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Nevin Manimala Statistics

Global burden of chronic respiratory diseases and risk factors, 1990-2019: an update from the Global Burden of Disease Study 2019

EClinicalMedicine. 2023 May;59:101936. doi: 10.1016/j.eclinm.2023.101936.

ABSTRACT

BACKGROUND: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019.

METHODS: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input.

FINDINGS: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6-4.3) with a prevalence of 454.6 million cases (417.4-499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4-225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9-3.6) deaths. With 262.4 million (224.1-309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively.

INTERPRETATION: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries.

PMID:37229504 | PMC:PMC7614570 | DOI:10.1016/j.eclinm.2023.101936

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Nevin Manimala Statistics

Optimization of spray dried yogurt and its application to prepare functional cookies

Front Nutr. 2023 May 9;10:1186469. doi: 10.3389/fnut.2023.1186469. eCollection 2023.

ABSTRACT

INTRODUCTION: Spray-dried yogurt powder (SDYP) has shelf stability and other functional properties that improve solubility and facilitate the use, processing, packaging, and transportation of other food derivatives, such as bread and pastries on a large scale. The present research was conducted to develop SDYP and further its utilization to prepare functional cookies.

METHODS: Yogurt was spray-dried by employing different outlet air temperatures (OAT) (65°C, 70°C & 75°C) and inlet air temperature (IAT) (150°C, 155°C & 160°C). Spray drying shows that increasing the temperature increases nutritional loss, whereas S. thermophilus culture shows resistance to the intensive heat approaches. On the other hand L. delbrueckii subsp. Bulgaricus culture was found to be significantly affected. A total of 4 treatments, including one control for the functional cookies development.

RESULTS AND DISCUSSION: A directly proportional relation was investigated between the increasing concentration of SDYP and baking characteristics and cookie’s mineral and protein profile. Bioactive parameters like antioxidant activity of 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH), 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and total phenolic content (TPC) were also affected significantly. The sensory profile shows an incline towards T0 (0% SDYP) to T3 (10% SDYP) in all attributes but starts to decline when the concentration of SDYP reaches 15%. This study suggests that by employing a certain combination of temperatures (OAT: 60°C IAT: 150°C); maximum survival of inoculated culture can be achieved, and this powder can be utilized in the development of functional cookies with enhanced sensory as well as biochemical characteristics significantly (P< 0.05).

PMID:37229469 | PMC:PMC10204867 | DOI:10.3389/fnut.2023.1186469

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Nevin Manimala Statistics

A longitudinal study of fatty acid profiles, macronutrient levels, and plasmin activity in human milk

Front Nutr. 2023 May 9;10:1172613. doi: 10.3389/fnut.2023.1172613. eCollection 2023.

ABSTRACT

INTRODUCTION: Human milk provides nutrients essential for infant growth and health, levels of which are dynamic during lactation.

METHODS: In this study, changes in macronutrients, fatty acids, and plasmin activities over the first six months of lactation in term milk were studied.

RESULTS: There was a significant influence of lactation stage on levels of protein and plasmin activities, but not on levels of fat and carbohydrate in term milk. Concerning fatty acids in term milk, levels of caproic acid and α-linolenic acid increased significantly (p < 0.05), whereas those of arachidonic acid and docosahexaenoic acid decreased, in the six months after birth. Significant impacts of maternal pre-pregnancy BMI and infant gender on fatty acid profiles were also found. Multivariate statistical analysis showed that protein level, plasmin activity, and several fatty acids (α-linolenic acid, lignoceric acid, and docasadienoic acid) contributed strongly to discrimination of milk from different lactational stages.

DISCUSSION: The study demonstrates that not all but some fatty acids were influenced by lactation, whereas protein and protease levels showed clear decreasing trends during lactation, which may help in understanding the nutritional requirements of infants.

PMID:37229467 | PMC:PMC10203173 | DOI:10.3389/fnut.2023.1172613

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Clinical evaluation of a deep learning segmentation model including manual adjustments afterwards for locally advanced breast cancer

Tech Innov Patient Support Radiat Oncol. 2023 May 13;26:100211. doi: 10.1016/j.tipsro.2023.100211. eCollection 2023 Jun.

ABSTRACT

INTRODUCTION: Deep learning (DL) models are increasingly developed for auto-segmentation in radiotherapy. Qualitative analysis is of great importance for clinical implementation, next to quantitative. This study evaluates a DL segmentation model for left- and right-sided locally advanced breast cancer both quantitatively and qualitatively.

