Category: Statistics

Rom J Intern Med. 2024 Jan 5. doi: 10.2478/rjim-2024-0001. Online ahead of print.

ABSTRACT

INTRODUCTION: Harmful alcohol consumption is one of the leading risk factors for global disease burden and injury condition, causing death and disability early in life, with over 3 million deaths worldwide every year. Alcoholic hepatitis (AH) is a clinical syndrome characterized by hepatic failure with recent onset of jaundice, consequence of a heavy chronic alcohol drinking. The disease severity ranges from mild to severe cases, with high short-term mortality. Individual variety regarding disease outcome and therapeutic response complicates the prognosis stratification. Thus, novel parameters and continuously sought for a better disease outcome assessment.

AIMS AND OBJECTIVES: To highlight new parameters that accurately assess 30-day mortality (short-term) in patients with AH and to develop a new severity score that uses readily available parameters accessible to any clinician.

MATERIALS AND METHODS: This is a prospective study on patients diagnosed with AH between 2022-2023. We identified 70 patients with AH who met the National Institute on Alcohol Abuse and Alcoholism (NIAAA) criteria for diagnosis after exclusion of patients with severe comorbidities that could influence disease outcome. Clinical and paraclinical parameters were assessed at least on admission and day 7. Mortality at 30-day was considered the endpoint. The database was composed using Microsoft Excel (Microsoft Corporation) and the data was analyzed using SPSS Statistics version 26 (IBM Corporation).

RESULTS: A total of 70 patients were included in the study with a mortality at 30-days of 22.9% (n=16). The independent variables associated with increased short-term mortality identified using the univariate analysis were: fever, infection, esophageal varices, prothrombin time PT, INR, total bilirubin, CRP, LDH and CHI (creatinine height index). Using multivariate regression we determined a novel prognostic score, with criterion for retaining variable being p<0.05. Total bilirubin day 7, CRP, PT, fever and CHI resulted after the analysis and were included into a new mortality score. Our Prognostic Model Score obtained an area under the ROC of 0.950 (95% CI: 0.890-0.980, p<0.001), with a cut-off value of 13.75 (Sn=87.5%, Sp=91%). Regarding the consecrated prognostic scores, MDF and Lille score obtained good AUROCs=0.839 and 0.881, respectively (p<0.000), with cut-off values comparable with literature (MDF=34.35 vs 32) and (Lille=0.475 vs 0.450). The discriminatory power for ABIC (p=0.58), GAHS (p=0.16), MELD-Na (p=0.61) was not significant.

CONCLUSION: We obtained a new prognostic score for the assessment of 30-day mortality in AH that includes markers of inflammation (CRP, fever) and markers of sarcopenia (CHI) along parameters of hepatic disfunction (total bilirubin and PT). Amongst consecrated prognostic models, MDF and Lille scores were representative for our study, while ABIC, GAHS and MELD-Na did not attain statistical significance. Our score is unique by the addition of CRP and this could prove to be a useful tool in AH severity stratification.

PMID:38180800 | DOI:10.2478/rjim-2024-0001

JMIR Hum Factors. 2024 Jan 5;11:e47755. doi: 10.2196/47755.

ABSTRACT

BACKGROUND: A future shortage of physicians, especially in general practice, will result in an increasing workload for health care providers as a whole. Therefore, it is important to optimize patient-encounter processes to increase time efficiency related to visits. Utilizing digital tools to record patients’ medical histories prior to a consultation offers great potential to achieve this goal. The collected information can be stored into the practice’s electronic medical record, allowing for the general practitioner to review structured information of the patients’ complaints and related medical history beforehand, thereby saving time during the encounter. However, the low usability of new digital developments in this setting often hinders implementation.

OBJECTIVE: The aim of this study was to evaluate the usability of an app designed for medical history taking in general practice to capture the patients’ perspective.

