Yale Journal of Biology and Medicine最新文献

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What Brings You in Today? Sex, Race, Substance Type, and Other Sociodemographic and Health-Related Characteristics Predict if Substance Use is the Main Reason for a Clinical Encounter. 今天是什么吸引你?性别、种族、物质类型和其他社会形态和健康相关特征可以预测药物使用是否是临床接触的主要原因。
IF 2.7 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/UDRG5942
Natasia S Courchesne-Krak, Carla B Marienfeld, Wayne Kepner
{"title":"What Brings You in Today? Sex, Race, Substance Type, and Other Sociodemographic and Health-Related Characteristics Predict if Substance Use is the Main Reason for a Clinical Encounter.","authors":"Natasia S Courchesne-Krak,&nbsp;Carla B Marienfeld,&nbsp;Wayne Kepner","doi":"10.59249/UDRG5942","DOIUrl":"10.59249/UDRG5942","url":null,"abstract":"<p><p><b>Background</b>: Substance-related diagnoses (SRDs) are a common healthcare presentation. This study identified sociodemographic and health-related characteristics associated with having an SRD as the primary reason for a clinical encounter compared to those with an SRD who are treated for other reasons. <b>Methods</b>: Electronic health record (EHR) data on patients with an SRD (n=12,358, ages 18-90) were used to assess if an SRD was the primary reason for a clinical encounter from January 1, 2012-January 1, 2018. Patients were matched on key demographic characteristics at a 1:1 ratio. Adjusting for covariates, odds ratios, and 95% confidence intervals were calculated. <b>Results</b>: In the matched cohort of 8,630, most reported male sex (65.8%), White race (70.0%), and single marital status (62.7%) with a mean age of 47.2 (SD=14.6). Patient reported female sex, Black race, age 70+, married status, and low-income (<$50,000) were associated with a lower likelihood of presenting to care for an SRD as the primary reason for a clinical encounter. A nicotine-, alcohol-, opioid-, or stimulant-related diagnosis was associated with a higher likelihood of presenting to care for an SRD as the primary reason for the clinical visit. <b>Conclusion</b>: This is the first study to investigate whether sociodemographic and health-related characteristics were associated with having an SRD as the primary reason for a clinical encounter. Using rigorous methods, we investigated a unique clinical question adding new knowledge to predictors of patients seeking clinical care. Understanding these predictors can help us better align service provision with population needs and inform new approaches to tailoring care.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"277-291"},"PeriodicalIF":2.7,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/10/e2/yjbm_96_3_277.PMC10524817.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41136392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Stop-gain Variant c.220C>T (p.(Gln74*)) in FLNB Segregates with Spondylocarpotarsal Synostosis Syndrome in a Consanguineous Family. FLNB中的一个停增变异株c.220C>T(p.(Gln74*))在一个血缘家族中分离并伴有强直性脊柱炎综合征。
IF 2.7 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/UTCP9818
Hamna Shahid, Nazish Shakoor, Anisa Bibi, Asma Saleem Qazi, Rida Fatima Saeed, Aqeela Nawaz, Sajid Malik, Sara Mumtaz
{"title":"A Stop-gain Variant c.220C>T (p.(Gln74*)) in <i>FLNB</i> Segregates with Spondylocarpotarsal Synostosis Syndrome in a Consanguineous Family.","authors":"Hamna Shahid,&nbsp;Nazish Shakoor,&nbsp;Anisa Bibi,&nbsp;Asma Saleem Qazi,&nbsp;Rida Fatima Saeed,&nbsp;Aqeela Nawaz,&nbsp;Sajid Malik,&nbsp;Sara Mumtaz","doi":"10.59249/UTCP9818","DOIUrl":"https://doi.org/10.59249/UTCP9818","url":null,"abstract":"<p><p>Spondylocarpotarsal synostosis (SCT) syndrome is a very rare and severe form of skeletal dysplasia. The hallmark features of SCT are disproportionate short stature, scoliosis, fusion of carpal and tarsal bones, and clubfoot. Other common manifestations are cleft palate, conductive and sensorineural hearing loss, joint stiffness, and dental enamel hypoplasia. Homozygous variants in <i>FLNB</i> are known to cause SCT. This study was aimed to investigate the phenotypic and genetic basis of unique presentation of SCT syndrome segregating in a consanguineous Pakistani family. Three of the four affected siblings evaluated had severe short stature, short trunk, short neck, kyphoscoliosis, pectus carinatum, and winged scapula. The subjects had difficulty in walking and gait problems and complained of knee pain and backache. Roentgenographic examination of the eldest patient revealed gross anomalies in the axial skeleton including thoracolumbar and cervical fusion of ribs, severe kyphoscoliosis, thoracic and lumbar lordosis, coxa valga, fusion of certain carpals and tarsals, and clinodactyly. The patients had normal faces and lacked other typical features of SCT like cleft palate, conductive and sensorineural hearing loss, joint stiffness, and dental enamel hypoplasia. Whole exome sequencing (WES) of two affected siblings led to the discovery of a rare stop-gain variant c.220C>T (p.