METHODS: For each side a DL model was trained, including primary breast CTV (CTVp), lymph node levels 1-4, heart, lungs, humeral head, thyroid and esophagus. For evaluation, both automatic segmentation, including correction of contours when needed, and manual delineation was performed and both processes were timed. Quantitative scoring with dice-similarity coefficient (DSC), 95% Hausdorff Distance (95%HD) and surface DSC (sDSC) was used to compare both the automatic (not-corrected) and corrected contours with the manual contours. Qualitative scoring was performed by five radiotherapy technologists and five radiation oncologists using a 3-point Likert scale.

RESULTS: Time reduction was achieved using auto-segmentation in 95% of the cases, including correction. The time reduction (mean ± std) was 42.4% ± 26.5% and 58.5% ± 19.1% for OARs and CTVs, respectively, corresponding to an absolute mean reduction (hh:mm:ss) of 00:08:51 and 00:25:38. Good quantitative results were achieved before correction, e.g. mean DSC for the right-sided CTVp was 0.92 ± 0.06, whereas correction statistically significantly improved this contour by only 0.02 ± 0.05, respectively. In 92% of the cases, auto-contours were scored as clinically acceptable, with or without corrections.

CONCLUSIONS: A DL segmentation model was trained and was shown to be a time-efficient way to generate clinically acceptable contours for locally advanced breast cancer.

PMID:37229460 | PMC:PMC10205480 | DOI:10.1016/j.tipsro.2023.100211

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Generate Analysis-Ready Data for Real-world Evidence: Tutorial for Harnessing Electronic Health Records With Advanced Informatic Technologies

J Med Internet Res. 2023 May 25;25:e45662. doi: 10.2196/45662.

ABSTRACT

Although randomized controlled trials (RCTs) are the gold standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world data has been vital in postapproval monitoring and is being promoted for the regulatory process of experimental therapies. An emerging source of real-world data is electronic health records (EHRs), which contain detailed information on patient care in both structured (eg, diagnosis codes) and unstructured (eg, clinical notes and images) forms. Despite the granularity of the data available in EHRs, the critical variables required to reliably assess the relationship between a treatment and clinical outcome are challenging to extract. To address this fundamental challenge and accelerate the reliable use of EHRs for RWE, we introduce an integrated data curation and modeling pipeline consisting of 4 modules that leverage recent advances in natural language processing, computational phenotyping, and causal modeling techniques with noisy data. Module 1 consists of techniques for data harmonization. We use natural language processing to recognize clinical variables from RCT design documents and map the extracted variables to EHR features with description matching and knowledge networks. Module 2 then develops techniques for cohort construction using advanced phenotyping algorithms to both identify patients with diseases of interest and define the treatment arms. Module 3 introduces methods for variable curation, including a list of existing tools to extract baseline variables from different sources (eg, codified, free text, and medical imaging) and end points of various types (eg, death, binary, temporal, and numerical). Finally, module 4 presents validation and robust modeling methods, and we propose a strategy to create gold-standard labels for EHR variables of interest to validate data curation quality and perform subsequent causal modeling for RWE. In addition to the workflow proposed in our pipeline, we also develop a reporting guideline for RWE that covers the necessary information to facilitate transparent reporting and reproducibility of results. Moreover, our pipeline is highly data driven, enhancing study data with a rich variety of publicly available information and knowledge sources. We also showcase our pipeline and provide guidance on the deployment of relevant tools by revisiting the emulation of the Clinical Outcomes of Surgical Therapy Study Group Trial on laparoscopy-assisted colectomy versus open colectomy in patients with early-stage colon cancer. We also draw on existing literature on EHR emulation of RCTs together with our own studies with the Mass General Brigham EHR.

PMID:37227772 | DOI:10.2196/45662

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Association of Second-generation Antiandrogens With Cognitive and Functional Toxic Effects in Randomized Clinical Trials: A Systematic Review and Meta-analysis

JAMA Oncol. 2023 May 25. doi: 10.1001/jamaoncol.2023.0998. Online ahead of print.

ABSTRACT

IMPORTANCE: The use of second-generation antiandrogens (AAs) in the treatment of prostate cancer is increasing. Retrospective evidence suggests an association between second-generation AAs and adverse cognitive and functional outcomes, but further data from prospective trials are needed.

