LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 135

Search options

  1. Article ; Online: Influence of Demographic Factors on Clinical Outcomes in Adults With Chronic Idiopathic Constipation Treated With Plecanatide.

    Rao, Satish S C / Laitman, Adam P / Miner, Philip B

    Clinical and translational gastroenterology

    2023  Volume 14, Issue 7, Page(s) e00598

    Abstract: Introduction: Chronic idiopathic constipation (CIC) is a common condition that affects some patient groups more often. Demographic/clinical characteristics can differ in presentation and therapeutic response. The impact of these characteristics on ... ...

    Abstract Introduction: Chronic idiopathic constipation (CIC) is a common condition that affects some patient groups more often. Demographic/clinical characteristics can differ in presentation and therapeutic response. The impact of these characteristics on plecanatide efficacy/safety was examined.
    Methods: Data from 2 identically designed, randomized, phase 3 trials of adults with CIC receiving 3 mg of plecanatide, 6 mg of plecanatide, or placebo for 12 weeks were analyzed. Subgroups were baseline age, body mass index (BMI), race/ethnicity, and sex/gender. Endpoints included durable overall complete spontaneous bowel movement (CSBM) responder rate, weekly CSBMs and spontaneous bowel movements (SBMs), and adverse events.
    Results: Overall (N = 2,639; 3 mg of plecanatide [n = 877]; 6 mg of plecanatide [n = 877]; and placebo [n = 885]), CSBM responder rates were significantly greater with 3 mg of plecanatide and 6 mg of plecanatide vs placebo in subgroups with those younger than 65 years ( P < 0.001), females ( P < 0.001), White individuals ( P < 0.001), and BMI <25 kg/m 2 ( P ≤ 0.004) and 25-30 kg/m 2 ( P < 0.001); as well, for 3 mg: 65 years or older ( P = 0.03), non-White individuals ( P < 0.001), and BMI ≥30 kg/m 2 ( P = 0.02). Improvement from baseline in weekly CSBM and SBM frequency occurred in all subgroups for both plecanatide doses vs placebo ( P ≤ 0.02) at week 12, except those aged 65 years or older for 6 mg of plecanatide. The most common adverse event was diarrhea (3 mg [4.9%]; 6 mg [5.4%]; and placebo [1.3%]).
    Discussion: Pooled data from identically designed CIC trials strengthened the ability to identify meaningful subgroup comparisons regarding plecanatide efficacy and safety.
    MeSH term(s) Adult ; Female ; Humans ; Constipation/drug therapy ; Defecation ; Ethnicity ; Natriuretic Peptides/therapeutic use
    Chemical Substances Natriuretic Peptides ; plecanatide (7IK8Z952OK)
    Language English
    Publishing date 2023-07-01
    Publishing country United States
    Document type Clinical Trial, Phase III ; Journal Article ; Randomized Controlled Trial ; Research Support, Non-U.S. Gov't
    ZDB-ID 2581516-7
    ISSN 2155-384X ; 2155-384X
    ISSN (online) 2155-384X
    ISSN 2155-384X
    DOI 10.14309/ctg.0000000000000598
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  2. Article ; Online: High-performance microchip electrophoresis separations of preterm birth biomarkers using 3D printed microfluidic devices.

    Esene, Joule E / Nasman, Parker R / Miner, Dallin S / Nordin, Gregory P / Woolley, Adam T

    Journal of chromatography. A

    2023  Volume 1706, Page(s) 464242

    Abstract: We employed digital light processing-stereolithography 3D printing to create microfluidic devices with different designs for microchip electrophoresis (µCE). Short or long straight channel, and two- or four-turn serpentine channel microfluidic devices ... ...

    Abstract We employed digital light processing-stereolithography 3D printing to create microfluidic devices with different designs for microchip electrophoresis (µCE). Short or long straight channel, and two- or four-turn serpentine channel microfluidic devices with separation channel lengths of 1.3, 3.1, 3.0, and 4.7 cm, respectively, all with a cross injector design, were fabricated. We measured current as a function of time and voltage to determine a separation time window and conditions for the onset of Joule heating in these designs. Separations in these devices were evaluated by performing µCE and measuring theoretical plate counts for electric field strengths near and above the onset of Joule heating, with fluorescently labeled glycine and phenylalanine as model analytes. We further demonstrated µCE of peptides and proteins related to preterm birth risk, showing increased peak capacity and resolution compared to previous results with 3D printed microdevices. These results mark an important step forward in the use of 3D printed microfluidic devices for rapid bioanalysis by µCE.
    MeSH term(s) Infant, Newborn ; Female ; Humans ; Electrophoresis, Microchip ; Premature Birth/diagnosis ; Lab-On-A-Chip Devices ; Biomarkers ; Printing, Three-Dimensional
    Chemical Substances Biomarkers
    Language English
    Publishing date 2023-08-01
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1171488-8
    ISSN 1873-3778 ; 0021-9673
    ISSN (online) 1873-3778
    ISSN 0021-9673
    DOI 10.1016/j.chroma.2023.464242
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  3. Article ; Online: Chatbots in the fight against the COVID-19 pandemic.

