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Objective: To evaluate the accuracy of two portable ultrasound machines (PUM) in assessing fetal biometry and estimated gestational age (EGA)., Methods: This was a secondary analysis of data from the Fetal Age Machine Learning Initiative, an observational study of pregnant women in the USA and Zambia. Each participant underwent ultrasound assessment by an experienced sonographer using both a high-specification ultrasound machine (HSUM) and a PUM (Butterfly iQ or Clarius C3) to measure fetal biometry and calculate EGA at each visit. By comparing paired PUM and HSUM scans, we estimated agreement between individual biometry measurements and aggregate gestational age estimates by reporting mean difference, intraclass correlation coefficient (ICC) and Bland-Altman plots, adjusting for trend., Results: Between April and December 2021, 818 participants contributed 1386 paired PUM-HSUM ultrasound investigations, of which 991 PUM scans were obtained using the Butterfly iQ device and 395 using the Clarius C3 device. Gestational age at scan ranged from 7 to 38 weeks. Compared with HSUM, the Butterfly iQ PUM had a mean difference of -0.20 (95% CI, -0.60 to 0.20) days in the first trimester and -0.68 (95% CI, -0.93 to -0.44) days in the second/third trimesters. Compared with HSUM, the Clarius C3 PUM had a mean difference of -0.47 (95% CI, -1.11 to 0.18) days in the first trimester and -1.67 (95% CI, -2.10 to -1.25) days in the second/third trimesters. ICCs were 0.989 or greater throughout. Increasing gestational age was associated with increasing error and absolute error in EGA and fetal biometry. Both PUM devices demonstrated a modest trend toward underestimation of EGA with advancing gestational age in second/third-trimester scans, compared with HSUM., Conclusion: The Butterfly iQ and Clarius C3 PUM devices were highly accurate in performing fetal biometry in a diverse population from the USA and Zambia. © 2023 International Society of Ultrasound in Obstetrics and Gynecology., (© 2023 International Society of Ultrasound in Obstetrics and Gynecology.)

Purpose: To evaluate the agreement between the measurements provided by a new optical biometer, the Aladdin, based on optical low-coherence interferometry (OLCI), and those provided by the most commonly used optical biometer (IOLMaster 500), based on partial-coherence interferometry (PCI)., Setting: Multicenter clinical trial., Design: Prospective evaluation of diagnostic test., Methods: In this study, 2 samples of adult patients were enrolled, 1 in the United States and the other in China. The U.S. group included a sample of consecutive patients scheduled for cataract surgery. The China group included a sample of healthy subjects with no cataracts. In both cases, only 1 eye of each patient was analyzed. Axial length (AL), corneal power (in diopters [D]) (K), anterior chamber depth (ACD) (corneal epithelium to lens), and corneal astigmatism were measured. All values were analyzed using a paired t test, the Pearson product-moment correlation coefficient (r), and Bland-Altman plots., Results: In the U.S. and China groups, the OLCI mean AL values did not show a statistically significant difference from PCI values and showed excellent agreement and correlation. On the contrary, OLCI measured a lower mean K (-0.14 D) and a deeper ACD measurements (U.S. +0.16 mm and China +0.05 mm). These differences were statistically significant (P < .0001). Vector analysis did not show a statistically significant difference in astigmatism measurements., Conclusions: Agreement between OLCI and PCI was good. However, the small but statistically significant differences in K and ACD measurements make constant optimization necessary when calculating the intraocular lens power using theoretical formulas., Financial Disclosure: Dr. Hoffer licenses the registered trademark name Hoffer to Carl Zeiss-Meditec (PCI), Haag-Streit (Lenstar), Movu (Argos), Oculus (Pentacam, AXL), Nidek (AL-Scan), Tomey (OA-2000), Topcon EU Visia Imaging (Aladdin), Ziemer (Galilei G6), and all A-scan biometer manufacturers. Dr. Shammas licenses his formulas to Carl Zeiss-Meditec (PCI), Haag-Streit (Lenstar), Nidek (AL-Scan), and Topcon EU (Visia Imaging) (Aladdin). None of the other authors has a financial or proprietary interest in any material or method mentioned., (Copyright © 2016 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.)