OBJECTIVE: To examine whether evidence from randomized clinical trials (RCTs) in prostate cancer supports an association between second-generation AAs and cognitive or functional toxic effects.

DATA SOURCES: PubMed, EMBASE, and Scopus (inception to September 12, 2022).

STUDY SELECTION: Randomized clinical trials of second-generation AAs (abiraterone, apalutamide, darolutamide, or enzalutamide) among individuals with prostate cancer that reported cognitive toxic effects, asthenic toxic effects (eg, fatigue, weakness), or falls were evaluated.

DATA EXTRACTION AND SYNTHESIS: Study screening, data abstraction, and bias assessment were completed independently by 2 reviewers following the Preferred Reporting Items for Systematic Reviews and Meta-analyses and Enhancing the Quality and Transparency of Health Research reporting guidelines. Tabular counts for all-grade toxic effects were determined to test the hypothesis formulated before data collection.

MAIN OUTCOMES AND MEASURES: Risk ratios (RRs) and SEs were calculated for cognitive toxic effects, asthenic toxic effects, and falls. Because fatigue was the asthenic toxic effect extracted from all studies, data on fatigue are specified in the results. Meta-analysis and meta-regression were used to generate summary statistics.

RESULTS: The systematic review included 12 studies comprising 13 524 participants. Included studies had a low risk of bias. An increased risk of cognitive toxic effects (RR, 2.10; 95% CI, 1.30-3.38; P = .002) and fatigue (RR, 1.34; 95% CI, 1.16-1.54; P < .001) was noted among individuals treated with second-generation AAs vs those in the control arms. The findings were consistent in studies that included traditional hormone therapy in both treatment arms for cognitive toxic effects (RR, 1.77; 95% CI, 1.12-2.79; P = .01) and fatigue (RR, 1.32; 95% CI, 1.10-1.58; P = .003). Meta-regression supported that, across studies, increased age was associated with a greater risk of fatigue with second-generation AAs (coefficient, 0.75; 95% CI, 0.04-0.12; P < .001). In addition, the use of second-generation AAs was associated with an increased risk of falls (RR, 1.87; 95% CI, 1.27-2.75; P = .001).

CONCLUSIONS AND RELEVANCE: The findings of this systematic review and meta-analysis suggest that second-generation AAs carry an increased risk of cognitive and functional toxic effects, including when added to traditional forms of hormone therapy.

PMID:37227736 | DOI:10.1001/jamaoncol.2023.0998

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County-Level Maternal Vulnerability and Preterm Birth in the US

JAMA Netw Open. 2023 May 1;6(5):e2315306. doi: 10.1001/jamanetworkopen.2023.15306.

ABSTRACT

IMPORTANCE: Appreciation for the effects of neighborhood conditions and community factors on perinatal health is increasing. However, community-level indices specific to maternal health and associations with preterm birth (PTB) have not been assessed.

OBJECTIVE: To examine the association of the Maternal Vulnerability Index (MVI), a novel county-level index designed to quantify maternal vulnerability to adverse health outcomes, with PTB.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used US Vital Statistics data from January 1 to December 31, 2018. Participants included 3 659 099 singleton births at 22 plus 0/7 to 44 plus 6/7 weeks of gestation born in the US. Analyses were conducted from December 1, 2021, through March 31, 2023.

EXPOSURE: The MVI, a composite measure of 43 area-level indicators, categorized into 6 themes reflecting physical, social, and health care landscapes. Overall MVI and theme were stratified by quintile (very low to very high) by maternal county of residence.

MAIN OUTCOMES AND MEASURES: The primary outcome was PTB (gestational age <37 weeks). Secondary outcomes were PTB categories: extreme (gestational age ≤28 weeks), very (gestational age 29-31 weeks), moderate (gestational age 32-33 weeks), and late (gestational age 34-36 weeks). Multivariable logistic regression quantified associations of MVI, overall and by theme, with PTB, overall and by PTB category.