    Miner, Adam S / Laranjo, Liliana / Kocaballi, A Baki

    NPJ digital medicine

    2020  Volume 3, Page(s) 65

    Abstract: We are all together in a fight against the COVID-19 pandemic. Chatbots, if effectively designed and deployed, could help us by sharing up-to-date information quickly, encouraging desired health impacting behaviors, and lessening the psychological damage ... ...

    Abstract We are all together in a fight against the COVID-19 pandemic. Chatbots, if effectively designed and deployed, could help us by sharing up-to-date information quickly, encouraging desired health impacting behaviors, and lessening the psychological damage caused by fear and isolation. Despite this potential, the risk of amplifying misinformation and the lack of prior effectiveness research is cause for concern. Immediate collaborations between healthcare workers, companies, academics and governments are merited and may aid future pandemic preparedness efforts.
    Keywords covid19
    Language English
    Publishing date 2020-05-04
    Publishing country England
    Document type Journal Article
    ISSN 2398-6352
    ISSN (online) 2398-6352
    DOI 10.1038/s41746-020-0280-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  4. Article ; Online: Predicting premature discontinuation of medication for opioid use disorder from electronic medical records.

    Lopez, Ivan / Fouladvand, Sajjad / Kollins, Scott / Chen, Chwen-Yuen Angie / Bertz, Jeremiah / Hernandez-Boussard, Tina / Lembke, Anna / Humphreys, Keith / Miner, Adam S / Chen, Jonathan H

    AMIA ... Annual Symposium proceedings. AMIA Symposium

    2024  Volume 2023, Page(s) 1067–1076

    Abstract: Medications such as buprenorphine-naloxone are among the most effective treatments for opioid use disorder, but limited retention in treatment limits long-term outcomes. In this study, we assess the feasibility of a machine learning model to predict ... ...

    Abstract Medications such as buprenorphine-naloxone are among the most effective treatments for opioid use disorder, but limited retention in treatment limits long-term outcomes. In this study, we assess the feasibility of a machine learning model to predict retention vs. attrition in medication for opioid use disorder (MOUD) treatment using electronic medical record data including concepts extracted from clinical notes. A logistic regression classifier was trained on 374 MOUD treatments with 68% resulting in potential attrition. On a held-out test set of 157 events, the full model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% CI: 0.64-0.90) and AUROC of 0.74 (95% CI: 0.62-0.87) with a limited model using only structured EMR data. Risk prediction for opioid MOUD retention vs. attrition is feasible given electronic medical record data, even without necessarily incorporating concepts extracted from clinical notes.
    MeSH term(s) Humans ; Electronic Health Records ; Area Under Curve ; Machine Learning ; Opioid-Related Disorders/drug therapy ; ROC Curve ; Analgesics, Opioid/therapeutic use
    Chemical Substances Analgesics, Opioid
    Language English
    Publishing date 2024-01-11
    Publishing country United States
    Document type Journal Article
    ISSN 1942-597X
    ISSN (online) 1942-597X
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  5. Article ; Online: Perceptions of Data Set Experts on Important Characteristics of Health Data Sets Ready for Machine Learning: A Qualitative Study.

    Ng, Madelena Y / Youssef, Alaa / Miner, Adam S / Sarellano, Daniela / Long, Jin / Larson, David B / Hernandez-Boussard, Tina / Langlotz, Curtis P

    JAMA network open

    2023  Volume 6, Issue 12, Page(s) e2345892

    Abstract: Importance: The lack of data quality frameworks to guide the development of artificial intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in health care and hinders the diagnostic excellence of developed ... ...

