generalised anxiety disorder-7) and self-reported SSB consumption (fluid ounces/d) before (July 2019) and during (May 2020) the COVID-19 pandemic.

Hospital sites in two conditions (four with SSB sales bans and three without sales bans) in Northern California.

We sampled 580 participants (hospital employees) from a larger trial of sales bans; all were regular consumers of SSB (minimum 3/week at main trial enrollment). This subsample was chosen based on having appropriately timed data for our study questions.

Across conditions, participants reduced SSB consumption over the study period. However, participants with higher pandemic-era anxiety scores experienced smaller reductions in SSB consumption after 9 months compared with those with lower anxiety scores (β = 0·65, P < 0·05). When the sample was disaggregated by sales ban condition, this relationship held for participants in the control group (access to SSB at work, β = 0·82, P < 0·05), but not for those exposed to an SSB sales ban (β = 0·42, P = 0·25).

SSB sales bans likely reduce SSB consumption through multiple pathways; buffering stress-related consumption may be one mechanism.

We reviewed outcomes in all 36 consecutive children <5 kg supported with the Berlin Heart pulsatile ventricular assist device at the University of Florida, comparing those with acquired heart disease (n = 8) to those with congenital heart disease (CHD) (n = 28).

The primary outcome was mortality. The Kaplan-Meier method and log-rank tests were used to assess group differences in long-term survival after ventricular assist device insertion. T-tests using estimated survival proportions were used to compare groups at specific time points.

Of 82 patients supported with the Berlin Heart at our institution, 49 (49/82 = 59.76%) weighed <10 kg and 36 (36/82 = 43.90%) weighed <5 kg. Of 36 patients <5 kg, 26 (26/36 = 72.22%) were successfully bridged to transplantation. (The duration of support with ventricular assist device for these 36 patients <5 kg was [days]: median = 109, range = 4–305.) Eight out of 36 patients <5 kg had acquired heart disease, and all eight [8/8 = 100%] were successfully bridged to transplantation. (The duration of support with ventricular assist device for these 8 patients <5 kg with acquired heart disease was [days]: median = 50, range = 9–130.) Twenty-eight of 36 patients <5 kg had congenital heart disease. Eighteen of these 28 [64.3%] were successfully bridged to transplantation. (The duration of support with ventricular assist device for these 28 patients <5 kg with congenital heart disease was [days]: median = 136, range = 4–305.) For all 36 patients who weighed <5 kg: 1-year survival estimate after ventricular assist device insertion = 62.7% (95% confidence interval = 48.5–81.2%) and 5-year survival estimate after ventricular assist device insertion = 58.5% (95% confidence interval = 43.8–78.3%). One-year survival after ventricular assist device insertion = 87.5% (95% confidence interval = 67.3–99.9%) in acquired heart disease and 55.6% (95% confidence interval = 39.5–78.2%) in CHD, P = 0.036. Five-year survival after ventricular assist device insertion = 87.5% (95% confidence interval = 67.3–99.9%) in acquired heart disease and 48.6% (95% confidence interval = 31.6–74.8%) in CHD, P = 0.014.

Pulsatile ventricular assist device facilitates bridge to transplantation in neonates and infants weighing <5 kg; however, survival after ventricular assist device insertion in these small patients is less in those with CHD in comparison to those with acquired heart disease.

Carbapenem-resistant Enterobacterales (CRE) infections are a public health threat due to the risk of transmission between patients and high associated mortality. We sought to identify risk factors for mortality in patients with invasive CRE infections and to specifically evaluate whether there was an association between indwelling medical devices and 90-day mortality.

Retrospective observational cohort study of patients infected with CRE in the eight-county metropolitan Atlanta area between 2012 and 2019.

Patients with invasive CRE infections were identified via the Georgia Emerging Infections Program’s active, population- and laboratory-based surveillance system and linked with the Georgia Vital Statistics database. We used bivariate analysis to identify risk factors for mortality and completed log binomial multivariable regression to estimate risk ratios (RR) for the association between indwelling devices and mortality.

