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Appetite May 2024Consuming enough energy to meet high energy demands can be challenging for military personnel wherein logistical constraints limit food availability. Increasing dietary...
Consuming enough energy to meet high energy demands can be challenging for military personnel wherein logistical constraints limit food availability. Increasing dietary energy density (ED) and/or volume density (VD) of rations may be countermeasures, but whether positive linear associations between ED and energy intake (EI) hold at moderate-to-high ED and VD is unclear. This study examined the effects of covertly increasing the ED and VD of moderate ED (≥1.6 kcal/g) foods on appetite and energy intake. Twenty healthy men completed four 2-day treatments in random order by consuming a standardized diet containing three experimental food items (EXP) engineered using leavening, physical compression and fat manipulation to be isovolumetric but lower (L) or higher (H) in ED and VD creating four treatments: LED/LVD, LED/HVD, HED/LVD, HED/HVD. Consumption of EXP was compulsory during two meals and a snack, but remaining intake was self-selected (SSF). Results failed to show any ED-by-VD interactions. During LVD, EI was lower for EXP (-417 kcal [95%CI: 432, -402], p < 0.01) and TOTAL (SSF + EXP) (-276 kcal [95%CI: 470, -83], p = 0.01) compared to HVD, while SSF EI did not differ (140 kcal [-51, 332], p = 0.15). During LED, EI for EXP (-291 kcal [95%CI: 306, -276], p < 0.01) was lower than HED, while SSF EI was higher than HED (203 kcal 95%CI: [12, 394], p = 0.04) and TOTAL EI did not differ (-88 kcal [-282, 105], p = 0.36). Thus, when a small isovolumetric portion of the diet was manipulated, increasing the VD of moderate ED foods failed to elicit compensatory reductions in ad libitum EI while increasing the ED of moderate ED foods did. Findings may support VD manipulation of moderate ED foods as a strategy to promote increased short-term EI in environments wherein logistical burden may limit food volume.
PubMed: 38825013
DOI: 10.1016/j.appet.2024.107537 -
BMC Public Health Jun 2024Globally, the counting of deaths based on gender identity and sexual orientation has been a challenge for health systems. In most cases, non-governmental organizations...
Accuracy, potential, and limitations of probabilistic record linkage in identifying deaths by gender identity and sexual orientation in the state of Rio De Janeiro, Brazil.
BACKGROUND
Globally, the counting of deaths based on gender identity and sexual orientation has been a challenge for health systems. In most cases, non-governmental organizations have dedicated themselves to this work. Despite these efforts in generating information, the scarcity of official data presents significant limitations in policy formulation and actions guided by population needs. Therefore, this manuscript aims to evaluate the accuracy, potential, and limits of probabilistic data relationships to yield information on deaths according to gender identity and sexual orientation in the State of Rio de Janeiro.
METHODS
This study evaluated the accuracy of the probabilistic record linkage to obtain information on deaths according to gender and sexual orientation. Data from two information systems were used from June 15, 2015 to December 31, 2020. We constructed nine probabilistic data relationship strategies and identified the performance and cutoff points of the best strategy.
RESULTS
The best data blocking strategy was established through logical blocks with the first and last names, birthdate, and mother's name in the pairing strategy. With a population base of 80,178 records, 1556 deaths were retrieved. With an area under the curve of 0.979, this strategy presented 93.26% accuracy, 98.46% sensitivity, and 90.04% specificity for the cutoff point ≥ 17.9 of the data relationship score. The adoption of the cutoff point optimized the manual review phase, identifying 2259 (90.04%) of the 2509 false pairs and identifying 1532 (98.46%) of the 1556 true pairs.
CONCLUSION
With the identification of possible strategies for determining probabilistic data relationships, the retrieval of information on mortality according to sexual and gender markers has become feasible. Based on information from the daily routine of health services, the formulation of public policies that consider the LGBTQ + population more closely reflects the reality experienced by these population groups.
Topics: Humans; Brazil; Female; Male; Gender Identity; Sexual Behavior; Medical Record Linkage; Data Accuracy; Death Certificates; Adult
PubMed: 38824562
DOI: 10.1186/s12889-024-19002-x -
Journal of Medical Internet Research May 2024Efficient data exchange and health care interoperability are impeded by medical records often being in nonstandardized or unstructured natural language format. Advanced...
