Tag: statistics

Ophthalmic Epidemiol. 2024 Mar 20:1-10. doi: 10.1080/09286586.2024.2321892. Online ahead of print.

ABSTRACT

PURPOSE: To evaluate the prevalence and risk factors of age-related macular degeneration (AMD) in the Korean population.

METHODS: In this cross-sectional study based on the Korea National Health and Nutrition Examination Survey (2017-2020) data 13,737 participants aged ≥ 40 years with assessable fundus images were included. The prevalence and risk factors of AMD were evaluated. The prevalence of early AMD, geographic atrophy (GA), and neovascular AMD were also assessed. Logistic regression analyses were used to identify risk factors.

RESULTS: The prevalence (95% confidence interval [CI]) of AMD was 13.94% (13.15-14.72). The prevalence (95% CI) of early AMD, GA, and neovascular AMD was 13.07% (12.29-13.85), 0.26% (0.17-0.35), and 0.61% (0.47-0.75), respectively. The prevalence increased with age; it was 3.61%, 11.33%, 20.31%, 31.37%, and 33.98% in participants in their 40s, 50s, 60s, 70s, and ≥ 80 years, respectively. In multivariate analysis, AMD was positively associated with older age (p < 0.001; odds ratio [OR], 1.08; 95% CI, 1.07-1.09), male sex (p = 0.014; OR, 1.27; 95% CI, 1.05-1.53), and lower degree of education (p < 0.001; OR, 1.36 (for junior high school graduates); 95% CI, 1.12-1.65).

CONCLUSIONS: AMD was detected in approximately one-third of individuals aged ≥ 70 years, thus indicating that AMD is a common disease among older Koreans. Regular fundus examinations in populations with risk factors for AMD as well as education on methods to prevent or delay AMD progression, such as the Mediterranean diet, are necessary.

PMID:38507599 | DOI:10.1080/09286586.2024.2321892

Am J Speech Lang Pathol. 2024 Mar 20:1-30. doi: 10.1044/2024_AJSLP-23-00366. Online ahead of print.

ABSTRACT

PURPOSE: Selecting vocabulary for preliterate individuals who use augmentative and alternative communication presents multiple challenges, as the number of symbols provided must be balanced with cognitive, motoric, and other needs. Prioritizing certain types of vocabulary thus becomes a necessity. For example, prioritizing core vocabulary-that is, words that are commonly used across a group of people and contexts-is a common practice that attempts to address some of these issues. However, most core vocabulary research to date has narrowly focused on individual word counts, ignoring other critical aspects of language development such as how vocabulary aligns with typical development and how children use core and fringe vocabulary within their utterances.

METHOD: Descriptive and inferential statistics were used to analyze 112 transcripts to describe how typically developing toddlers (aged 2.5 years) use core and fringe vocabulary within their utterances, in reference to a range of commonly used core vocabulary lists.

RESULTS: Results indicated that the proportion of the toddlers’ utterances that consisted of only core, only fringe, or core + fringe vocabulary varied dramatically depending on the size of the core vocabulary list used, with smaller core lists yielding few “core-only” utterances. Furthermore, utterances containing both core and fringe vocabulary were both grammatically and semantically superior to utterances containing only core or only fringe vocabulary, as evidenced by measures such as mean length of utterance and total number of words.

CONCLUSION: Thus, relying on word frequency counts is an insufficient basis for selecting vocabulary for aided preliterate communicators.

PMID:38507571 | DOI:10.1044/2024_AJSLP-23-00366

JMIR Public Health Surveill. 2024 Mar 20;10:e46903. doi: 10.2196/46903.

ABSTRACT

BACKGROUND: The COVID-19 pandemic necessitated public health policies to limit human mobility and curb infection spread. Human mobility, which is often underestimated, plays a pivotal role in health outcomes, impacting both infectious and chronic diseases. Collecting precise mobility data is vital for understanding human behavior and informing public health strategies. Google’s GPS-based location tracking, which is compiled in Google Mobility Reports, became the gold standard for monitoring outdoor mobility during the pandemic. However, indoor mobility remains underexplored.

OBJECTIVE: This study investigates in-home mobility data from ecobee’s smart thermostats in Canada (February 2020 to February 2021) and compares it directly with Google’s residential mobility data. By assessing the suitability of smart thermostat data, we aim to shed light on indoor mobility patterns, contributing valuable insights to public health research and strategies.

