Recent publications
Insomnia is prevalent among patients with alcohol use disorder (AUD), potentially undermining treatment and increasing the risk of relapse. Cognitive behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for insomnia, but its efficacy is not well-characterized in patients across the spectrum of AUD. The aim of this meta-analysis was to quantify the effectiveness of CBT-I in improving insomnia severity and alcohol-related outcomes in adults with heavy alcohol use and/or varying levels of AUD severity and comorbid insomnia. MEDLINE, Cochrane Library, PsycINFO and ClinicalTrials.gov were systematically searched (up to February 2024) to retrieve randomized controlled trials (RCTs). Multilevel meta-analyses were conducted to estimate mean differences over time in insomnia severity, measured using the Insomnia Severity Index (ISI), as well as in alcohol craving and alcohol-related psychosocial problems between CBT-I and control groups. For the number of heavy-drinking/abstinent days, incidence rate ratios were estimated. Risk of bias was assessed using the Risk of Bias 2 (RoB 2) tool. Eight RCTs encompassing 426 adults (68.78 % men) were included. Compared with control conditions, CBT-I resulted in a large reduction of insomnia severity post-treatment [estimated ISI reduction = -5.51, 95% CI (-7.13 to -3.90)], which was maintained at 1-to-3-month [7 studies; estimate = -4.39, 95% CI (-6.08 to -2.70)], and 6-month follow-up [4 studies; estimate = -4.55, 95% CI (-6.77 to -2.33)]. Alcohol-related outcomes were reported less consistently, and no significant differences were found. The included trials were judged to have a low or moderate overall risk of bias for the assessment of all outcomes. CBT-I effectively reduces insomnia severity across the spectrum of AUD, supporting wide implementation in AUD prevention and treatment settings. PROSPERO registration number: CRD42023464612.
Polymer-coated controlled-release fertilizers (PC-CRFs) are valued for nutrient efficiency, but concerns remain about the long-term impacts of their plastic coatings on soil health. This study investigates the physicochemical characteristics of two commercially available PC-CRFs, type A and B, and their changes during nutrient release. Accelerated nutrient release experiments were conducted for 25 d in ultrapure water (free water) and saturated soil with five wet-dry cycles. Total phosphorus and total nitrogen release were measured, with lower concentrations found in soil column effluent compared to water. Additionally, studying microplastic (MP) release from type A PC-CRFs during nutrient release showed that a significantly greater number of MPs were released in the soil column than in water. The results also indicated a preferential migration of smaller MPs to the deeper layers of the soil column. Microscopic pores and cracks were observed through surface morphology analysis, likely caused by osmotic pressure during nutrient release, potentially contributing to MP generation. Mechanical degradation of the type A PC-CRF microcapsules was assessed through surface wear and shear tests to simulate the forces exerted by soil particles and agricultural machinery. Our results showed that longer surface wear duration increased the number of generated MPs, while higher loading in surface wear experiments resulted in a larger median diameter of the MPs.
- Selin Manoj Kumar
- Sathishkumar Munusamy
- Saravanan Enbanathan
- [...]
- Kulathu Iyer Sathiyanarayanan
A new phenanthridine appended quinoline-based chemoreceptor 5-(5-(quinolin-8-yl)thiophen-2-yl)-tetrahydrodibenzo[a,i]phenanthridine (PHQBA) was successfully synthesized and characterized by ¹H, ¹³C, and HRMS spectral analyses. The promising chelation-induced process in PHQBA was accelerated by Th⁴⁺ ions, which impart robust ratiometric green fluorescence at 515 nm. The host–guest complex formed in a 1 : 1 binding stoichiometry between Th⁴⁺ ions and PHQBA was demonstrated by Jobs plot experiments. The Benesi–Hildebrand (BH) plot was employed to compute the binding constant for the complexation of PHQBA + Th⁴⁺, which was determined to be 3.77 × 10⁵ M⁻¹. To comprehend the detection mechanism of PHQBA, DFT, and TDDFT, eased computational studies were conducted and well supported by the experimental results. Moreover, the limit of detection (LOD) of PHQBA was determined as 223 nM, which defines the remarkable optical sensitivity of the sensor PHQBA. Further, portable paper strip detection and real-time determination of Th⁴⁺ ions in real water samples ensure the practical applications of PHQBA.
Antiretroviral therapy (ART) is effective in reducing HIV transmission and mortality, yet daily adherence remains a challenge for many people with HIV (PWH). Suboptimal adherence can lead to virological failure and increased mortality, particularly among those with substance use disorders, such as cocaine use disorder (CUD). The Information-Motivation-Behavioral (IMB) skills model offers a framework to understand and enhance ART adherence by addressing individual and social barriers. In this study, we tested the IMB skills model among 80 cocaine-using PWH currently on ART, and found that behavioral skills significantly predicted adherence. In the extension of the IMB skills model, the addition of practical barriers altered the relationship by showing that motivational barriers such as treatment fatigue and practical barriers significantly affected ART adherence. The findings suggest that for PWH with substance use disorders, addressing practical barriers and motivational factors may be crucial for improving ART adherence, in addition to building behavioral skills.