BACKGROUND
Efficient data exchange and health care interoperability are impeded by medical records often being in nonstandardized or unstructured natural language format. Advanced language models, such as large language models (LLMs), may help overcome current challenges in information exchange.
OBJECTIVE
This study aims to evaluate the capability of LLMs in transforming and transferring health care data to support interoperability.
METHODS
Using data from the Medical Information Mart for Intensive Care III and UK Biobank, the study conducted 3 experiments. Experiment 1 assessed the accuracy of transforming structured laboratory results into unstructured format. Experiment 2 explored the conversion of diagnostic codes between the coding frameworks of the ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), and Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) using a traditional mapping table and a text-based approach facilitated by the LLM ChatGPT. Experiment 3 focused on extracting targeted information from unstructured records that included comprehensive clinical information (discharge notes).
RESULTS
The text-based approach showed a high conversion accuracy in transforming laboratory results (experiment 1) and an enhanced consistency in diagnostic code conversion, particularly for frequently used diagnostic names, compared with the traditional mapping approach (experiment 2). In experiment 3, the LLM showed a positive predictive value of 87.2% in extracting generic drug names.
CONCLUSIONS
This study highlighted the potential role of LLMs in significantly improving health care data interoperability, demonstrated by their high accuracy and efficiency in data transformation and exchange. The LLMs hold vast potential for enhancing medical data exchange without complex standardization for medical terms and data structure.
Topics: Humans; Health Information Exchange; Health Information Interoperability; Electronic Health Records; Natural Language Processing; Systematized Nomenclature of Medicine
PubMed: 38819879
DOI: 10.2196/56614 -
Heliyon May 2024Emotion recognition technology through EEG signal analysis is currently a fundamental concept in artificial intelligence. This recognition has major practical... (Review)
Review
Emotion recognition technology through EEG signal analysis is currently a fundamental concept in artificial intelligence. This recognition has major practical implications in emotional health care, human-computer interaction, and so on. This paper provides a comprehensive study of different methods for extracting electroencephalography (EEG) features for emotion recognition from four different perspectives, including time domain features, frequency domain features, time-frequency features, and nonlinear features. We summarize the current pattern recognition methods adopted in most related works, and with the rapid development of deep learning (DL) attracting the attention of researchers in this field, we pay more attention to deep learning-based studies and analyse the characteristics, advantages, disadvantages, and applicable scenarios. Finally, the current challenges and future development directions in this field were summarized. This paper can help novice researchers in this field gain a systematic understanding of the current status of emotion recognition research based on EEG signals and provide ideas for subsequent related research.
PubMed: 38818173
DOI: 10.1016/j.heliyon.2024.e31485 -
Scientific Reports May 2024Post-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a potential diagnostic biomarker for PTSD is investigated in this study....
Post-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a potential diagnostic biomarker for PTSD is investigated in this study. We analyze an original cohort of 148 individuals exposed to the November 13, 2015, terrorist attacks in Paris. The interviews, conducted 5-11 months after the event, include individuals from similar socioeconomic backgrounds exposed to the same incident, responding to identical questions and using uniform PTSD measures. Using this dataset to collect nuanced insights that might be clinically relevant, we propose a three-step interdisciplinary methodology that integrates expertise from psychiatry, linguistics, and the Natural Language Processing (NLP) community to examine the relationship between language and PTSD. The first step assesses a clinical psychiatrist's ability to diagnose PTSD using interview transcription alone. The second step uses statistical analysis and machine learning models to create language features based on psycholinguistic hypotheses and evaluate their predictive strength. The third step is the application of a hypothesis-free deep learning approach to the classification of PTSD in our cohort. Results show that the clinical psychiatrist achieved a diagnosis of PTSD with an AUC of 0.72. This is comparable to a gold standard questionnaire (Area Under Curve (AUC) ≈ 0.80). The machine learning model achieved a diagnostic AUC of 0.69. The deep learning approach achieved an AUC of 0.64. An examination of model error informs our discussion. Importantly, the study controls for confounding factors, establishes associations between language and DSM-5 subsymptoms, and integrates automated methods with qualitative analysis. This study provides a direct and methodologically robust description of the relationship between PTSD and language. Our work lays the groundwork for advancing early and accurate diagnosis and using linguistic markers to assess the effectiveness of pharmacological treatments and psychotherapies.