METHODS: Motion sensor data were acquired from the ecobee “Donate Your Data” initiative via Google’s BigQuery cloud platform. Concurrently, residential mobility data were sourced from the Google Mobility Report. This study centered on 4 Canadian provinces-Ontario, Quebec, Alberta, and British Columbia-during the period from February 15, 2020, to February 14, 2021. Data processing, analysis, and visualization were conducted on the Microsoft Azure platform using Python (Python Software Foundation) and R programming languages (R Foundation for Statistical Computing). Our investigation involved assessing changes in mobility relative to the baseline in both data sets, with the strength of this relationship assessed using Pearson and Spearman correlation coefficients. We scrutinized daily, weekly, and monthly variations in mobility patterns across the data sets and performed anomaly detection for further insights.

RESULTS: The results revealed noteworthy week-to-week and month-to-month shifts in population mobility within the chosen provinces, aligning with pandemic-driven policy adjustments. Notably, the ecobee data exhibited a robust correlation with Google’s data set. Examination of Google’s daily patterns detected more pronounced mobility fluctuations during weekdays, a trend not mirrored in the ecobee data. Anomaly detection successfully identified substantial mobility deviations coinciding with policy modifications and cultural events.

CONCLUSIONS: This study’s findings illustrate the substantial influence of the Canadian stay-at-home and work-from-home policies on population mobility. This impact was discernible through both Google’s out-of-house residential mobility data and ecobee’s in-house smart thermostat data. As such, we deduce that smart thermostats represent a valid tool for facilitating intelligent monitoring of population mobility in response to policy-driven shifts.

PMID:38506901 | DOI:10.2196/46903

JMIR Public Health Surveill. 2024 Mar 20;10:e50407. doi: 10.2196/50407.

ABSTRACT

BACKGROUND: The Ministry of Health in Côte d’Ivoire and the International Training and Education Center for Health at the University of Washington, funded by the United States President’s Emergency Plan for AIDS Relief, have been collaborating to develop and implement the Open-Source Enterprise-Level Laboratory Information System (OpenELIS). The system is designed to improve HIV-related laboratory data management and strengthen quality management and capacity at clinical laboratories across the nation.

OBJECTIVE: This evaluation aimed to quantify the effects of implementing OpenELIS on data quality for laboratory tests related to HIV care and treatment.

METHODS: This evaluation used a quasi-experimental design to perform an interrupted time-series analysis to estimate the changes in the level and slope of 3 data quality indicators (timeliness, completeness, and validity) after OpenELIS implementation. We collected paper and electronic records on clusters of differentiation 4 (CD4) testing for 48 weeks before OpenELIS adoption until 72 weeks after. Data collection took place at 21 laboratories in 13 health regions that started using OpenELIS between 2014 and 2020. We analyzed the data at the laboratory level. We estimated odds ratios (ORs) by comparing the observed outcomes with modeled counterfactual ones when the laboratories did not adopt OpenELIS.

RESULTS: There was an immediate 5-fold increase in timeliness (OR 5.27, 95% CI 4.33-6.41; P<.001) and an immediate 3.6-fold increase in completeness (OR 3.59, 95% CI 2.40-5.37; P<.001). These immediate improvements were observed starting after OpenELIS installation and then maintained until 72 weeks after OpenELIS adoption. The weekly improvement in the postimplementation trend of completeness was significant (OR 1.03, 95% CI 1.02-1.05; P<.001). The improvement in validity was not statistically significant (OR 1.34, 95% CI 0.69-2.60; P=.38), but validity did not fall below pre-OpenELIS levels.

CONCLUSIONS: These results demonstrate the value of electronic laboratory information systems in improving laboratory data quality and supporting evidence-based decision-making in health care. These findings highlight the importance of OpenELIS in Côte d’Ivoire and the potential for adoption in other low- and middle-income countries with similar health systems.

PMID:38506899 | DOI:10.2196/50407

JMIR Mhealth Uhealth. 2024 Mar 20;12:e51236. doi: 10.2196/51236.

ABSTRACT

BACKGROUND: Patient engagement attrition in mobile health (mHealth) remote patient monitoring (RPM) programs decreases program benefits. Systemic disparities lead to inequities in RPM adoption and use. There is an urgent need to understand patients’ experiences with RPM in the real world, especially for patients who have stopped using the programs, as addressing issues faced by patients can increase the value of mHealth for patients and subsequently decrease attrition.

