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In recent years, there has been a growing interest in the investigation of very old individuals. However, various challenges arise when collecting data from this age group. Given potential health and cognitive impairments and the difficulty of retrieving accurate self-reported data, involving individuals knowledgeable of the target person as proxy respondents are an invaluable solution. The primary goal of this study is to explore the association between proxy-centenarian relationship and item nonresponse, a pivotal data quality measure. We used data from the phone study conducted within SWISS100, a study on centenarians in Switzerland, focusing on a subsample of 94 centenarians and 75 proxy respondents. We compared characteristics of centenarians who provided self-reports with those interviewed through proxy respondents using descriptive analyses, and Firth's regression models to investigate the association of different types of proxies (children, other relatives, and non-relatives) with item nonresponse. We noted differences between centenarians participating themselves in interviews and those represented by proxies, observing higher proportions of men and private home residents in the self-report group. There was a low prevalence of item nonresponse among proxy respondents. Proxy type significantly impacted item nonresponse, particularly with non-relatives showing notably higher unanswered question rates. A robust association between non-relatives as proxies and increased item nonresponse persisted even when controlling for potential confounding factors. This study enhances the understanding of data quality, particularly item nonresponse, and highlights the impact of the proxy-centenarian relationship when studying the oldest-old. The findings stress the importance of carefully choosing proxy respondents, preferably children, to improve data quality and inclusivity for those individuals hard to reach or to interview. Future research should investigate various data quality indicators and rely on larger samples to enhance the representation and methodological rigour in the study of the oldest-old.

Background Tracking the evolution of scientific knowledge is challenging due to the scale and complexity of the biomedical literature. Neurosyphilis is a clinically complex and historically stigmatized condition that remains difficult to diagnose and manage. Its underexplored literature offers an ideal test case to evaluate digital methods for mapping research trends and identifying knowledge gaps. We aim to assess how large language models (LLMs), network analysis, and interrupted time series analysis (ITSA) can be combined to automate literature classification and examine how knowledge of neurosyphilis has evolved. Methods We systematically searched Web of Science, Embase, PubMed Central, the Cochrane Library, and Lens for records on neurosyphilis published until December 31, 2024. We included records with available titles and abstracts in which GPT-4o mini was identified as being focused primarily on syphilis or neurosyphilis. Eligible records were classified into 23 research fields via LLM-based prompts. Network analysis visualized changes in research structures over time, and the ITSA assessed associations between publication trends and major clinical or technological milestones. Results Among the 14 934 retrieved records, 4 646 met the inclusion criteria. LLM-based classification showed high repeatability (agreement = 99·67%, 95% CI 99·47–99·80; Cohen’s κ = 0·99, 95% CI 0·96–1·00). Biomedical, Clinical, and Health sciences were the most common domains. Network analysis revealed a shift from dense, discipline-specific clusters to larger interdisciplinary structures. ITSA revealed significant increases in publication activity following the introduction of penicillin G, HIV emergence, genome sequencing of Treponema pallidum , and the rise of digital dissemination platforms. Conclusions Combining LLMs with bibliometric and network methods provides a scalable framework for analyzing large-scale biomedical literature. When applied to neurosyphilis, the approach revealed links between research activity and clinical and technological advances. In addition to this case study, the method could support meta-research and inform evidence-based decision-making across other complex medical conditions.

Abstract Altfhough every second child born after the year 2000 is expected to become a centenarian, little is known about what characterizes life at age 100. This is also the case for Switzerland, one of the countries with the highest life expectancy world-wide. In this presentation, we will report findings from SWISS100, the first nation-wide centenarian study in Switzerland. During the COVID-19 pandemic, we conducted a telephone study with centenarians and a family member as proxy informant, to investigate specific characteristics and challenges of centenarians. Centenarians were identified through the national address registry. A total of 171 centenarian cases were included in the SWISS100 Phone Study, including reports from 96 centenarians and 102 proxy respondents (mostly children). Centenarians were on average 102 years old, with a range of 100 to 110 years; 75% were women and 25% were men. One third of the centenarians had received basic education only, one third had completed an apprenticeship and about one third had higher education. Most of them lived in institutions (63%). Of those living in private, about half lived alone, one fourth lived with a child, and 12% still lived with a spouse. The majority was widowed. About 85% had children. Over half of the centenarians reported good to excellent subjective health; at the same time, over 70% of the centenarians indicated to often experience health restrictions. Those still able to communicate had high well-being and notable psychological strengths. In sum, findings demonstrate vulnerability but also psychological resilience in Swiss centenarians.

Abstract Depressive symptoms (DS) are prevalent among older adults (WHO, 2021). However, data on DS appear to be scarce in centenarians. In addition, DS may have been aggravated by the COVID-19 pandemic, especially in centenarians who may have been more susceptible to the negative consequences of pandemic restrictions. Thus, as part of the SWISS100 study (Jopp et al., 2023), we measured DS in centenarians living in Switzerland during the COVID-19 pandemic. Randomly selected centenarians from across the country and their proxies were invited to participate in a telephone interview between December 2020 and June 2022. The study sample was composed of 171 centenarians, with a mean age of 101.8 (SD=1.7) years; 128 (74.9%) participants were female and 63 (36.8%) lived at home. DS were assessed via five selected items of the Geriatric Depression Scale (Sheikh and Yesavage, 1986). The mean DS score was 1.6 (SD=1.6). Considering a cut-off ≥2 (Brañez-Condorena et al., 2021), 75 (43.9%) centenarians were screened positive for possible depression. Further analysis indicated that women had a higher level of DS, and that nursing home residents were more depressed than community-dwelling centenarians. Thus, our study suggests that almost half of the centenarians may have presented with relevant DS during the pandemic in Switzerland, which is notably higher than in other studies. DS in centenarians should be screened systematically, not less so in the context of a health crisis. Depressive symptomatology in the very old is highly relevant for successful professional care and needs further investigation to develop best practice.