Category: Nevin Manimala

Obstet Gynecol. 2023 Jun 1;141(6):1163-1170. doi: 10.1097/AOG.0000000000005197. Epub 2023 May 3.

ABSTRACT

OBJECTIVE: To use administrative claims data to evaluate the association of a remote blood pressure monitoring program with adverse postpartum clinical outcomes in patients with a hypertensive disorder of pregnancy.

METHODS: This was a retrospective cohort study of Independence Blue Cross members with a hypertensive disorder of pregnancy diagnosis across three obstetric hospitals from 2017 to 2021. Patients who were enrolled in twice-daily text-based blood pressure monitoring for 10 days postpartum were compared with two propensity-score matched cohorts of patients who met the program criteria: an asynchronous cohort (cohort A), consisting of patients at any of the three participating hospitals before remote monitoring program implementation, and a contemporaneous cohort (cohort C), consisting of patients at other hospitals during the same time period as clinical use of the program. Patients with less than 16 months of continuous insurance enrollment before delivery were excluded. Claims for adverse clinical outcomes after delivery discharge were evaluated. Health care service utilization and total medical costs were evaluated.

RESULTS: The 1,700 patients in remote blood pressure monitoring program were matched to 1,021 patients in cohort A and 1,276 in cohort C. Within the first 6 months after delivery, patients enrolled in remote monitoring were less likely to have the composite adverse outcome than those in cohort A (2.9% vs 4.7%; OR 0.61, 95% CI 0.40-0.98). There was no statistically significant difference relative to cohort C (3.2% vs 4.5%; OR 0.71, 95% CI 0.47-1.07). The remote monitoring group had more cardiology visits and fewer postnatal emergency department (ED) visits and readmissions compared with both comparison cohorts. Reductions in ED visits and readmissions drove overall lower total medical costs for the program cohort.

CONCLUSION: Patients enrolled in a remote blood pressure monitoring program were less likely to experience an adverse outcome in the first 6 months after delivery. Reductions in ED visits and readmissions resulted in lower postpartum total medical costs compared with both control cohorts. Broad implementation of evidence-based remote monitoring programs may reduce postpartum adverse outcomes, thereby reducing morbidity and mortality in populations such as the one studied here.

PMID:37486653 | DOI:10.1097/AOG.0000000000005197

JAMA Netw Open. 2023 Jul 3;6(7):e2324389. doi: 10.1001/jamanetworkopen.2023.24389.

ABSTRACT

IMPORTANCE: Mental health among children and adolescents is a critical public health issue, and transgender and gender nonbinary youths are at an even greater risk. Social media has been consistently associated with youth mental health, but little is known about how gender identity interacts with this association.

OBJECTIVE: To use a risk and resilience approach to examine the association between social media use and mental health among transgender, gender nonbinary, and cisgender youths.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study analyzed data collected from an online survey between May and August 2021. Participants included a random sample of US youths; eligibility requirements included being aged 10 to 17 years and residing in the US. Statistical analysis was performed from February to April 2022.

MAIN OUTCOMES AND MEASURES: Social media use (time, type of use, favorite site, social comparisons, mindfulness, taking intentional breaks, cleaning and curating feeds, problematic use, and media literacy programs at their school) and mental health (depression, emotional problems, conduct problems, and body image) as main outcomes.

RESULTS: Participants included 1231 youths aged 10 to 17 years from a national quota sample from the United States; 675 (54.8%) identified as cisgender female, 479 (38.9%) as cisgender male, and 77 (6.3%) as transgender, gender nonbinary, or other; 4 (0.3%) identified as American Indian or Alaska Native, 111 (9.0%) as Asian, 185 (15.0%) as Black, 186 (15.1%) as Hispanic or Latinx, 1 (0.1%) as Pacific Islander, 703 (57.1%) as White, and 41 (3.3%) as mixed and/or another race or ethnicity. Gender identity moderated both the strength and the direction of multiple associations between social media practices and mental health: active social media use (eg, emotional problems: B = 1.82; 95% CI, 0.16 to 3.49; P = .03), cleaning and/or curating social media feeds (eg, depression: B = -0.91; 95% CI, -1.98 to -0.09; P = .03), and taking intentional breaks (eg, depression: B = 1.03; 95% CI, 0.14 to 1.92; P = .02).