OBJECTIVE: This study sought to understand patient engagement and experiences in an RPM mHealth intervention in lung transplant recipients.

METHODS: Between May 4, 2020, and November 1, 2022, a total of 601 lung transplant recipients were enrolled in an mHealth RPM intervention to monitor lung function. The predictors of patient engagement were evaluated using multivariable logistic and linear regression. Semistructured interviews were conducted with 6 of 39 patients who had engaged in the first month but stopped using the program, and common themes were identified.

RESULTS: Patients who underwent transplant more than 1 year before enrollment in the program had 84% lower odds of engaging (odds ratio [OR] 0.16, 95% CI 0.07-0.35), 82% lower odds of submitting pulmonary function measurements (OR 0.18, 95% CI 0.09-0.33), and 78% lower odds of completing symptom checklists (OR 0.22, 95% CI 0.10-0.43). Patients whose primary language was not English had 78% lower odds of engaging compared to English speakers (OR 0.22, 95% CI 0.07-0.67). Interviews revealed 4 prominent themes: challenges with devices, communication breakdowns, a desire for more personal interactions and specific feedback with the care team about their results, understanding the purpose of the chat, and understanding how their data are used.

CONCLUSIONS: Care delivery and patient experiences with RPM in lung transplant mHealth can be improved and made more equitable by tailoring outreach and enhancements toward non-English speakers and patients with a longer time between transplant and enrollment. Attention to designing programs to provide personalization through supplementary provider contact, education, and information transparency may decrease attrition rates.

PMID:38506896 | DOI:10.2196/51236

Int J Artif Organs. 2024 Mar 20:3913988241239198. doi: 10.1177/03913988241239198. Online ahead of print.

ABSTRACT

OBJECTIVE: Our study aimed to compare the outcomes of COVID-19 patients who met a low-risk inclusion criteria for veno-venous extra corporeal membrane oxygenation (VV ECMO) with those who did not meet criteria due to higher risk but were subsequently cannulated.

METHODS: This was a retrospective observational cohort study that included adult patients who were placed on VV ECMO for COVID-19 related acute respiratory distress syndrome (ARDS) at a tertiary care academic medical center. The primary outcome was the association between the low-risk criteria and mortality. The patients met the criteria if they met EOLIA severe ARDS criteria, no absolute contraindications (age > 60 years, BMI > 55 kg/m², mechanical ventilation (MV) duration >7 days, irreversible neurologic damage, chronic lung disease, active malignancy, or advanced multiorgan dysfunction), and had three or less relative contraindications (age > 50 years, BMI > 45 kg/m², comorbidities, MV duration > 4 days, acute kidney injury, receiving vasopressors, hospital LOS > 14 days, or COVID-19 diagnosis > 4 weeks).

RESULTS: Sixty-five patients were included from March 2020 through March 2022. Patients were stratified into low-risk or high-risk categories. The median Sequential Organ Failure Assessment score was 7 and the median PaO2/FiO2 ratio was 44 at the time of ECMO cannulation. The in-hospital mortality was 47.8% in the low-risk group and 69.0% in the high-risk group (p = 0.096).

CONCLUSION: There was not a statistically significant difference in survival between low-risk patients and high-risk patients; however, there was a trend toward higher survival in the lower-risk group.

PMID:38506888 | DOI:10.1177/03913988241239198

J Glaucoma. 2024 Mar 19. doi: 10.1097/IJG.0000000000002372. Online ahead of print.

ABSTRACT

PRCIS: Elevated corneal hysteresis (CH) and resistance factor (CRF) in obese and over-weight children imply weight’s effect on corneal biomechanics. Increased Goldmann-correlated intraocular pressure (IOPg) in obese indicates glaucoma risk, emphasizing screening for IOP, retinal changes.

PURPOSE: To evaluate the effect of obesity on corneal biomechanics, retinal nerve fibre layer (RNFL) and central macular thicness (CMT) in children.

PATIENTS AND METHODS: In this prospective, cross-sectional, comparative study, 146 eyes of normal-weight, over-weight, and obese children aged between 6 to 17 years were evaluated. The IOPg, corneal compensated IOP (IOPcc), CH, CRF and the average retinal nerve fiber layer (RNFL), average cup-to-disk ratio (c/d), central macular thickness (CMT) were measured by Ocular Response Analyser and Spectral-Domain Optical Coherence Tomography (SD-OCT), respectively.