In total, 154 invasive CRE infections were identified, with indwelling devices present in most patients (87.7%) around the time of infection. Admission to an intensive care unit was found to be associated with 90-day mortality (adjusted RR [aRR] 1.55, 95% CI 1.07, 2.24); however, the presence of any indwelling device was not associated with increased risk of 90-day mortality in multivariable analysis (aRR 1.22, 95% CI 0.55, 2.73). Having at least two indwelling devices was associated with increased mortality (aRR 1.79, 95% CI 1.05, 3.05).

Indwelling devices were prevalent in our cohort but were not consistently associated with an increased risk of mortality. Further studies are needed to examine this relationship and the role of device removal.

Sleep has been shown to directly impact cognitive function throughout the lifespan; good quality sleep benefits and improves cognitive function, including processing speed and attention, while poor quality sleep can contribute to negative cognitive outcomes1. In particular, attention, learning, and memory have been demonstrated to be sensitive to sleeping changes, including fragmentation and restriction2. Subjective sleeping scales are utilized in both research and clinical practice, allowing sleep to be measured via self-report on various domains, including duration and factors that can contribute to sleep disruption and disturbances3. This study aims to examine the possible relation between subjective sleep quality and cognitive function among middle-aged adults to inform future research for early interventions of modifiable behaviors that can contribute to abnormal cognitive decline.

Data for this analysis is part of the preliminary results of an ongoing pilot study. 29 middle-aged (40-65 years, inclusive), cognitively unimpaired individuals were recruited from the community. Subjective sleep quality was measured with the Pittsburgh Sleep Quality Index (PSQI). Attention and memory were measured using the California Verbal Learning Test, Third Edition (CVLT-III).

Multiple hierarchical regression analyses were conducted to evaluate if aspects of sleep quality were significantly correlated to complex attention and learning performance in this sample. First, correlation amylases showed significant relationships between PSQI Component 6 (Use of Sleeping Medication) and Trials 1 to 2 Learning Slope (R2 = -0.56, p =0.002) and CVLT-III Trials 1 through 5 Recall Discriminability (R2 = -0.42, p = 0.02), each with significant regression analyses outcomes (b =0.42, p = 0.04 and b = -0.46, p = 0.04, respectively). There were other variables that were found to be significantly correlated; however, after adjusting for relevant demographic variables (age, education, sex), the hierarchical regression analyses revealed no association between the aforementioned variables.

While multiple aspects of sleep quality were expected to influence measures of attention and learning, only PSQI Component 6 was found to be statistically significantly associated with only two learning variables. Limitations of this study included a small sample size which was limited to cognitive and relatively physically healthy middle-aged adults. Further, sleep quality was measured with one subjective measure and no objective data was collected to support the hypotheses. Future analysis is needed to continue to explore the relation between subjective sleep quality and cognitive outcomes. As this is an ongoing study, we look forward to exploring this research question in more detail as the study progresses.

Previous research has found that measures of premorbid intellectual functioning may be predictive of performance on memory tasks among older adults (Duff, 2010). Intellectual functioning itself is correlated with education. The purpose of this study was to investigate the incremental validity of a measure of premorbid intellectual functioning over education levels to predict performance on the Virtual Environment Grocery Store (VEGS), which involves a simulated shopping experience assessing learning, memory, and executive functioning.

Older adults (N = 118, 60.2% female, age 60-90, M = 73.51, SD = 7.46) completed the Wechsler Test of Adult Reading and the VEGS.

WTAR and education level explained 9.4% of the variance in VEGS long delay free recall, F = 5.97, p = 0.003). WTAR was a significant predictor (ß = 0.25, p = 0.006), while level of education was not.

These results suggest that crystalized intelligence may benefit recall on a virtual reality shopping task.

The purpose of this study was to explore overall recovery time and post-concussive symptoms (PCSS) of pediatric concussion patients who were referred to a specialty concussion clinic after enduring a protracted recovery (>28 days). This included patients who self-deferred care or received management from another provider until recovery became complicated. It was hypothesized that protracted recovery patients, who initiated care within a specialty concussion clinic, would have similar recovery outcomes as typical acute injury concussion patients (i.e., within 3 weeks).