Purpose of Review
Attention-Deficit Hyperactivity Disorder (ADHD) is a complex neuropsychiatric condition characterized by persistent patterns of inattention, hyperactivity, and impulsivity. In adults, ADHD presents unique challenges in its diagnosis and management. This review updates the current landscape of non-pharmacological management of adult ADHD, with a specific focus on geriatric ADHD management.
Recent Findings
Psychotherapy remains the cornerstone of effective treatment for ADHD. Among the therapeutic modalities, Cognitive Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), and Metacognitive Therapy (MCT) have demonstrated considerable success. These therapies require specific adaptations, such as modifying session structure, focusing on adult-specific issues like time management and workplace challenges, and integrating techniques to meet the complex needs of the adult ADHD population. Additionally, support groups and mindfulness practices have shown to be effective, especially within the geriatric group. These methods help in cultivating a sense of community, enhancing coping strategies, and improving mental resilience. Emerging treatments such as hypnotherapy, Transcranial Magnetic Stimulation (TMS), neurofeedback, and dietary supplements are also discussed. While these treatments show potential, they currently require further empirical studies to better establish their effectiveness and optimal application in clinical settings.
Summary
This review emphasizes the importance of a tailored, multifaceted approach to managing adult ADHD through non-pharmacological means. By incorporating a range of therapeutic interventions, clinicians can better address the complex symptomatology and improve the overall quality of life for adults living with ADHD.
When the decision has been made to perform cataract surgery in a glaucoma patient, the options of cataract surgery alone with a microinvasive procedure, or combined with conjunctival involving glaucoma surgery, are available to the surgeon. Trabeculectomy is the glaucoma procedure that has been by history most frequently and for the longest time combined with cataract surgery, to assist in the control of intraocular pressure (IOP). Other combined procedures are discussed elsewhere in the text. As discussed throughout the text, cataract and glaucoma often present in the same patient and are common comorbidities.
Uncontrolled hypertension is a significant US health problem, despite existing effective treatments. This study assessed the impact of variations in patterns of blood pressure data on physician perceptions of hypertension control using different forms of data visualization.
Physicians (N = 57) reviewed eight brief vignettes describing a fictitious patient; each vignette included a graph of the patient’s blood pressure data. We examined how variations in mean systolic blood pressure (SBP), blood pressure standard deviation (SD), and form of visualization (e.g., line graph with raw values or smoothed values only) affected judgments about hypertension control and need for medication change.
Smoothing successfully reduced visual noise for the physicians. For controlled hypertension, physician judgments were more consistent with clinical guidelines when using the smoothed graph compared with the raw data graph. Judgments about hypertension control with the smoothed graph were similar to judgments made using the raw data graph for cases of uncontrolled hypertension.
Data visualization can direct physicians to attend to more clinically meaningful information, thereby improving their judgments of hypertension control.
Importance
The profile of gastrointestinal (GI) tract outcomes associated with the postacute and chronic phases of COVID-19 in children and adolescents remains unclear.
Objective
To investigate the risks of GI tract symptoms and disorders during the postacute (28-179 days after documented SARS-CoV-2 infection) and the chronic (180-729 days after documented SARS-CoV-2 infection) phases of COVID-19 in the pediatric population.
Design, Setting, and Participants
This retrospective cohort study was performed from March 1, 2020, to September 1, 2023, at 29 US health care institutions. Participants included pediatric patients 18 years or younger with at least 6 months of follow-up. Data analysis was conducted from November 1, 2023, to February 29, 2024.
Exposures
Presence or absence of documented SARS-CoV-2 infection. Documented SARS-CoV-2 infection included positive results of polymerase chain reaction analysis, serological tests, or antigen tests for SARS-CoV-2 or diagnosis codes for COVID-19 and postacute sequelae of SARS-CoV-2.
Main Outcomes and Measures
GI tract symptoms and disorders were identified by diagnostic codes in the postacute and chronic phases following documented SARS-CoV-2 infection. The adjusted risk ratios (ARRs) and 95% CI were determined using a stratified Poisson regression model, with strata computed based on the propensity score.
Results
The cohort consisted of 1 576 933 pediatric patients (mean [SD] age, 7.3 [5.7] years; 820 315 [52.0%] male). Of these, 413 455 patients had documented SARS-CoV-2 infection and 1 163 478 did not; 157 800 (13.6%) of those without documented SARS-CoV-2 infection had a complex chronic condition per the Pediatric Medical Complexity Algorithm. Patients with a documented SARS-CoV-2 infection had an increased risk of developing at least 1 GI tract symptom or disorder in both the postacute (8.64% vs 6.85%; ARR, 1.25; 95% CI, 1.24-1.27) and chronic (12.60% vs 9.47%; ARR, 1.28; 95% CI, 1.26-1.30) phases compared with patients without a documented infection. Specifically, the risk of abdominal pain was higher in COVID-19–positive patients during the postacute (2.54% vs 2.06%; ARR, 1.14; 95% CI, 1.11-1.17) and chronic (4.57% vs 3.40%; ARR, 1.24; 95% CI, 1.22-1.27) phases.