CONCLUSIONS AND RELEVANCE: In this cross-sectional study of gender identity, social media, and mental health, gender identity was associated with youths’ experiences of social media in ways that may have distinct implications for mental health. These results suggest that research about social media effects on youths should attend to gender identity; directing children and adolescents to spend less time on social media may backfire for those transgender and gender nonbinary youths who are intentional about creating safe spaces on social media that may not exist in their offline world.

PMID:37486631 | DOI:10.1001/jamanetworkopen.2023.24389

JAMA Netw Open. 2023 Jul 3;6(7):e2325158. doi: 10.1001/jamanetworkopen.2023.25158.

ABSTRACT

IMPORTANCE: Soft drink consumption is associated with weight gain in children and adolescents, but little is known about the association between soft drink consumption and prevalence of the overweight and obesity in adolescents.

OBJECTIVE: To investigate the association of soft drink consumption with overweight and obesity in adolescents enrolled in school (hereafter, school-going adolescents) using country-level and individual-level data.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from 3 cross-sectional studies including 107 countries and regions that participated in the Global School-Based Student Health Survey (2009-2017), the European Health Behavior in School-Aged Children study (2017-2018), and the US Youth Risk Behavior Survey (2019).

EXPOSURE: Daily soft drink consumption (consuming soft drinks 1 or more times per day or not).

MAIN OUTCOME AND MEASURE: Overweight and obesity defined by the World Health Organization Growth Reference Data.

RESULTS: Among the 107 countries and regions, 65 were low- and middle-income, and 42 were high-income countries and regions, with a total of 405 528 school-going adolescents (mean [SD] age, 14.2 [1.7] years; 196 147 [48.4%] males). The prevalence of overweight and obesity among adolescent students varied from 3.3% (95% CI, 2.6 to 4.1) in Cambodia to 64.0% (95% CI, 57.0 to 71.6) in Niue, and the prevalence of adolescent students consuming soft drinks 1 or more times per day varied from 3.3% (95% CI, 2.9 to 3.7) in Iceland to 79.6% (95% CI, 74.0 to 85.3) in Niue. There was a positive correlation between the prevalence of daily soft drink consumption and the prevalence of overweight and obesity (R, 0.44; P < .001). The pooled analysis using individual-level data also showed a statistically significant association between daily soft drink consumption and overweight and obesity (daily soft drink consumption vs nondaily soft drink consumption), with an odds ratio of 1.14 (95% CI, 1.08 to 1.21) among school-going adolescents.

CONCLUSIONS AND RELEVANCE: In this study of 107 countries and regions, the prevalence of daily consumption of soft drinks was associated with the prevalence of overweight and obesity among adolescent students. Our results, in conjunction with other evidence, suggest that reducing soft drink consumption should be a priority in combating adolescent overweight and obesity.

PMID:37486630 | DOI:10.1001/jamanetworkopen.2023.25158

Br J Radiol. 2023 Jul 24:20230292. doi: 10.1259/bjr.20230292. Online ahead of print.

ABSTRACT

Image reconstruction for positron emission tomography (PET) has been developed over many decades, with advances coming from improved modelling of the data statistics and improved modelling of the imaging physics. However, high noise and limited spatial resolution have remained issues in PET imaging, and state-of-the-art PET reconstruction has started to exploit other medical imaging modalities (such as MRI) to assist in noise reduction and enhancement of PET’s spatial resolution. Nonetheless, there is an ongoing drive towards not only improving image quality, but also reducing the injected radiation dose and reducing scanning times. While the arrival of new PET scanners (such as total body PET) is helping, there is always a need to improve reconstructed image quality due to the time and count limited imaging conditions. Artificial intelligence (AI) methods are now at the frontier of research for PET image reconstruction. While AI can learn the imaging physics as well as the noise in the data (when given sufficient examples), one of the most common uses of AI arises from exploiting databases of high-quality reference examples, to provide advanced noise compensation and resolution recovery. There are three main AI reconstruction approaches: i) direct data-driven AI methods which rely on supervised learning from reference data, ii) iterative (unrolled) methods which combine our physics and statistical models with AI learning from data, and iii) methods which exploit AI with our known models, but crucially can offer benefits even in the absence of any example training data whatsoever. This article reviews these methods, considering opportunities and challenges of AI for PET reconstruction.

