This study analyzes disparities in initial health care responses in Turkey and Syria following the 2023 earthquakes.

Using Humanitarian Data Exchange, Crude Mortality Rates (CMR) and injury rates in both countries were calculated, and temporal trends of death tolls and injuries in the first month post- catastrophe were compared. World Health Organization (WHO) Flash Appeal estimated funding requirements, and ratios of humanitarian aid personnel in Urban Search and Rescue (USAR) teams per population from ReliefWeb and MAPACTION data were used to gauge disparities.

56 051 096 individuals were exposed, with Turkey having 44 million vs 12 million in Syria. Turkey had higher CMR in affected areas (10.5 vs. 5.0 per 10,000), while Syria had higher CMR in intensely seismic regions (9.3 vs. 7.7 per 1,000). Turkey had higher injury rates (24.6 vs. 9.9 per 10 000). Death and injury rates plateaued in Syria after 3 days, but steadily rose in Turkey. Syria allocated more funding for all priorities per population except health care facilities’ rehabilitation. Turkey had 219 USAR teams compared to Syria’s 6, with significantly more humanitarian aid personnel (23 vs. 2/100,000).

Significant disparities in the initial health care response were observed between Turkey and Syria, highlighting the need for policymakers to enhance response capabilities in conflict-affected events to reduce the impact on affected populations.

The 2023 Turkish-Syrian earthquakes, the most devastating in the region since 1939, heightened challenges in Syria’s health care system amid ongoing conflict, disrupting Gaziantep’s humanitarian aid supply route. The initial health care responses post-earthquakes in Turkey and Syria were analyzed through a descriptive study, where Crude Mortality Rates (CMR) and injury rates during the first week were calculated. The World Health Organization’s funding priorities and the ratio of humanitarian aid personnel in Urban Search and Rescue teams per population were assessed. Turkey had 4-fold higher earthquake exposure and experienced higher CMR and injuries per population, while Syria had higher CMR in intensely seismic regions. Temporal trends showed plateaued death and injury rates in Syria within 3 days, while Turkey’s continued to increase. Syria required more funding across nearly all priorities while Turkey had more humanitarian aid personnel per population. Significant health care response disparities were observed, emphasizing the imperative for policymakers to enhance initial responses in conflict-affected events.

To better delineate multiplexed gastrointestinal polymerase chain reaction (PCR) panel (MGPP) diagnostic and therapeutic stewardship for patients undergoing treatment for acute leukemia including indications and benefits of testing, optimal timing, and interpretation of results.

We retrieved all MGPP ordered on 662 consecutive patients admitted with newly diagnosed acute leukemia between June 2015 and May 2024.

Regional referral center for acute leukemia.

Fifty-one (17%) of 305 MGPP obtained on the 198 patients who underwent testing identified at least one and 4 (1%) more than one diarrheagenic pathogen. The probability of a positive result was greater if obtained as an outpatient [20/52(38%)], but was not related to type of leukemia, sex, or age. Among the positive results, the pathogens identified included Clostridioides difficile (78% of tests), norovirus (16%), diarrheagenic Escherichia coli (6%), adenovirus 40/41 (4%), and Giardia lamblia (4%). The results of 30 of the 305 tests resulted in a change in treatment (28 C. difficile, 2 G. lamblia). For the MGPP C. difficile results with an accompanying toxin determination, this included treatment following 16/19 tests with a positive toxin result and 11/19 with a negative. Actionable results other than C. difficile were rarely seen in the inpatient population.

MGPP testing is most useful when administered as an outpatient and of little benefit for inpatients with hospital-onset diarrhea. Since MGPP is sensitive and does not distinguish between colonization and causes of diarrhea, caution is needed in interpretation of results, especially for toxin-negative C. difficile.

The Hierarchical Taxonomy of Psychopathology (HiTOP) offers a promising framework to identify the neurobiological mechanisms of psychopathology. Many forms of psychopathology are characterized by dysfunctional emotional reactivity. The late positive potential (LPP) is an event-related potential component that provides an index of neurobiological emotional reactivity. Several categorical disorders have demonstrated a similar association with the emotion-modulated LPP. It is possible that higher-order dimensional representations of psychopathology might explain the comparable results. The present study examined the association between HiTOP-consistent pathological personality dimensions across multiple levels of the hierarchy and neurobiological emotional reactivity.

The sample included 215 18–35-year-old adults (86% female) who were oversampled for psychopathology. Participants completed the emotional interrupt task while electroencephalography was recorded to examine the LPP. Participants also completed the Comprehensive Assessment of Traits relevant to Personality Disorders to assess pathological personality.