METHODS: Between November 2021 and January 2022, we recruited 406 patients with acute complaints in one out-of-hour urgent care and seven general practice clinics. These study participants used the app during their waiting time and subsequently assessed its usability by completing the System Usability Scale (SUS), a robust and well-established 10-question survey measuring the perceived usability of products and technologies. Additionally, we collected general participant information, including age, sex, media usage, health literacy, and native language. Descriptive and inferential statistics were applied to identify patient characteristics associated with low or high SUS scores.

RESULTS: We analyzed data from 397 patients (56.7% female, 43.3% male). The mean total SUS score was 77.8 points; 54.4% (216/397) of participants had SUS scores of 80 points or higher, indicating high usability of the app. In a multiple linear regression predicting SUS score, male sex and higher age (65 years or older) were significantly negatively associated with the SUS score. Conversely, a higher health literacy score and German as the native language were significantly positively associated with the SUS score.

CONCLUSIONS: Usability testing based on the SUS anticipates successful implementation of the app. However, not all patients will easily adapt to utilizing the app, as exemplified by the participants of older age in this study who reported lower perceived usability. Further research should examine these groups of people, identify the exact problems in operating such an app, and provide targeted solutions.

TRIAL REGISTRATION: German Clinical Trials Register World Health Organization Trial Registration Data Set DRKS00026659; https://trialsearch.who.int/Trial2.aspx?TrialID=DRKS00026659.

PMID:38180798 | DOI:10.2196/47755

J Med Internet Res. 2024 Jan 5;26:e45020. doi: 10.2196/45020.

ABSTRACT

BACKGROUND: Telemedicine has demonstrated its potential in alleviating the unbalanced distribution of medical resources across different regions. Henan, a province in China with a population of approximately 100 million, is especially affected by a health care divide. The province has taken a proactive step by establishing a regional collaborative platform for telemedicine services provided by top-tier provincial hospitals.

OBJECTIVE: We aim to identify the key factors that influence the current operationalization and effectiveness of telemedicine services in Henan province. The insights gained from this study will serve as valuable references for enhancing the efficient operation of telemedicine platforms in low- and middle-income regions.

METHODS: We analyzed service reports from the performance management system of telemedicine services in Henan province throughout 2020. Using descriptive statistics and graphical methods, we examined key influencing factors, such as management competency; device configuration; and hospital capability, capacity, and service efficacy, across hospitals at 2 different tiers. In addition, we used generalized linear models and multiple linear regression models to identify key operational factors that significantly affect the service volume and efficacy of 2 major telemedicine services, namely teleconsultation and tele-education.

RESULTS: Among the 89 tier 3 hospitals and 97 tier 2 hospitals connected to the collaborative telemedicine platform, 65 (73%) and 55 (57%), respectively, have established standardized management procedures for telemedicine services. As the primary delivery method for telemedicine services, 90% (80/89) of the tier 3 hospitals and 94% (91/97) of the tier 2 hospitals host videoconferencing consultations through professional hardware terminals rather than generic computers. Teleconsultation is the dominant service type, with an average annual service volume per institution of 173 (IQR 37-372) and 60 (IQR 14-271) teleconsultations for tier 3 and tier 2 hospitals, respectively. Key factors influencing the service volume at each hospital include available funding, management competency, the number of connected upper tiers, and the number of professional staff. After receiving teleconsultations from tier 3 (65/89, 73%) and tier 2 (61/97, 63%) hospitals, patients reported significant improvements in their medical conditions. In addition, we observed that service efficacy is positively influenced by management competency, financial incentives, the number of connected upper or lower tiers, and the involvement of participating medical professionals.

CONCLUSIONS: Telemedicine has become increasingly popular in Henan province, with a notable focus on teleconsultation and tele-education services. Despite its popularity, many medical institutions, especially tier 2 hospitals, face challenges related to management competency. In addition to enhancing the effectiveness of existing telemedicine services, health care decision-makers in Henan province and other low- and middle-income regions should consider expanding the service categories, such as including remote emergency care and telesurgery, which have promise in addressing crucial health care needs in these regions.