Retrospective data were gathered from electronic medical records of concussion patients aged 6-19 years. Demographic data were examined based on age, gender, race, concussion history, and comorbid psychiatric diagnosis. Concussion injury data included days from injury to initial clinic visit, total visits, PCSS scores, days from injury to recovery, and days from initiating care with a specialty clinic to recovery. All participants were provided standard return-to-learn and return-to-play protocols, aerobic exercise recommendations, behavioral health recommendations, personalized vestibular/ocular motor rehabilitation exercises, and psychoeducation on the expected recovery trajectory of concussion.

52 patients were included in this exploratory analysis (Mean age 14.6, SD ±2.7; 57.7% female; 55.7% White, 21.2% Black or African American, 21.2% Hispanic). Two percent of our sample did not disclose their race or ethnicity. Prior concussion history was present in 36.5% of patients and 23.1% had a comorbid psychiatric diagnosis. The patient referral distribution included emergency departments (36%), local pediatricians (26%), neurologists (10%), other concussion clinics (4%), and self-referrals (24%).

Given the nature of our specialty concussion clinic sample, the data was not normally distributed and more likely to be skewed by outliers. As such, the median value and interquartile range were used to describe the results. Regarding recovery variables, the median days to clinic from initial injury was 50.0 (IQR=33.5-75.5) days, the median PCSS score at initial visit was 26.0 (IQR=10.0-53.0), and the median overall recovery time was 81.0 (IQR=57.0-143.3) days.

After initiating care within our specialty concussion clinic, the median recovery time was 21.0 (IQR=14.0-58.0) additional days, the median total visits were 2.0 (IQR=2.0-3.0), and the median PCSS score at follow-up visit was 7.0 (IQR=1-17.3).

Research has shown that early referral to specialty concussion clinics may reduce recovery time and the risk of protracted recovery. Our results extend these findings to suggest that patients with protracted recovery returned to baseline similarly to those with an acute concussion injury after initiating specialty clinic care. This may be due to the vast number of resources within specialty concussion clinics including tailored return-to-learn and return-to-play protocols, rehabilitation recommendations consistent with research, and home exercises that supplement recovery. Future studies should compare outcomes of protracted recovery patients receiving care from a specialty concussion clinic against those who sought other forms of treatment. Further, evaluating the influence of comorbid factors (e.g., psychiatric and/or concussion history) on pediatric concussion recovery trajectories may be useful for future research.

To determine whether residing in a hospital bed that previously held an occupant with Clostridioides difficile increases the risk of hospital-onset C. difficile infection (HO-CDI).

In this retrospective cohort study, we used a real-time location system to track the movement of hospital beds in 2 academic hospitals from April 2018 to August 2019. We abstracted patient demographics, clinical characteristics, and C. difficile polymerase chain reaction (PCR) results from the medical record. We defined patients as being exposed to a potentially “contaminated” bed or room if, within the preceding 7 days from their HO-CDI diagnosis, they resided in a bed or room respectively, that held an occupant with C. difficile in the previous 90 days. We used multivariable logistic regression to determine whether residing in a contaminated bed was associated with HO-CDI after controlling for time at risk and requiring intensive care. We assessed mediation and interaction from a contaminated hospital room.

Of 25,032 hospital encounters with 18,860 unique patients, we identified 237 cases of HO-CDI. Exposure to a contaminated bed was associated with HO-CDI in unadjusted analyses (odds ratio [OR], 1.8; 95% confidence interval [CI], 1.4–2.31) and adjusted analyses (OR, 1.5; 95% CI, 1.2–2.0). Most of this effect was due to both mediation from and interaction with a contaminated hospital room.

Residing in a hospital bed or room that previously had a patient with C. difficile increases the risk of HO-CDI. Increased attention to cleaning and disinfecting the healthcare environment may reduce hospital transmission of C. difficile.