(Gln74*)) in exon 1 of the <i>FLNB</i> gene. The variant was homozygous and segregated with the malformation in this family. This study reports extensive phenotypic variability in SCT and expands the mutation spectrum of <i>FLNB</i>.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"383-396"},"PeriodicalIF":2.7,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/87/cc/yjbm_96_3_383.PMC10524816.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41140085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Clinical Informatics in Critical Care Medicine. 重症医学临床信息学。
IF 2.5 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/WTTU3055
Girish N Nadkarni, Ankit Sakhuja
{"title":"Clinical Informatics in Critical Care Medicine.","authors":"Girish N Nadkarni, Ankit Sakhuja","doi":"10.59249/WTTU3055","DOIUrl":"10.59249/WTTU3055","url":null,"abstract":"<p><p>Continuous monitoring and treatment of patients in intensive care units generates vast amounts of data. Critical Care Medicine clinicians incorporate this continuously evolving data to make split-second, life or death decisions for management of these patients. Despite the abundance of data, it can be challenging to consider every accessible data point when making the quick decisions necessary at the point of care. Consequently, Clinical Informatics offers a natural partnership to improve the care for critically ill patients. The last two decades have seen a significant evolution in the role of Clinical Informatics in Critical Care Medicine. In this review, we will discuss how Clinical Informatics improves the care of critically ill patients by enhancing not only data collection and visualization but also bedside medical decision making. We will further discuss the evolving role of machine learning algorithms in Clinical Informatics as it pertains to Critical Care Medicine.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"397-405"},"PeriodicalIF":2.5,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/61/1f/yjbm_96_3_397.PMC10524812.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41148298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Ophthalmology at the Forefront of Big Data Integration in Medicine: Insights from the IRIS Registry Database. 医学大数据集成前沿的眼科学:来自IRIS注册数据库的见解。
IF 2.7 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/VUPM2510
Austen N Knapp, Theodore Leng, Ehsan Rahimy
{"title":"Ophthalmology at the Forefront of Big Data Integration in Medicine: Insights from the IRIS Registry Database.","authors":"Austen N Knapp,&nbsp;Theodore Leng,&nbsp;Ehsan Rahimy","doi":"10.59249/VUPM2510","DOIUrl":"https://doi.org/10.59249/VUPM2510","url":null,"abstract":"<p><p>Ophthalmology stands at the vanguard of incorporating big data into medicine, as exemplified by the integration of The Intelligent Research in Sight (IRIS) Registry. This synergy cultivates patient-centered care, demonstrates real world efficacy and safety data for new therapies, and facilitates comprehensive population health insights. By evaluating the creation and utilization of the world's largest specialty clinical data registry, we underscore the transformative capacity of data-driven medical paradigms, current shortcomings, and future directions. We aim to provide a scaffold for other specialties to adopt big data integration into medicine.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"421-426"},"PeriodicalIF":2.7,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/32/1f/yjbm_96_3_421.PMC10524808.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41159182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Recurrent Mutation in Growth Hormone Receptor (GHR) Gene Underlying Laron-type Dwarfism in a Pakistani Family. 生长激素受体(GHR)基因的一个复发性突变导致一个巴基斯坦家族的Laron型侏儒症。
IF 2.7 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/TCAA2040
Rana Muhammad Kamran Shabbir, Gökhan Nalbant, Qamar Zaman, Aslıhan Tolun, Sajid Malik, Sara Mumtaz