RESULTS: There was no statistically significant difference regarding age, sex, IOPcc, average RNFL thickness, c/d ratio, and CMT among the groups (P≥0.05). The IOPg was significantly higher in obese children compared to normal-weight children, while CH and CRF values were significantly higher in both obese and over-weight children compared to healthy ones (P<0.05). There was a positive correlation between BMI percentile and IOPg, CH, and CRF values.

CONCLUSION: In our study, higher IOPg, corneal hysteresis, and corneal resistance factor values suggest that obese children could be potential candidates for glaucoma. Therefore, it would be appropriate to screen them for IOP and retinal alterations. On the other hand, further investigations with larger sample sizes and longer follow-up periods are needed to eliminate the risk of glaucoma in obese children.

PMID:38506830 | DOI:10.1097/IJG.0000000000002372

JAMA Psychiatry. 2024 Mar 20. doi: 10.1001/jamapsychiatry.2024.0171. Online ahead of print.

ABSTRACT

IMPORTANCE: Suicide rates in the US increased by 35.6% from 2001 to 2021. Given that most individuals die on their first attempt, earlier detection and intervention are crucial. Understanding modifiable risk factors is key to effective prevention strategies.

OBJECTIVE: To identify distinct suicide profiles or classes, associated signs of suicidal intent, and patterns of modifiable risks for targeted prevention efforts.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the 2003-2020 National Violent Death Reporting System Restricted Access Database for 306 800 suicide decedents. Statistical analysis was performed from July 2022 to June 2023.

EXPOSURES: Suicide decedent profiles were determined using latent class analyses of available data on suicide circumstances, toxicology, and methods.

MAIN OUTCOMES AND MEASURES: Disclosure of recent intent, suicide note presence, and known psychotropic usage.

RESULTS: Among 306 800 suicide decedents (mean [SD] age, 46.3 [18.4] years; 239 627 males [78.1%] and 67 108 females [21.9%]), 5 profiles or classes were identified. The largest class, class 4 (97 175 [31.7%]), predominantly faced physical health challenges, followed by polysubstance problems in class 5 (58 803 [19.2%]), and crisis, alcohol-related, and intimate partner problems in class 3 (55 367 [18.0%]), mental health problems (class 2, 53 928 [17.6%]), and comorbid mental health and substance use disorders (class 1, 41 527 [13.5%]). Class 4 had the lowest rates of disclosing suicidal intent (13 952 [14.4%]) and leaving a suicide note (24 351 [25.1%]). Adjusting for covariates, compared with class 1, class 4 had the highest odds of not disclosing suicide intent (odds ratio [OR], 2.58; 95% CI, 2.51-2.66) and not leaving a suicide note (OR, 1.45; 95% CI, 1.41-1.49). Class 4 also had the lowest rates of all known psychiatric illnesses and psychotropic medications among all suicide profiles. Class 4 had more older adults (23 794 were aged 55-70 years [24.5%]; 20 100 aged ≥71 years [20.7%]), veterans (22 220 [22.9%]), widows (8633 [8.9%]), individuals with less than high school education (15 690 [16.1%]), and rural residents (23 966 [24.7%]).

CONCLUSIONS AND RELEVANCE: This study identified 5 distinct suicide profiles, highlighting a need for tailored prevention strategies. Improving the detection and treatment of coexisting mental health conditions, substance and alcohol use disorders, and physical illnesses is paramount. The implementation of means restriction strategies plays a vital role in reducing suicide risks across most of the profiles, reinforcing the need for a multifaceted approach to suicide prevention.

PMID:38506817 | DOI:10.1001/jamapsychiatry.2024.0171

JAMA Netw Open. 2024 Mar 4;7(3):e243109. doi: 10.1001/jamanetworkopen.2024.3109.

ABSTRACT

IMPORTANCE: Platform trials have become increasingly common, and evidence is needed to determine how this trial design is actually applied in current research practice.

OBJECTIVE: To determine the characteristics, progression, and output of randomized platform trials.