    Abstract Importance: The lack of data quality frameworks to guide the development of artificial intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in health care and hinders the diagnostic excellence of developed clinical AI applications for patient care.
    Objective: To discern what constitutes high-quality and useful data sets for health and biomedical ML research purposes according to subject matter experts.
    Design, setting, and participants: This qualitative study interviewed data set experts, particularly those who are creators and ML researchers. Semistructured interviews were conducted in English and remotely through a secure video conferencing platform between August 23, 2022, and January 5, 2023. A total of 93 experts were invited to participate. Twenty experts were enrolled and interviewed. Using purposive sampling, experts were affiliated with a diverse representation of 16 health data sets/databases across organizational sectors. Content analysis was used to evaluate survey information and thematic analysis was used to analyze interview data.
    Main outcomes and measures: Data set experts' perceptions on what makes data sets AI ready.
    Results: Participants included 20 data set experts (11 [55%] men; mean [SD] age, 42 [11] years), of whom all were health data set creators, and 18 of the 20 were also ML researchers. Themes (3 main and 11 subthemes) were identified and integrated into an AI-readiness framework to show their association within the health data ecosystem. Participants partially determined the AI readiness of data sets using priority appraisal elements of accuracy, completeness, consistency, and fitness. Ethical acquisition and societal impact emerged as appraisal considerations in that participant samples have not been described to date in prior data quality frameworks. Factors that drive creation of high-quality health data sets and mitigate risks associated with data reuse in ML research were also relevant to AI readiness. The state of data availability, data quality standards, documentation, team science, and incentivization were associated with elements of AI readiness and the overall perception of data set usefulness.
    Conclusions and relevance: In this qualitative study of data set experts, participants contributed to the development of a grounded framework for AI data set quality. Data set AI readiness required the concerted appraisal of many elements and the balancing of transparency and ethical reflection against pragmatic constraints. The movement toward more reliable, relevant, and ethical AI and ML applications for patient care will inevitably require strategic updates to data set creation practices.
    MeSH term(s) Adult ; Female ; Humans ; Male ; Artificial Intelligence ; Delivery of Health Care ; Machine Learning ; Qualitative Research
    Language English
    Publishing date 2023-12-01
    Publishing country United States
    Document type Journal Article
    ISSN 2574-3805
    ISSN (online) 2574-3805
    DOI 10.1001/jamanetworkopen.2023.45892
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  6. Article ; Online: Examining the Examiners: How Medical Death Investigators Describe Suicidal, Homicidal, and Accidental Death.

    Miner, Adam S / Markowitz, David M / Peterson, Brian L / Weston, Benjamin W

    Health communication

    2020  Volume 37, Issue 4, Page(s) 467–475

    Abstract: This study describes differences in medicolegal death investigators' written descriptions for people who died by homicide, suicide, or accident. We evaluated 17 years of death descriptions from a midsized metropolitan midwestern county in the United ... ...

    Abstract This study describes differences in medicolegal death investigators' written descriptions for people who died by homicide, suicide, or accident. We evaluated 17 years of death descriptions from a midsized metropolitan midwestern county in the United States to assess how death investigators psychologically respond to different manners of death (
    MeSH term(s) Accidents ; Cause of Death ; Homicide ; Humans ; Retrospective Studies ; Suicidal Ideation ; Suicide ; United States/epidemiology
    Language English
    Publishing date 2020-12-01
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1038723-7
    ISSN 1532-7027 ; 1041-0236
    ISSN (online) 1532-7027
    ISSN 1041-0236
    DOI 10.1080/10410236.2020.1851862
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

  7. Article ; Online: Chatbots in the fight against the COVID-19 pandemic

    Adam S. Miner / Liliana Laranjo / A. Baki Kocaballi

    npj Digital Medicine, Vol 3, Iss 1, Pp 1-

    2020  Volume 4

    Abstract: We are all together in a fight against the COVID-19 pandemic. Chatbots, if effectively designed and deployed, could help us by sharing up-to-date information quickly, encouraging desired health impacting behaviors, and lessening the psychological damage ... ...

    Abstract We are all together in a fight against the COVID-19 pandemic. Chatbots, if effectively designed and deployed, could help us by sharing up-to-date information quickly, encouraging desired health impacting behaviors, and lessening the psychological damage caused by fear and isolation. Despite this potential, the risk of amplifying misinformation and the lack of prior effectiveness research is cause for concern. Immediate collaborations between healthcare workers, companies, academics and governments are merited and may aid future pandemic preparedness efforts.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  8. Article ; Online: Chatbots in the fight against the COVID-19 pandemic

    Adam S. Miner / Liliana Laranjo / A. Baki Kocaballi

    npj Digital Medicine, Vol 3, Iss 1, Pp 1-

    2020  Volume 4

    Abstract: We are all together in a fight against the COVID-19 pandemic. Chatbots, if effectively designed and deployed, could help us by sharing up-to-date information quickly, encouraging desired health impacting behaviors, and lessening the psychological damage ... ...

    Abstract We are all together in a fight against the COVID-19 pandemic. Chatbots, if effectively designed and deployed, could help us by sharing up-to-date information quickly, encouraging desired health impacting behaviors, and lessening the psychological damage caused by fear and isolation. Despite this potential, the risk of amplifying misinformation and the lack of prior effectiveness research is cause for concern. Immediate collaborations between healthcare workers, companies, academics and governments are merited and may aid future pandemic preparedness efforts.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; covid19
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

  9. Article ; Online: Chatbots in the fight against the COVID-19 pandemic

    Miner, Adam S. / Laranjo, Liliana / Kocaballi, A. Baki

    npj Digital Medicine

    2020  Volume 3, Issue 1

    Keywords covid19
    Language English
    Publisher Springer Science and Business Media LLC
    Publishing country us
    Document type Article ; Online
    ISSN 2398-6352
    DOI 10.1038/s41746-020-0280-0
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    More links

    Kategorien

To top