{"title":"A Recurrent Mutation in Growth Hormone Receptor (<i>GHR</i>) Gene Underlying Laron-type Dwarfism in a Pakistani Family.","authors":"Rana Muhammad Kamran Shabbir,&nbsp;Gökhan Nalbant,&nbsp;Qamar Zaman,&nbsp;Aslıhan Tolun,&nbsp;Sajid Malik,&nbsp;Sara Mumtaz","doi":"10.59249/TCAA2040","DOIUrl":"https://doi.org/10.59249/TCAA2040","url":null,"abstract":"<p><p>Laron syndrome (LS) is a rare autosomal recessively segregating disorder of severe short stature. The condition is characterized by short limbs, delayed puberty, hypoglycemia in infancy, and obesity. Mutations in growth hormone receptor (<i>GHR</i>) have been implicated in LS; hence, it is also known as growth hormone insensitivity syndrome (MIM-262500). Here we represent a consanguineous Pakistani family in which three siblings were afflicted with LS. Patients had rather similar phenotypic presentations marked with short stature, delayed bone age, limited extension of elbows, truncal obesity, delayed puberty, childish appearance, and frontal bossing. They also had additional features such as hypo-muscularity, early fatigue, large ears, widely-spaced breasts, and attention deficit behavior, which are rarely reported in LS. The unusual combination of the features hindered a straightforward diagnosis and prompted us to first detect the regions of shared homozygosity and subsequently the disease-causing variant by next generation technologies, like SNP genotyping and exome sequencing. A homozygous pathogenic variant c.508G>C (p.(Asp170His)) in <i>GHR</i> was detected. The variant is known to be implicated in LS, supporting the molecular diagnosis of LS. Also, we present detailed clinical, hematological, and hormonal profiling of the siblings.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"313-325"},"PeriodicalIF":2.7,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a6/2a/yjbm_96_3_313.PMC10524814.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41166905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial Intelligence to Improve Patient Understanding of Radiology Reports. 人工智能提高患者对放射学报告的理解。
IF 2.7 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/NKOY5498
Kanhai Amin, Pavan Khosla, Rushabh Doshi, Sophie Chheang, Howard P Forman
{"title":"Artificial Intelligence to Improve Patient Understanding of Radiology Reports.","authors":"Kanhai Amin, Pavan Khosla, Rushabh Doshi, Sophie Chheang, Howard P Forman","doi":"10.59249/NKOY5498","DOIUrl":"10.59249/NKOY5498","url":null,"abstract":"<p><p>Diagnostic imaging reports are generally written with a target audience of other providers. As a result, the reports are written with medical jargon and technical detail to ensure accurate communication. With implementation of the 21st Century Cures Act, patients have greater and quicker access to their imaging reports, but these reports are still written above the comprehension level of the average patient. Consequently, many patients have requested reports to be conveyed in language accessible to them. Numerous studies have shown that improving patient understanding of their condition results in better outcomes, so driving comprehension of imaging reports is essential. Summary statements, second reports, and the inclusion of the radiologist's phone number have been proposed, but these solutions have implications for radiologist workflow. Artificial intelligence (AI) has the potential to simplify imaging reports without significant disruptions. Many AI technologies have been applied to radiology reports in the past for various clinical and research purposes, but patient focused solutions have largely been ignored. New natural language processing technologies and large language models (LLMs) have the potential to improve patient understanding of their imaging reports. However, LLMs are a nascent technology and significant research is required before LLM-driven report simplification is used in patient care.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"407-417"},"PeriodicalIF":2.7,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/02/b7/yjbm_96_3_407.PMC10524809.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41174169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ChatGPT and the Future of Journal Reviews: A Feasibility Study. ChatGPT与期刊评论的未来:可行性研究。
IF 2.5 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/SKDH9286
Som Biswas, Dushyant Dobaria, Harris L Cohen
{"title":"ChatGPT and the Future of Journal Reviews: A Feasibility Study.","authors":"Som Biswas, Dushyant Dobaria, Harris L Cohen","doi":"10.59249/SKDH9286","DOIUrl":"10.59249/SKDH9286","url":null,"abstract":"<p><p>The increasing volume of research submissions to academic journals poses a significant challenge for traditional peer-review processes. To address this issue, this study explores the potential of employing ChatGPT, an advanced large language model (LLM), developed by OpenAI, as an artificial intelligence (AI) reviewer for academic journals. By leveraging the vast knowledge and natural language processing capabilities of ChatGPT, we hypothesize it may be possible to enhance the efficiency, consistency, and quality of the peer-review process. This research investigated key aspects of integrating ChatGPT into the journal review workflow. We compared the critical analysis of ChatGPT, acting as an AI reviewer, to human reviews for a single published article. Our methodological framework involved subjecting ChatGPT to an intricate examination, wherein its evaluative acumen was juxtaposed against human-authored reviews of a singular published article. As this is a feasibility study, one article was reviewed, which was a case report on scurvy. The entire article was used as an input into ChatGPT and commanded it to \"Please perform a review of the following article and give points for revision.