PMID:38180795 | DOI:10.2196/45020

JMIR Med Educ. 2024 Jan 5;10:e51247. doi: 10.2196/51247.

ABSTRACT

BACKGROUND: The use of artificial intelligence (AI) in medicine not only directly impacts the medical profession but is also increasingly associated with various potential ethical aspects. In addition, the expanding use of AI and AI-based applications such as ChatGPT demands a corresponding shift in medical education to adequately prepare future practitioners for the effective use of these tools and address the associated ethical challenges they present.

OBJECTIVE: This study aims to explore how medical students from Germany, Austria, and Switzerland perceive the use of AI in medicine and the teaching of AI and AI ethics in medical education in accordance with their use of AI-based chat applications, such as ChatGPT.

METHODS: This cross-sectional study, conducted from June 15 to July 15, 2023, surveyed medical students across Germany, Austria, and Switzerland using a web-based survey. This study aimed to assess students’ perceptions of AI in medicine and the integration of AI and AI ethics into medical education. The survey, which included 53 items across 6 sections, was developed and pretested. Data analysis used descriptive statistics (median, mode, IQR, total number, and percentages) and either the chi-square or Mann-Whitney U tests, as appropriate.

RESULTS: Surveying 487 medical students across Germany, Austria, and Switzerland revealed limited formal education on AI or AI ethics within medical curricula, although 38.8% (189/487) had prior experience with AI-based chat applications, such as ChatGPT. Despite varied prior exposures, 71.7% (349/487) anticipated a positive impact of AI on medicine. There was widespread consensus (385/487, 74.9%) on the need for AI and AI ethics instruction in medical education, although the current offerings were deemed inadequate. Regarding the AI ethics education content, all proposed topics were rated as highly relevant.

CONCLUSIONS: This study revealed a pronounced discrepancy between the use of AI-based (chat) applications, such as ChatGPT, among medical students in Germany, Austria, and Switzerland and the teaching of AI in medical education. To adequately prepare future medical professionals, there is an urgent need to integrate the teaching of AI and AI ethics into the medical curricula.

PMID:38180787 | DOI:10.2196/51247

JMIR Med Educ. 2024 Jan 5;10:e51148. doi: 10.2196/51148.

ABSTRACT

BACKGROUND: The United States Medical Licensing Examination (USMLE) has been critical in medical education since 1992, testing various aspects of a medical student’s knowledge and skills through different steps, based on their training level. Artificial intelligence (AI) tools, including chatbots like ChatGPT, are emerging technologies with potential applications in medicine. However, comprehensive studies analyzing ChatGPT’s performance on USMLE Step 3 in large-scale scenarios and comparing different versions of ChatGPT are limited.

OBJECTIVE: This paper aimed to analyze ChatGPT’s performance on USMLE Step 3 practice test questions to better elucidate the strengths and weaknesses of AI use in medical education and deduce evidence-based strategies to counteract AI cheating.

METHODS: A total of 2069 USMLE Step 3 practice questions were extracted from the AMBOSS study platform. After including 229 image-based questions, a total of 1840 text-based questions were further categorized and entered into ChatGPT 3.5, while a subset of 229 questions were entered into ChatGPT 4. Responses were recorded, and the accuracy of ChatGPT answers as well as its performance in different test question categories and for different difficulty levels were compared between both versions.

RESULTS: Overall, ChatGPT 4 demonstrated a statistically significant superior performance compared to ChatGPT 3.5, achieving an accuracy of 84.7% (194/229) and 56.9% (1047/1840), respectively. A noteworthy correlation was observed between the length of test questions and the performance of ChatGPT 3.5 (ρ=-0.069; P=.003), which was absent in ChatGPT 4 (P=.87). Additionally, the difficulty of test questions, as categorized by AMBOSS hammer ratings, showed a statistically significant correlation with performance for both ChatGPT versions, with ρ=-0.289 for ChatGPT 3.5 and ρ=-0.344 for ChatGPT 4. ChatGPT 4 surpassed ChatGPT 3.5 in all levels of test question difficulty, except for the 2 highest difficulty tiers (4 and 5 hammers), where statistical significance was not reached.