Conclusions and Relevance
In this cohort study, the increased risk of GI tract symptoms and disorders was associated with the documented SARS-CoV-2 infection in children or adolescents during the postacute or chronic phase. Clinicians should note that lingering GI tract symptoms may be more common in children after documented SARS-CoV-2 infection than in those without documented infection.
Early prediction of hematoma expansion (HE) following nontraumatic intracerebral hemorrhage (ICH) may inform preemptive therapeutic interventions. We sought to identify how accurately machine learning (ML) radiomics models predict HE compared with expert clinicians using head computed tomography (HCT).
We used data from 900 study participants with ICH enrolled in the Antihypertensive Treatment of Acute Cerebral Hemorrhage 2 Study. ML models were developed using baseline HCT images, as well as admission clinical data in a training cohort (n = 621), and their performance was evaluated in an independent test cohort (n = 279) to predict HE (defined as HE by 33% or > 6 mL at 24 h). We simultaneously surveyed expert clinicians and asked them to predict HE using the same initial HCT images and clinical data. Area under the receiver operating characteristic curve (AUC) were compared between clinician predictions, ML models using radiomic data only (a random forest classifier and a deep learning imaging model) and ML models using both radiomic and clinical data (three random forest classifier models using different feature combinations). Kappa values comparing interrater reliability among expert clinicians were calculated. The best performing model was compared with clinical predication.
The AUC for expert clinician prediction of HE was 0.591, with a kappa of 0.156 for interrater variability, compared with ML models using radiomic data only (a deep learning model using image input, AUC 0.680) and using both radiomic and clinical data (a random forest model, AUC 0.677). The intraclass correlation coefficient for clinical judgment and the best performing ML model was 0.47 (95% confidence interval 0.23–0.75).
We introduced supervised ML algorithms demonstrating that HE prediction may outperform practicing clinicians. Despite overall moderate AUCs, our results set a new relative benchmark for performance in these tasks that even expert clinicians find challenging. These results emphasize the need for continued improvements and further enhanced clinical decision support to optimally manage patients with ICH.
Bovine fascioliasis, a parasitic disease caused by Fasciola species, severely affects cattle health and agricultural productivity in tropical regions like Nigeria. It leads to economic losses through liver condemnations, decreased meat and milk production, and increased veterinary expenses. Despite its public health and economic significance, existing data on its prevalence and epidemiological patterns in Nigeria is limited.
This systematic review and meta-analysis compiled findings from 40 studies conducted between 1980 and 2024 to evaluate the prevalence and distribution of bovine fascioliasis in Nigeria.
The analysis included 5,174,019 cattle and identified 120,678 infections, with a pooled prevalence of 29% (95% CI: 0.21, 0.38) using a random-effects model. A high level of heterogeneity was noted (I² = 100%, tau² = 0.0893). Subgroup analyses showed a higher prevalence in cross-sectional studies (33%, 95% CI: 0.25–0.42) compared to retrospective studies (18%, 95% CI: 0.04, 0.40). Diagnostic methods notably impacted prevalence estimates, with serological tests reporting 72%, versus 33% for microscopy and 22% for post-mortem examinations. Regional disparities were also evident, with the South-South zone exhibiting the highest prevalence in the country, underscoring the influence of environmental factors.
This study reveals the significant burden of bovine fascioliasis in Nigeria and highlights the need for region-specific, evidence-based control strategies. The findings also point to critical gaps in diagnostic standardization and surveillance, underscoring the necessity for improved diagnostic tools and integrated management practices to alleviate the effects of this parasitic disease.
Computational thinking (CT) is becoming increasingly important for K‐12 science education, thus warranting new integrations of CT and science content. This intervention study integrated CT through unplugged, or handwritten, algorithmic explanations of natural selection. As students investigated natural selection in varying contexts (specific and context‐general), students created explanations based on evidence of natural selection by using algorithm concepts and engaging in CT practices. Students' CT learning over time was analyzed through algorithmic explanations created during the unit. Research questions guiding the investigation were: (1) How do students learn CT over the course of a CT and science integrated unit? (2) What are students' perspectives of learning CT in an integrated unit? (3) How do students come to think about CT and its applications? Students' CT competencies significantly increased from pre‐ to post‐unit. Students indicated creating algorithmic explanations helped them learn natural selection and develop CT competencies. At the end of the unit, students recognized the universal application of CT as a way to logically and clearly explain processes. Implications of this work are that CT can be used as a science practice that helps students simultaneously learn science and CT practice competencies. Moreover, these student learning outcomes can be achieved with unplugged, or computer‐free, CT.
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