\" Since this was a case report with a limited word count the entire article could fit in one chat box. The output by ChatGPT was then compared with the comments by human reviewers. Key performance metrics, including precision and overall agreement, were judiciously and subjectively measured to portray the efficacy of ChatGPT as an AI reviewer in comparison to its human counterparts. The outcomes of this rigorous analysis unveiled compelling evidence regarding ChatGPT's performance as an AI reviewer. We demonstrated that ChatGPT's critical analyses aligned with those of human reviewers, as evidenced by the inter-rater agreement. Notably, ChatGPT exhibited commendable capability in identifying methodological flaws, articulating insightful feedback on theoretical frameworks, and gauging the overall contribution of the articles to their respective fields. While the integration of ChatGPT showcased immense promise, certain challenges and caveats surfaced. For example, ambiguities might present with complex research articles, leading to nuanced discrepancies between AI and human reviews. Also figures and images cannot be reviewed by ChatGPT. Lengthy articles need to be reviewed in parts by ChatGPT as the entire article will not fit in one chat/response. The benefits consist of reduction in time needed by journals to review the articles submitted to them, as well as an AI assistant to give a different perspective about the research papers other than the human reviewers. In conclusion, this research contributes a groundbreaking foundation for incorporating ChatGPT into the pantheon of journal reviewers. The delineated guidelines distill key insights into operationalizing ChatGPT as a proficient reviewer within academic journal frameworks, paving the way for a more eff","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"415-420"},"PeriodicalIF":2.5,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/1c/fa/yjbm_96_3_415.PMC10524821.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41172019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis. 老年女性癌症患者行乳房切除术与乳房切除术的疗效比较分析:基于深度学习的大数据分析。
IF 2.5 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/IAJU7580
Jiping Wang, Shunqin Zhang, Huangdi Yi, Shuangge Ma
{"title":"Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.","authors":"Jiping Wang, Shunqin Zhang, Huangdi Yi, Shuangge Ma","doi":"10.59249/IAJU7580","DOIUrl":"10.59249/IAJU7580","url":null,"abstract":"<p><p><b>Objectives</b>: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost, a limited sample size, an inability to fully reflect the real world, and feasibility concerns. The objective is to showcase a big data approach that takes advantage of large electronic medical record (EMR) data to emulate clinical trials. To overcome the limitations of regression analysis, a deep learning-based analysis pipeline was developed. <b>Study Design and Setting</b>: Lumpectomy (breast-conserving surgery) and mastectomy are the two most commonly used surgical procedures for early-stage female breast cancer patients. An emulation trial was designed using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data to evaluate their relative effectiveness in overall survival. The analysis pipeline consisted of a propensity score step, a weighted survival analysis step, and a bootstrap inference step. <b>Results</b>: A total of 65,997 subjects were enrolled in the emulated trial, with 50,704 and 15,293 in the lumpectomy and mastectomy arms, respectively. The two surgery procedures had comparable effects in terms of overall survival (survival year change = 0.08, 95% confidence interval (CI): -0.08, 0.25) for the elderly SEER-Medicare early-stage female breast cancer patients. <b>Conclusion</b>: This study demonstrated the power of \"mining large EMR data + deep learning-based analysis,\" and the proposed analysis strategy and technique can be potentially broadly applicable. It provided convincing evidence of the comparative effectiveness of lumpectomy and mastectomy.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"327-346"},"PeriodicalIF":2.5,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/0a/be/yjbm_96_3_327.PMC10524818.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41156052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Racial Disparities in Invasive ICU Treatments Among Septic Patients: High Resolution Electronic Health Records Analysis from MIMIC-IV. 败血症患者侵入性ICU治疗中的种族差异:来自MIMIC-IV的高分辨率电子健康记录分析。