PMID:37486607 | DOI:10.1259/bjr.20230292

Acta Biomed. 2023 Jul 24;94(S1):e2023205. doi: 10.23750/abm.v94iS1.14198.

ABSTRACT

Talar body fractures are uncommon fractures of the foot and its management results to be very hard due to retrograde vascularization and wide articular cartilage coverage of talar surface, which could easily lead to poor functional outcomes, avascular osteonecrosis and early post traumatic arthritis. We describe a case of displaced, vertical, talar body fracture in a 41-year-old patient treated with reduction and fixation by talar anteromedial approach coupled to medial malleolar osteotomy to better expose the fracture. Our literature review has found few studies, in addition with a low level of statistical evidence. We advocate for more studies with a bigger sample and with a design of randomized control trials.

PMID:37486598 | DOI:10.23750/abm.v94iS1.14198

Metabolomics. 2023 Jul 24;19(8):68. doi: 10.1007/s11306-023-02032-8.

ABSTRACT

INTRODUCTION: Lantana trifolia L. (Verbenaceae) is a shrubby plant. In folk medicine, its leaves are used in the form of infusions and syrups to treat angina, coughs, and colds; they are also applied as tranquilizer. Previous studies have reported the antimicrobial potential of the compounds present in L. trifolia leaves.

OBJECTIVES: To report the anti-Candida activities of the fractions obtained from the fruits and leaves of two L. trifolia specimens.

METHODS: The L. trifolia fractions were submitted to UFLC-DAD-(+)-ESI-MS/MS, and the data were analyzed by using multivariate statistical tools (PCA, PLS-DA) and spectral similarity analyses based on molecular networking, which aided dereplication of the bioactive compounds. Additionally, NMR analyses were performed to confirm the chemical structure of some of the major compounds in the fractions.

RESULTS: The ethyl acetate fractions presented MIC values lower than 100 µg mL^-1 against the three Candida strains evaluated herein (C. albicans, C. tropicalis, and C. glabrata). Fractions FrPo AcOEt, FrPe AcOEt, and FrPe nBut had MIC values of 1.46, 2.93, and 2.93 µg mL^-1 against C. glabrata, respectively. These values resembled the MIC value of amphotericin B, the positive control (0.5-1.0 µg mL^-1), against this same strain. Cytotoxicity was measured and used to calculate the selectivity index.

CONCLUSION: On the basis of our data, the most active fractions in the antifungal assay were more selective against C. glabrata than against non-infected cells. The analytical approach adopted here allowed us to annotate 29 compounds, nine of which were bioactive (PLS-DA results) and belong to the class of phenolic compounds.

PMID:37486581 | DOI:10.1007/s11306-023-02032-8

J Patient Rep Outcomes. 2023 Jul 24;7(1):77. doi: 10.1186/s41687-023-00616-5.

ABSTRACT

BACKGROUND: Longitudinal estimates of long COVID burden during Omicron remain limited. This study characterized long-term impacts of COVID-19 and booster vaccination on symptoms, Health-Related Quality of Life (HRQoL), and Work Productivity Activity Impairment (WPAI).

METHODS: Outpatients with ≥ 1 self-reported symptom and positive SARS-CoV-2 test at CVS Health United States test sites were recruited between 01/31 and 04/30/2022. Symptoms, EQ-5D and WPAI were collected via online surveys until 6 months following infection. Both observed and model-based estimates were analyzed. Effect sizes based on Cohen’s d quantified the magnitude of outcome changes over time, within and between vaccination groups. Mixed models for repeated measures were conducted for multivariable analyses, adjusting for covariates. Logistic regression assessed odds ratio (OR) of long COVID between vaccination groups.