CONCLUSIONS: In this study, ChatGPT 4 demonstrated remarkable proficiency in taking the USMLE Step 3, with an accuracy rate of 84.7% (194/229), outshining ChatGPT 3.5 with an accuracy rate of 56.9% (1047/1840). Although ChatGPT 4 performed exceptionally, it encountered difficulties in questions requiring the application of theoretical concepts, particularly in cardiology and neurology. These insights are pivotal for the development of examination strategies that are resilient to AI and underline the promising role of AI in the realm of medical education and diagnostics.

PMID:38180782 | DOI:10.2196/51148

Fam Pract. 2024 Jan 5:cmad124. doi: 10.1093/fampra/cmad124. Online ahead of print.

ABSTRACT

BACKGROUND: Microalbuminuria is an early indicator for renal and cardiovascular diseases, especially among patients with diabetes mellitus (DM) and hypertension (HTN). We determined the prevalence and the factors associated with microalbuminuria among patients with type 2 DM and/or HTN in the urban areas of the Puducherry district in India.

METHODS: We included 225 patients aged 40-69 years with DM and/or HTN from a non-communicable diseases (NCDs) survey conducted during 2019-2020 in the urban areas of Puducherry district. The prevalence of microalbuminuria and various biological risk factors of NCDs were assessed as per the WHO STEPS methodology. The prevalence of microalbuminuria was presented as proportions (95% CI), and the adjusted prevalence ratio (aPR) was estimated using weighted forward stepwise generalized linear modelling. P-value ≤0.05 was considered statistically significant.

RESULTS: The mean (SD) age of the patients was 54 (11) years. Over one-third (38.2%) (95% CI: 31.6-44.4) of patients with DM and/or HTN had microalbuminuria. The prevalence was highest among those having both DM and HTN 48% (95% CI: 37-59), followed by those having only DM 40.6% (95% CI: 29-52.2) and only HTN 27.7% (95% CI: 18.1-38.6). The prevalence of microalbuminuria was twice (aPR = 2.1, 95% CI: 1.1-3.9) higher among women and 2.4 times (95% CI: 1.12-5.1) higher among those having both DM and HTN as compared to those with only HTN.

CONCLUSION: The prevalence of microalbuminuria among patients with DM and/or HTN is concerningly high. Population-based screening for microalbuminuria, especially among women and those having both DM and HTN, needs to be undertaken in the urban areas of Puducherry district.

PMID:38180781 | DOI:10.1093/fampra/cmad124

Invest Ophthalmol Vis Sci. 2024 Jan 2;65(1):17. doi: 10.1167/iovs.65.1.17.

ABSTRACT

PURPOSE: Studies have reported different numbers of spatial frequency channels for chromatic and achromatic vision. To resolve the difference, we performed factor analysis, a multivariate modeling technique, on population data of achromatic and chromatic sensitivity. In addition, we included resampling and visualization methods to evaluate models from factor analysis. These routines are complex but widely useful. Therefore we have archived our analysis routines by building smCSF, an open-source software package in R (https://smin95.github.io/dataviz/).

METHODS: Data of 103 normally-sighted adults were analyzed. They included blue-yellow, red-green, and achromatic contrast sensitivity. To obtain the confidence interval of relevant statistical parameters, factor analysis was performed using a resampling method. Then exploratory models were developed. We then performed model selections by fitting them against the empirical data and quantifying the quality of the fits.