RESULTS: Among 3 659 099 births, 298 847 (8.2%) were preterm (male, 51.1%; female, 48.9%). Maternal race and ethnicity included 0.8% American Indian or Alaska Native, 6.8% Asian or Pacific Islander, 23.6% Hispanic, 14.5% non-Hispanic Black, 52.1% non-Hispanic White, and 2.2% with more than 1 race. Compared with full-term births, MVI was higher for PTBs across all themes. Very high MVI was associated with increased PTB in unadjusted (odds ratio [OR], 1.50 [95% CI, 1.45-1.56]) and adjusted (OR, 1.07 [95% CI, 1.01-1.13]) analyses. In adjusted analyses of PTB categories, MVI had the largest association with extreme PTB (adjusted OR, 1.18 [95% CI, 1.07-1.29]). Higher MVI in the themes of physical health, mental health and substance abuse, and general health care remained associated with PTB overall in adjusted models. While the physical health and socioeconomic determinant themes were associated with extreme PTB, physical health, mental health and substance abuse, and general health care themes were associated with late PTB.

CONCLUSIONS AND RELEVANCE: The findings of this cohort study suggest that MVI was associated with PTB even after adjustment for individual-level confounders. The MVI is a useful measure for county-level PTB risk that may have policy implications for counties working to lower preterm rates and improve perinatal outcomes.

PMID:37227724 | DOI:10.1001/jamanetworkopen.2023.15306

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The role of habitual learning in premotor attention allocation

J Vis. 2023 May 2;23(5):19. doi: 10.1167/jov.23.5.19.

ABSTRACT

Dual-task studies have demonstrated that goal-directed actions are typically preceded by a premotor shift of visual attention toward the movement goal location. This finding is often taken as evidence for an obligatory coupling between attention and motor preparation. Here, we examined whether this coupling entails a habitual component relating to an expectation of spatial congruence between visual and motor targets. In two experiments, participants had to identify a visual discrimination target (DT) while preparing variably delayed pointing movements to a motor target (MT). To induce distinct expectations regarding the DT position, different groups of participants performed a training phase in which the DT either always appeared at MT, opposite to MT, or at an unpredictable position. In a subsequent test phase, the DT position was randomized to assess the impact of learned expectancy on premotor attention allocation. Although we applied individually determined DT presentation times in the test phase of Experiment 1, a fixed DT presentation time was used in Experiment 2. Both experiments yielded evidence for attentional enhancement at the expected DT position. Although interpretability of this effect was limited in Experiment 1 because of between-group differences in DT presentation time, results of Experiment 2 were much clearer. Specifically, a marked discrimination benefit was observed at the position opposite to MT in participants anticipating the DT at this position, whereas no statistically significant benefit was found at MT. Crucially, this was observed at short movement delays, demonstrating that expectation of spatial incongruence between visual and motor targets allows for decoupling of attentional resources from ongoing motor preparation. Based on our findings, we suggest that premotor attention shifts entail a considerable habitual component rather than being the sole result of motor programming.

PMID:37227715 | DOI:10.1167/jov.23.5.19

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Association of Metformin With the Development of Age-related Macular Degeneration in the Diabetes Prevention Program Outcomes Study-Reply

JAMA Ophthalmol. 2023 May 25. doi: 10.1001/jamaophthalmol.2023.1892. Online ahead of print.

NO ABSTRACT

PMID:37227711 | DOI:10.1001/jamaophthalmol.2023.1892

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Correlates of Homelessness Among Adults with Personality Disorder

Psychiatr Q. 2023 May 25. doi: 10.1007/s11126-023-10027-w. Online ahead of print.

ABSTRACT

Although personality disorders (PDs) are more common among persons experiencing homelessness than the general population, few studies have investigated the risk of experiencing homelessness among persons with PDs. This study seeks to identify the demographic, socioeconomic, and behavioral health correlates of past-year homelessness among persons with antisocial, borderline, and schizotypal PDs. Nationally representative data of the civilian, noninstitutionalized population of the United States was used to identify correlates of homelessness. Descriptive statistics and bivariate associations between variables and homeless status were summarized prior to conducting several multivariate logistic regression models to identify correlates of homelessness. Main findings revealed positive associations between poverty, relationship dysfunction, and lifetime suicide attempt with homelessness. In the antisocial PD (ASPD) and borderline PD (BPD) models, comorbid BPD and ASPD, respectively, were associated with higher odds of past-year homelessness. Findings underscore the importance of poverty, interpersonal difficulties, and behavioral health comorbidities on homelessness among persons with ASPD, BPD, and schizotypal PD. Strategies to promote economic security, stable relationships, and interpersonal functioning may buffer against the effects of economic volatility and other systemic factors that could contribute to homelessness and persons with PD.

PMID:37227676 | DOI:10.1007/s11126-023-10027-w