Topics: Stress Disorders, Post-Traumatic; Humans; Deep Learning; Male; Machine Learning; Female; Adult; Language; Natural Language Processing; Biomarkers; Middle Aged
PubMed: 38816468
DOI: 10.1038/s41598-024-61557-7 -
Heliyon May 2024This study aims to explore the effect of eco-innovation and renewable energy on carbon dioxide emissions (CDE) for G7 countries. Using regression models, the results...
This study aims to explore the effect of eco-innovation and renewable energy on carbon dioxide emissions (CDE) for G7 countries. Using regression models, the results reveal that eco-innovation and renewable energy lead to reducing CDE in the presence of governance variables. Additional analysis is conducted to examine whether Hofstede national culture dimensions moderate the nexus of "eco-innovation- carbon emission" and "renewable energy-carbon emission". The results show that individualism, long-term orientation, and indulgence dimensions moderate positively the eco-innovation-carbon emission relationship. Moreover, power distance and uncertainty avoidance dimensions moderate the relationship between renewable energy and CDE and help reduce carbon emissions. The outcomes of this study provide new insights and directives for policymakers and regulators. In fact, increased investment in eco-innovation and renewable energy will support the environmental agenda of G7 countries. National cultural dimensions should be taken into consideration to improve awareness of environmental quality. Moreover, the combination of governance indicators plays a key role in environmental sustainability.
PubMed: 38813154
DOI: 10.1016/j.heliyon.2024.e31142 -
Case Reports in Critical Care 2024Acute hypoxemic respiratory failure from infective endocarditis with septic emboli has been attributed to the vicious cycle of tissue damage and inflammatory cytokine...
Acute hypoxemic respiratory failure from infective endocarditis with septic emboli has been attributed to the vicious cycle of tissue damage and inflammatory cytokine response. Spontaneous pneumothorax is a rare complication and can be a late-onset presentation despite appropriate antibiotic therapy. We present a rare case of bilateral spontaneous pneumothoraces in a patient with tricuspid valve endocarditis and septic pulmonary emboli. We suspect that the profound inflammatory response from two different bacterial pathogens and the peripheral location of the septic thrombosis are the basis of the development of bilateral pneumothorax development in our patient.
PubMed: 38808068
DOI: 10.1155/2024/3049691 -
Current Research in Food Science 2024This study explores the effect of spray-drying (SD) inlet temperatures (T 120 and 150 °C) and wall material on the chemical and physico-chemical properties of...
This study explores the effect of spray-drying (SD) inlet temperatures (T 120 and 150 °C) and wall material on the chemical and physico-chemical properties of microencapsulated hop extracts (MHE). Hop extract was formulated with maltodextrin (MD) and gum Arabic (GA) used in single or in combination with β-cyclodextrin (βCD). MHE were evaluated for physical properties, bitter acids (BA), total polyphenol content (TPC) and encapsulation efficiency (TPC EE), and antioxidant capacity (AOC). Powders produced at T 150 °C exhibited the highest flowability and generally higher TPC yield. Besides T, MD enabled the obtaining of MHE with the highest encapsulation efficiency. Other physico-chemical and antioxidant properties differently varied depending on the T. Overall, the βCD addition positively affected α-acids, and β-acids of MHE obtained at T 120 °C. ATR-FTIR analysis showed hydrogen bond formation between hop compounds and βCD. Multifactorial ANOVA highlighted that T, W, and their interaction influenced almost all the chemical and physico-chemical properties of MHE.
PubMed: 38800638
DOI: 10.1016/j.crfs.2024.100769 -
JAMA Health Forum May 2024Prices for brand-name drugs affect both federal spending and out-of-pocket liability for Medicare Part D enrollees.
IMPORTANCE
Prices for brand-name drugs affect both federal spending and out-of-pocket liability for Medicare Part D enrollees.