At the spectra level, higher negative emotionality was associated with a larger emotion-modulated LPP, while higher detachment was associated with a smaller emotion-modulated LPP. There were no associations between higher-order psychopathology levels and the emotion-modulated LPP. Compared to categorical diagnoses, spectra-level personality pathology dimensions significantly improved the prediction of the emotion-modulated LPP.

The present study indicates that HiTOP spectra levels of negative emotionality and detachment demonstrate unique associations with neurobiological emotional reactivity. The study highlights the utility of examining dimensional and hierarchical, rather than categorical, representations of psychopathology in the attempt to identify the neurobiological origins of psychopathology.

Viral hemorrhagic fevers (VHFs), such as Ebola virus disease, Marburg virus disease, and Lassa fever, are associated with significant morbidity and mortality and the potential for person-to-person transmission. While most individuals in whom VHF is suspected will ultimately be diagnosed with a non-VHF illness, such patients may present to any United States healthcare facility (HCF) for initial evaluation; therefore, all HCFs must be prepared to evaluate and initiate care for suspect VHF patients, especially if they are acutely ill. Included within this evaluation is the ability to perform basic routine laboratory testing before VHF-specific diagnostic test results are available, as well as rapid malaria testing to assess for a common, dangerous “VHF mimic.”

To improve laboratory preparedness and readiness in the initial care of suspect VHF patients who may present to acute care hospitals.

Plan-Do-Study-Act quality improvement model.

Frontline healthcare facilities and their clinical laboratories.

We describe the development of a laboratory testing toolkit for a suspect VHF patient that can assist frontline HCFs in providing basic laboratory testing required for the care of these patients.

The toolkit provides guidance on infection prevention and control, waste management, occupational health, laboratory test collection, processing, and resulting, in the context of suspect VHF patient evaluation.

The toolkit is designed to be readily adapted by any frontline HCF in the US. With the guidance provided, facilities will be able to support safer initial evaluation of VHF suspects and ensure high-quality patient care.

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.

Individuals diagnosed with autism spectrum disorder (ASD) experience negative self-evaluation, indicated by low levels of self-esteem and describing themselves more negatively to others. Variations in reading comprehension, difficulty identifying emotions, and masking (camouflaging of autistic traits) make it difficult to accurately measure self-evaluation of individuals with ASD using subjective self-report scales such as the Rosenburg Self-Esteem Scale. Therefore, it is important to explore more objective methods of measuring self-evaluation in ASD. Sentiment analysis is a popular Natural Language Processing (NLP) technique used to quantify the emotional content of language programmatically by automatically transforming text into a data frame of words represented as individual values or tokens. Each token can then be categorized as positive or negative with a sentiment dictionary. The current study aims to investigate an automated sentiment analysis approach to evaluate self-evaluation by quantifying implicit linguistic affective valence of ASD participants' verbal self-describing statements in a naturalistic setting. Specifically, we evaluated the frequency of positive or negative words used during a mock job interview in which individuals with ASD were asked to describe themselves. We then examined the relationship between positive and negative word usage and standard self-report measures of self-evaluation.

Twenty-four young adults with ASD were included in this study with an age range of 15-24 and a mean age of 19.2 years. Participants completed a battery of assessments including a mock job interview in which they were asked to describe themselves as a measure of implicit self-esteem. Self-esteem and knowledge of personal strengths was assessed using the Rosenberg Self-Esteem Scale and Strengths Knowledge Scale, respectively. Interview transcripts were automatically transformed into word token data frames using the tidytext package in Rstudio. Frequencies of positive and negative words were calculated and their ratio to total word count was used to measure the implicit positivity and negativity of transcripts.

There was a significant negative correlation between the frequency of negative sentiment in transcripts and measure on the Rosenburg Self-Esteem Scale (r = -.376, p = .035) and the Strengths Knowledge Scale (r = -.387, p = .031) indicating that individuals with higher self-esteem and knowledge of their strengths used fewer negative words when talking during a mock interview.

While our results are preliminary, this pilot study represents the first to use automated sentiment analysis to study self-evaluation in individuals with ASD. The use of this technique on natural linguistic data collected through a mock job interview allows researchers to quantitatively analyze the emotionality of transcriptions and create insights that would otherwise be unavailable using more subjective qualitative techniques. Limited research into self-evaluation in this population has yielded inconsistent results, relying too heavily upon qualitative or self-report measures. The ability to programmatically quantify affective valence in transcripts is a time and cost-effective technique for improving validity of future measures of self-evaluation.

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.