RESULTS: During the exploratory factor analysis, different statistical tests supported different factor models. These could partially be reasons for why there have been conflicting reports. However, after the confirmatory analysis, we found that a model that included two spatial channels was adequate to approximate the chromatic sensitivity data, whereas that with three channels was so for the achromatic sensitivity data.

CONCLUSIONS: Our findings provide novel insights about the spatial channels for chromatic and achromatic contrast sensitivity from population data. Also, the analysis and visualization routines have been archived in a computational package to boost the transparency and replicability of science.

PMID:38180771 | DOI:10.1167/iovs.65.1.17

JAMA Netw Open. 2024 Jan 2;7(1):e2350424. doi: 10.1001/jamanetworkopen.2023.50424.

ABSTRACT

IMPORTANCE: Fertility status is a marker for future health, and infertility has been associated with risk for later cancer and diabetes, but associations with midlife cardiovascular health (CVH) in female individuals remain understudied.

OBJECTIVE: To evaluate the association of infertility history with CVH at midlife (approximately age 50 years) among parous individuals.

DESIGN, SETTING, AND PARTICIPANTS: Project Viva is a prospective cohort study of pregnant participants enrolled between 1999 and 2002 who delivered a singleton live birth in the greater Boston, Massachusetts, area. Infertility history was collected at a midlife visit between 2017 and 2021, approximately 18 years after enrollment. Data analysis was performed from January to June 2023.

EXPOSURES: The primary exposure was any lifetime history of infertility identified by self-report, medical record, diagnosis, or claims for infertility treatment.

MAIN OUTCOMES AND MEASURES: The American Heart Association’s Life’s Essential 8 (LE8) is a construct for ranking CVH that includes scores from 0 to 100 (higher scores denote better health status) in 4 behavioral (diet, physical activity, sleep, and smoking status) and 4 biomedical (body mass index, blood pressure, blood lipids, and glycemia) domains to form an overall assessment of CVH. Associations of a history of infertility (yes or no) with mean LE8 total, behavioral, biomedical, and blood biomarker (lipids and glycemia) scores were examined, adjusting for age at outcome (midlife visit), race and ethnicity, education, household income, age at menarche, and perceived body size at age 10 years.

RESULTS: Of 468 included participants (mean [SD] age at the midlife visit, 50.6 [5.3] years) with exposure and outcome data, 160 (34.2%) experienced any infertility. Mean (SD) LE8 scores were 76.3 (12.2) overall, 76.5 (13.4) for the behavioral domain, 76.0 (17.5) for the biomedical domain, and 78.9 (19.2) for the blood biomarkers subdomain. In adjusted models, the estimated overall LE8 score at midlife was 2.94 points lower (95% CI, -5.13 to -0.74 points), the biomedical score was 4.07 points lower (95% CI, -7.33 to -0.78 points), and the blood subdomain score was 5.98 points lower (95% CI, -9.71 to -2.26 points) among those with vs without history of infertility. The point estimate also was lower for the behavioral domain score (β = -1.81; 95% CI, -4.28 to 0.66), although the result was not statistically significant.

CONCLUSIONS AND RELEVANCE: This cohort study of parous individuals found evidence for an association between a history of infertility and lower overall and biomedical CVH scores. Future study of enhanced cardiovascular preventive strategies among those who experience infertility is warranted.

PMID:38180761 | DOI:10.1001/jamanetworkopen.2023.50424

JAMA Netw Open. 2024 Jan 2;7(1):e2350495. doi: 10.1001/jamanetworkopen.2023.50495.

ABSTRACT

IMPORTANCE: Physicians play an important role in assessing patients’ ability to drive. There is a dearth of peer-reviewed information on policies regarding physician reporting of medically impaired drivers.

OBJECTIVE: To investigate state reporting requirements and the availability of confidentiality and legal immunity for physicians who report medically impaired drivers.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study was conducted from November 1 to 30, 2022, in 3 rounds. First, all 50 US states’ Department of Motor Vehicle (DMV) websites were systematically reviewed. Second, DMV staff from each state were surveyed via telephone. Third, each state’s legal codes for driver licensing were reviewed.