OBJECTIVE
To examine how prices for brand-name drugs, net of rebates and discounts, have changed from 2010 to 2019 and to examine the role of specialty drugs in those changes.
DESIGN, SETTING, AND PARTICIPANTS
This study involved a descriptive analysis of prescription drug spending and prices between 2010 and 2019. The universe of prescription drug event data from those years were combined with confidential data from the Centers for Medicare & Medicaid Services on rebates and discounts that manufacturers and pharmacies pay to Medicare Part D plans to calculate rebate percentages, net spending, and net prices at the drug level. Specialty drugs were identified using information from IQVIA, allowing for a stratified analysis by specialty status. Data were analyzed from March 2019 to March 2024.
MAIN OUTCOMES AND MEASURES
Average prices (net of rebates and discounts in 2019 US dollars) and average annual price growth for brand-name prescription drugs, overall and separately for specialty and nonspecialty drugs.
RESULTS
Average net prices for brand-name drugs doubled from 2010 to 2019 (from $167 to $370). Growth in specialty drug prices was an underlying factor in those increases: average annual price growth was 13.2% for specialty drugs compared with 2.6% for nonspecialty drugs. Price growth for specialty drugs over the decade was smaller than what the Congressional Budget Office reported for the 2010 to 2015 period (increase of 22.3% per year vs 4.5% per year for nonspecialty drug prices), suggesting that price growth slowed after 2015. Drugs that treat hepatitis C contributed to that difference because prices for those drugs were initially high and then subsequently fell. Absent those drugs, price growth for specialty drugs averaged 18.1% in the first half of the decade and 6.9% in the second half.
CONCLUSIONS AND RELEVANCE
Results of this study show that prices for specialty drugs have continued to increase over time in the Medicare Part D program, which contributes to high out-of-pocket liability for users of those drugs in addition to US federal budgetary expenditures.
Topics: United States; Medicare Part D; Humans; Drug Costs; Prescription Drugs; Health Expenditures
PubMed: 38787543
DOI: 10.1001/jamahealthforum.2024.1188 -
Diseases (Basel, Switzerland) May 2024Hepatitis C Virus (HCV) infection represents a significant global health challenge, with its natural course largely influenced by the host's immune response. Human...
Frequency of the Main Human Leukocyte Antigen A, B, DR, and DQ Loci Known to Be Associated with the Clearance or Persistence of Hepatitis C Virus Infection in a Healthy Population from the Southern Region of Morocco: A Preliminary Study.
Hepatitis C Virus (HCV) infection represents a significant global health challenge, with its natural course largely influenced by the host's immune response. Human Leukocyte Antigen (HLA) molecules, particularly HLA class I and II, play a crucial role in the adaptive immune response against HCV. The polymorphism of HLA molecules contributes to the variability in immune response, affecting the outcomes of HCV infection. This study aims to investigate the frequency of HLA A, B, DR, and DQ alleles known to be associated with HCV clearance or persistence in a healthy Moroccan population. Conducted at the University Hospital Center Mohammed VI, Marrakech, this study spanned from 2015 to 2022 and included 703 healthy Moroccan individuals. HLA class I and II typing was performed using complement-dependent cytotoxicity and polymerase chain reaction-based methodologies. The results revealed the distinct patterns of HLA-A, B, DRB1, and DQB1 alleles in the Moroccan population. Notably, alleles linked to favorable HCV outcomes, such as HLA-DQB1*0301, DQB1*0501, and DRB1*1101, were more prevalent. Conversely, alleles associated with increased HCV susceptibility and persistence, such as HLA-DQB1*02 and DRB1*03, were also prominent. Gender-specific variations in allele frequencies were observed, providing insights into genetic influences on HCV infection outcomes. The findings align with global trends in HLA allele associations with HCV infection outcomes. The study emphasizes the role of host genetics in HCV infection, highlighting the need for further research in the Moroccan community, including HCV-infected individuals. The prevalence of certain HLA alleles, both protective and susceptibility-linked, underscores the potential for a national HLA data bank in Morocco.
PubMed: 38785761
DOI: 10.3390/diseases12050106