Objective: Telehealthcare has been used to provide healthcare service, and information technology infrastructure appears to be essential while providing telehealthcare service. Insufficiencies have been identified, such as lack of integration, need of accommodation of diverse biometric sensors, and accessing diverse networks as different houses have varying facilities, which challenge the promotion of telehealthcare. This study designs an information technology framework to strengthen telehealthcare delivery., Materials and Methods: The proposed framework consists of a system architecture design and a network transmission design. The aim of the framework is to integrate data from existing information systems, to adopt medical informatics standards, to integrate diverse biometric sensors, and to provide different data transmission networks to support a patient's house network despite the facilities. The proposed framework has been evaluated with a case study of two telehealthcare programs, with and without the adoption of the framework., Results: The proposed framework facilitates the functionality of the program and enables steady patient enrollments. The overall patient participations are increased, and the patient outcomes appear positive. The attitudes toward the service and self-improvement also are positive., Conclusions: The findings of this study add up to the construction of a telehealthcare system. Implementing the proposed framework further assists the functionality of the service and enhances the availability of the service and patient acceptances.

This special issue of Biodemography and Social Demography assesses the value to social science and health research of incorporating biomeasures in a social survey. The focus is on the Panel Study of Income Dynamics (PSID), an ongoing, nationally representative panel study of U.S. households. A brief description of the PSID and the features that make it a promising survey for biomeasures is provided along with an overview of each individual article. Seven of the nine articles cover a major health domain: fatness and obesity, metabolic syndrome and cardiovascular disease, infectious disease, inflammation and immune function and cardiovascular disease, daily stress exposure and reactivity, respiratory health, and genetics. These articles describe the scientific rationale for collecting data in each domain as well as the specific biological samples or measurements needed to assess the domain, potential respondent burden, ethical- and legal issues, fieldwork logistics, and costs. The final two articles address a pair of overarching issues: one provides international comparisons and perspectives and the other discusses ethical and legal concerns.

The inclusion of biomarkers in social surveys such as the Panel Study of Income Dynamics (PSID) has the potential to answer many elusive questions in social science and public health, including the much-studied relationship between socioeconomic status and health. This article reviews the potential inclusion of biomarkers of cardiovascular and metabolic risk in the PSID. We first discuss the considerable analytical benefits of adding these biomarkers to the PSID, including the exploration of life course hypotheses and the potential to test causal relationships between the social environment and biological systems. Next, we review evidence on the reliability of self-reports of cardiovascular and metabolic risk factors, concluding that the potential bias from relying on self-reports may be substantial. Based on evidence of biological importance as well as practical considerations of ease of in-home collection, our first tier of recommended biomarkers includes measured height, weight, waist and hip circumference, diastolic and systolic blood pressure, resting heart rate, total and high-density lipoprotein (HDL) cholesterol, glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and cystatin C. Additional markers of secondary priority are also discussed.

The marketability and viability of biometric technologies by companies marketing their own versions of pre-approved registered travel programmes have generated a number of controversies. Data were collected and analysed to formulate graphs, run regression and correlation analyses, and use Chi-square to formally test basic research propositions on a sample of 241 professionals in the Pittsburgh area. It was found that there was a significant relationship between the respondents' familiarity with new technology (namely web-enabled and internet sophistication) and knowledge of biometrics, in particular iris scans. Participants who frequently use the internet are more comfortable with innovative technology; although individuals with higher income levels have less trust in the government, it appeared that virtually everyone is concerned about trusting the government with their personal information. Healthcare professionals need to document the safety, CRM-related factors, and provide leadership in the international collaboration of biometric-related personal identification technologies, since they will be one of the main beneficiaries of the implementation of such technologies.

From the back office to the operating room, technology is transforming hospitals, making them more efficient and able to deliver leading-edge care. But one area remains stubbornly low tech: the nonclinical, routine interactions with patients. From registration to food service, some pioneering hospitals are now using IT to improve the patient experience.