MAIN OUTCOMES AND MEASURES: Outcome measures included the percentage of states with mandatory and voluntary reporting policies, reporting instructions on DMV websites, anonymous reporting options, and legal immunity for reporting physicians, in addition to characteristics of states’ mandatory reporting policies (ie, types of medical conditions that require reporting) and policies surrounding the confidentiality of reports. The data were analyzed using descriptive statistics.

RESULTS: One-third of state DMV websites (17 [34%]) lacked instructions regarding physician reporting. Six states had mandatory reporting requirements; 4 of these states only required reporting of conditions characterized by lapses of consciousness. Only 3 states (6%) accepted anonymous reports, and 7 states (14%) deemed physician reports of medically impaired drivers confidential without exception. Nearly one-third of states (15 [30%]) deemed reports by physicians confidential, with the exception that reported drivers could find out who reported them if they asked for a copy of the reporting form. Most states (37 [74%]) had statutes that protected physicians from liability related to reporting medically impaired drivers.

CONCLUSIONS AND RELEVANCE: This cross-sectional study of state reporting requirements regarding medically impaired drivers found many differences in state policies regarding mandatory reporting and the conditions that require reporting. There was also limited availability of online reporting instructions, anonymous reporting options, and legal protections for reporting physicians.

PMID:38180760 | DOI:10.1001/jamanetworkopen.2023.50495

JAMA Netw Open. 2024 Jan 2;7(1):e2350630. doi: 10.1001/jamanetworkopen.2023.50630.

ABSTRACT

IMPORTANCE: Xylazine is increasingly reported in street drugs and fatal overdoses in the US, yet state-level data are limited, hampering local public health responses.

OBJECTIVE: To gather available state-level data on xylazine involvement in overdose deaths and in forensic drug reports.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study was a secondary analysis of 2019 to 2022 data from the National Forensic Laboratory Information System (NFLIS), National Center for Health Statistics, and individual states’ medical examiner or public health agency reports. Data were analyzed from August to October 2023.

EXPOSURE: State.

MAIN OUTCOMES AND MEASURES: Yearly xylazine-related overdose deaths per 100 000 residents; xylazine NFLIS drug reports, both per 100 000 residents and as a percentage of all NFLIS drug reports (from samples of drugs seized by law enforcement and analyzed by NFLIS-participating laboratories).

RESULTS: A total of 63 state-years were included in analyses of mortality rates, while 204 state-years were included in analyses of NFLIS reports. According to the publicly available data compiled in this study, at least 43 states reported at least 1 xylazine-related overdose death from 2019 to 2022, yet yearly totals of xylazine-related deaths were available for only 21 states. Of states with data available, xylazine-involved overdose death rates were highest in Vermont (10.5 per 100 000 residents) and Connecticut (9.8 per 100 000 residents) in 2022. In 2019, 16 states had zero xylazine reports included in NFLIS reports; in 2022, only 2 states had zero xylazine reports and all but 3 states had recorded an increase in xylazine’s representation in NFLIS reports. In 2022, xylazine represented 16.17% of all NFLIS reports in Delaware and between 5.95% and 7.00% of NFLIS reports in Connecticut, Maryland, District of Columbia, New Jersey, and Rhode Island, yet less than 1.0% of NFLIS reports in 35 different states.

CONCLUSIONS AND RELEVANCE: In this cross-sectional study of publicly available data on fatal overdoses and drugs analyzed by forensic laboratories, xylazine’s reported presence in overdose deaths and forensic reports was concentrated in the eastern US yet extended across the country to encompass nearly all states. In spite of xylazine’s geographic reach, yearly state-level numbers of xylazine-related overdose deaths were publicly available for less than half of all states.

PMID:38180756 | DOI:10.1001/jamanetworkopen.2023.50630