RESULTS: At long COVID start (Week 4), 328 participants included 87 (27%) Boosted with BNT162b2, 86 (26%) with a BNT162b2 primary series (Primed), and 155 (47%) Unvaccinated. Mean age was 42.0 years, 73.8% were female, 26.5% had ≥ 1 comorbidity, 36.9% prior infection, and 39.6% reported ≥ 3 symptoms (mean: 3.1 symptoms). At Month 6, among 260 participants, Boosted reported a mean of 1.1 symptoms versus 3.4 and 2.8 in Unvaccinated and Primed, respectively (p < 0.001). Boosted had reduced risks of ≥ 3 symptoms versus Unvaccinated (observed: OR 0.22, 95% CI 0.10-0.47, p < 0.001; model-based: OR 0.36, 95% CI 0.15-0.87, p = 0.019) and Primed (observed: OR 0.29, 95% CI 0.13-0.67, p = 0.003; model-based: OR 0.59, 95% CI 0.21-1.65, p = 0.459). Results were consistent using ≥ 2 symptoms. Regarding HRQoL, among those with long COVID, Boosted had higher EQ-5D Utility Index (UI) than Unvaccinated (observed: 0.922 vs. 0.731, p = 0.014; model-based: 0.910 vs. 0.758, p-value = 0.038) and Primed (0.922 vs. 0.648, p = 0.014; model-based: 0.910 vs. 0.708, p-value = 0.008). Observed and model-based estimates for EQ-VAS and UI among Boosted were comparable with pre-COVID since Month 3. Subjects vaccinated generally reported better WPAI scores.

CONCLUSIONS: Long COVID negatively impacted HRQoL and WPAI. The BNT162b2 booster could have a beneficial effect in reducing the risk and burden of long COVID. Boosted participants reported fewer and less durable symptoms, which contributed to improve HRQoL and maintain WPAI levels. Limitations included self-reported data and small sample size for WPAI.

PMID:37486567 | DOI:10.1186/s41687-023-00616-5

Head Neck Pathol. 2023 Jul 24. doi: 10.1007/s12105-023-01570-w. Online ahead of print.

NO ABSTRACT

PMID:37486534 | DOI:10.1007/s12105-023-01570-w

Adv Exp Med Biol. 2023;1424:255-263. doi: 10.1007/978-3-031-31982-2_29.

ABSTRACT

The brain’s temperature measurements (T_B) in patients with severe brain damage are important, in order to offer the optimal treatment. The purpose of this research is the creation of mathematical models for the T_B‘s prediction, based on the temperatures in the bladder (T_BL), femoral artery (T_FA), ear canal (T_ΕC), and axilla (T_A), without the need for placement of intracranial catheter, contributing significantly to the research of the human thermoregulatory system.The research involved 18 patients (13 men and 5 women), who were hospitalized in the adult intensive care units (ICU) of Larissa’s two hospitals, with severe brain injury. An intracranial catheter with a thermistor was used to continuously measure T_B and other parameters. The T_B‘s measurements, and simultaneously one or more of T_BL, T_FA, T_EC, and T_A, were recorded every 1 h.To create T_B predicting models, the data of each measurement was separated into (a) model sample (measurements’ 80%) and (b) validation sample (measurements’ 20%). Multivariate linear regression analysis demonstrated that it is possible to predict brain’s temperature (PrT_B), using independent variables (R₂ was T_BL = 0.73, T_FA = 0.80, T_EC = 0.27, and T_A = 0.17, p < 0.05). Significant linear associations were found, statistically, and no difference in means between T_B and PrT_B of each prediction model. Also, the 95% limits of agreement and the percent coefficient of variation showed sufficient agreement between the T_B and PrT_B in each prediction model.In conclusion, brain’s temperature prediction models based on T_BL, T_FA, T_EC, and T_A were successful. Its determination contributes to the improvement of clinical decision-making.

PMID:37486502 | DOI:10.1007/978-3-031-31982-2_29

Adv Exp Med Biol. 2023;1424:233-240. doi: 10.1007/978-3-031-31982-2_26.

ABSTRACT

In an attempt to develop therapeutic agents to treat Alzheimer’s disease, a series of flavonoid analogues were collected, which already had established acetylcholinesterase (AChE) enzyme inhibition activity. For each molecule we also collected biological activity data (Ki). Then, 3D-QSAR (quantitative structure-activity relationship model) was developed which showed acceptable predictive and descriptive capability as represented by standard statistical parameters r2 and q2. This SAR data can explain the key descriptors which can be related to AChE inhibitory activity. Using the QSAR model, pharmacophores were developed based on which, virtual screening was done and a dataset was obtained which loaded as a prediction set to fit the developed QSAR model. Top 10 compounds fitting the QSAR model were subjected to molecular docking. CHEMBL1718051 was found to be the lead compound. This study is offering an example of a computationally-driven tool for prioritisation and discovery of probable AChE inhibitors. Further, in vivo and in vitro testing will show its therapeutic potential.

PMID:37486499 | DOI:10.1007/978-3-031-31982-2_26