IF 2.7 3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-29 eCollection Date: 2023-09-01 DOI: 10.59249/WDJI8829
Sara Mohammed, João Matos, Matthieu Doutreligne, Leo Anthony Celi, Tristan Struja
{"title":"Racial Disparities in Invasive ICU Treatments Among Septic Patients: High Resolution Electronic Health Records Analysis from MIMIC-IV.","authors":"Sara Mohammed,&nbsp;João Matos,&nbsp;Matthieu Doutreligne,&nbsp;Leo Anthony Celi,&nbsp;Tristan Struja","doi":"10.59249/WDJI8829","DOIUrl":"10.59249/WDJI8829","url":null,"abstract":"<p><p><b>Background</b>: Low-resolution administrative databases can give biased results, whereas high-resolution, time-stamped variables from clinical databases like MIMIC-IV might provide nuanced insights. We evaluated racial-ethnic disparities in life-sustaining ICU-treatments (Invasive Mechanical Ventilation (IMV), Renal Replacement Therapy (RRT), and Vasopressors (VP)) among patients with sepsis. <b>Methods</b>: In this observational retrospective cohort study, patients fulfilling sepsis-3 criteria were categorized by treatment assignment within the first 4 days. The outcomes were treatment allocations. The likelihood of receiving treatment was calculated by race-ethnicity (Racial-ethnic group (REG) or White group (WG)) using 5-fold sub-sampling nested logistic regression and XGBoost. <b>Results</b>: In 23,914 admissions, 82% were White, 42% were women. REG were less likely to receive IMV across all eligibility days (day 1 odds ratio (OR) 0.87, 95% confidence interval (CI) 0.83-0.94, day 4 OR 0.80, 95% CI 0.72 - 0.87). There were no differences in RRT (day 1 OR 1.00, 95% CI 0.96-1.09, day 4 OR 1.00, 95% CI 0.94-1.06). REG were also less likely to be treated with VP at days 1 to 3 (day 1 OR 0.87, 95% CI 0.76-0.94), but not at day 4 (OR 0.95, 95% CI 0.87-1.01). These findings remained robust when relaxing eligibility criteria for treatment allocation. <b>Conclusion</b>: Our findings reveal significant disparities in the use of invasive life-saving ICU treatments among septic patients from racial and ethnic minority backgrounds, particularly with respect to IMV and VP use. These disparities underscore not only the need to address inequality in critical care settings, but also highlight the importance of high-resolution data.</p>","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"96 3","pages":"293-312"},"PeriodicalIF":2.7,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/78/ba/yjbm_96_3_293.PMC10524813.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41166958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Autonomy of the Living Cell, Driving Force of Evolution 活细胞的自主性,进化的驱动力
3区 工程技术
Yale Journal of Biology and Medicine Pub Date : 2023-09-09 DOI: 10.17352/jbm.000040
Ford Brian J
{"title":"Autonomy of the Living Cell, Driving Force of Evolution","authors":"Ford Brian J","doi":"10.17352/jbm.000040","DOIUrl":"https://doi.org/10.17352/jbm.000040","url":null,"abstract":"Conventional biologists and medical doctors conceptualize the body as divided into cells. It is construed as a bag of organs, with one of everything down the center, and two of everything down the sides. My alternative view is the body as a community of autonomous living cells whose choreographed cohesion gives rise to the phenomenon we know as the body. Science reduces multicellular life to the biochemical interplay of its components, and systems biology to a concatenation of subunits acting according to the laws of chemistry and physics. Current studies of living cells concentrate on the subcellular components since mitochondria were designated the “powerhouse of the cell” though they can be seen to move, migrate, and respond to stimuli. Although we understand cells in communities and the organelles within each cell, we ignore the lives lived by individual cells as they conduct themselves in heuristic (decision-making) and in motivating evolutionary progress. Here we review original observations on the behavior of living cells and conclude that they are essential drivers of coordinated community cohesion.","PeriodicalId":48617,"journal":{"name":"Yale Journal of Biology and Medicine","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136193777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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