EVIDENCE REVIEW: In this systematic review of randomized platform trials, Medline, Embase, Scopus, trial registries, gray literature, and preprint servers were searched, and citation tracking was performed in July 2022. Investigators were contacted in February 2023 to confirm data accuracy and to provide updated information on the status of platform trial arms. Randomized platform trials were eligible if they explicitly planned to add or drop arms. Data were extracted in duplicate from protocols, publications, websites, and registry entries. For each platform trial, design features such as the use of a common control arm, use of nonconcurrent control data, statistical framework, adjustment for multiplicity, and use of additional adaptive design features were collected. Progression and output of each platform trial were determined by the recruitment status of individual arms, the number of arms added or dropped, and the availability of results for each intervention arm.

FINDINGS: The search identified 127 randomized platform trials with a total of 823 arms; most trials were conducted in the field of oncology (57 [44.9%]) and COVID-19 (45 [35.4%]). After a more than twofold increase in the initiation of new platform trials at the beginning of the COVID-19 pandemic, the number of platform trials has since declined. Platform trial features were often not reported (not reported: nonconcurrent control, 61 of 127 [48.0%]; multiplicity adjustment for arms, 98 of 127 [77.2%]; statistical framework, 37 of 127 [29.1%]). Adaptive design features were only used by half the studies (63 of 127 [49.6%]). Results were available for 65.2% of closed arms (230 of 353). Premature closure of platform trial arms due to recruitment problems was infrequent (5 of 353 [1.4%]).

CONCLUSIONS AND RELEVANCE: This systematic review found that platform trials were initiated most frequently during the COVID-19 pandemic and declined thereafter. The reporting of platform features and the availability of results were insufficient. Premature arm closure for poor recruitment was rare.

PMID:38506807 | DOI:10.1001/jamanetworkopen.2024.3109

JAMA Netw Open. 2024 Mar 4;7(3):e243201. doi: 10.1001/jamanetworkopen.2024.3201.

ABSTRACT

IMPORTANCE: The emergence and promise of generative artificial intelligence (AI) represent a turning point for health care. Rigorous evaluation of generative AI deployment in clinical practice is needed to inform strategic decision-making.

OBJECTIVE: To evaluate the implementation of a large language model used to draft responses to patient messages in the electronic inbox.

DESIGN, SETTING, AND PARTICIPANTS: A 5-week, prospective, single-group quality improvement study was conducted from July 10 through August 13, 2023, at a single academic medical center (Stanford Health Care). All attending physicians, advanced practice practitioners, clinic nurses, and clinical pharmacists from the Divisions of Primary Care and Gastroenterology and Hepatology were enrolled in the pilot.

INTERVENTION: Draft replies to patient portal messages generated by a Health Insurance Portability and Accountability Act-compliant electronic health record-integrated large language model.

MAIN OUTCOMES AND MEASURES: The primary outcome was AI-generated draft reply utilization as a percentage of total patient message replies. Secondary outcomes included changes in time measures and clinician experience as assessed by survey.

RESULTS: A total of 197 clinicians were enrolled in the pilot; 35 clinicians who were prepilot beta users, out of office, or not tied to a specific ambulatory clinic were excluded, leaving 162 clinicians included in the analysis. The survey analysis cohort consisted of 73 participants (45.1%) who completed both the presurvey and postsurvey. In gastroenterology and hepatology, there were 58 physicians and APPs and 10 nurses. In primary care, there were 83 physicians and APPs, 4 nurses, and 8 clinical pharmacists. The mean AI-generated draft response utilization rate across clinicians was 20%. There was no change in reply action time, write time, or read time between the prepilot and pilot periods. There were statistically significant reductions in the 4-item physician task load score derivative (mean [SD], 61.31 [17.23] presurvey vs 47.26 [17.11] postsurvey; paired difference, -13.87; 95% CI, -17.38 to -9.50; P < .001) and work exhaustion scores (mean [SD], 1.95 [0.79] presurvey vs 1.62 [0.68] postsurvey; paired difference, -0.33; 95% CI, -0.50 to -0.17; P < .001).

CONCLUSIONS AND RELEVANCE: In this quality improvement study of an early implementation of generative AI, there was notable adoption, usability, and improvement in assessments of burden and burnout. There was no improvement in time. Further code-to-bedside testing is needed to guide future development and organizational strategy.

PMID:38506805 | DOI:10.1001/jamanetworkopen.2024.3201