medRxiv : the preprint server for health sciences最新文献

{"title":"Longitudinal Cognitive Recovery in Survivors of Critical Illness: Impact of Sepsis and Benzodiazepine Exposure.","authors":"Ruhi Sahu, Ruth-Ann Brown, Anthony S Bonavia","doi":"10.1101/2025.09.23.25336354","DOIUrl":"https://doi.org/10.1101/2025.09.23.25336354","url":null,"abstract":"<p><strong>Background: </strong>Post-critical illness cognitive dysfunction (PCICD) is a common and debilitating condition affecting survivors of critical illness. While sepsis has been implicated in poor cognitive outcomes, its independent contribution remains unclear due to multiple associated confounders in critical illness. This study aimed to characterize cognitive recovery trajectories over 12 months post-intensive care unit (ICU) and to evaluate the influence of sepsis and benzodiazepine exposure on cognitive outcomes.</p><p><strong>Methods: </strong>In this single-center, prospective cohort study, adult ICU survivors were assessed at 30 days, 3 months, 6 months, and 12 months post-discharge using the telephone-administered Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MoCA). Scores were standardized into <i>z-</i> scores for comparability. Mixed-effects models assessed changes over time and the effects of clinical covariates, including sepsis status and benzodiazepine exposure. Additionally, we investigated whether any one specific cognitive domain was disproportionally impaired by critical illness over time.</p><p><strong>Results: </strong>Of 197 eligible patients during the enrollment period, 77 (39%) completed at least one cognitive assessment. Standardized cognitive scores significantly improved over time, with the greatest gains observed within 6 months: +0.40 SD at 3 months (p = 0.041), +0.54 SD at 6 months (p = 0.016), and +0.49 SD at 12 months (p = 0.033) compared to scores at the time of acute illness. Sepsis status had no significant effect on recovery trajectory. No single cognitive domain was disproportionately affected by critical illness; instead, changes were observed in the overall score over time. Benzodiazepine exposure showed complex associations: longer duration (-0.24 SD/day, p = 0.008) and higher daily dose (-0.02 SD/unit, p = 0.006) were linked to worse cognition, while total cumulative dose was paradoxically associated with better scores (+0.03 SD/unit, p < 0.001), possibly reflecting confounding by indication or survival bias.</p><p><strong>Conclusions: </strong>ICU survivors experience gradual cognitive recovery over the first year, primarily within 6 months. Sepsis does not independently affect this trajectory. Benzodiazepine exposure, especially prolonged or high daily dosing, emerges as a modifiable risk factor for cognitive impairment, consistent with prior investigations of PCICD. These findings highlight the importance of sedation strategies and structured cognitive follow-up.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perioperative Wearable Device Features are associated with Moderate-to-Severe Chronic Pain after Surgery in the \"All of Us\" Research Program.","authors":"Wenyu Zhang, Mindy K Ross, Madelyn R Frumkin","doi":"10.1101/2025.09.23.25336489","DOIUrl":"10.1101/2025.09.23.25336489","url":null,"abstract":"<p><p>Chronic pain is a common and disabling condition affective over 50 million adults in the United States. Surgery may offer a critical opportunity to prevent chronic pain, as 10-35% of surgical patients develop new or worsening pain. However, prevention and treatment of chronic pain among surgical patients is hindered by a lack of reliable and clinically actionable biomarkers. Digital health technologies offer novel opportunities to develop and validate <i>digital biomarkers</i> of chronic pain among surgical patients. In this study, we leveraged data from the \"All of Us\" Research Program, which linked Electronic Health Record (EHR) data with participant's own Fitbit data. We identified participants who: 1) had a surgical procedure as indicated in the EHR; 2) had Fitbit data available 30 days before and/or after surgery; and 3) completed the Overall Health Questionnaire assessing pain intensity 3 months to 5 years after surgery. Our final cohort included 302 surgical patients, 29% of whom reported moderate-to-severe pain approximately 1.5 years after surgery. Among the domain-specific models, sleep features provided the best predictive performance, achieving an AUC of .722 in a held-out test set. The lowest AIC was observed in the stepwise model based on the subset of participants whose Fitbits provided sleep stage data (n = 244, AIC = 178.75, AUC = .649, sensitivity = 0.37, specificity = 0.87). Younger age (OR = 0.97; p = 0.048), lower preoperative step variability (OR = 0.56; p = 0.009), and higher preoperative variability in REM sleep proportion (OR = 1.62; p = 0.023) were associated with greater risk of moderate-to-severe pain approximately 1.5 years after surgery. Digital biomarkers derived from consumer wearable device data appear highly promising for improving prediction and understand of chronic postoperative pain.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gabapentin Treatment Patterns Among Older Patients After Hospital Discharge for Acute Ischemic Stroke.","authors":"Shuo Sun, Maria A Donahue, Rebeka Bustamante Rocha, Madhav Sankaranarayanan, Joseph P Newhouse, Sonia Hernandez-Diaz, Alexander C Tsai, Sebastien Haneuse, Lidia M V R Moura","doi":"10.1101/2025.09.23.25336477","DOIUrl":"10.1101/2025.09.23.25336477","url":null,"abstract":"<p><strong>Importance: </strong>Gabapentin is frequently prescribed off-label for pain management following an acute ischemic stroke. However, little is known about optimal gabapentin prescribing practices, such as appropriate treatment duration for specific indications, particularly off-label uses.</p><p><strong>Objective: </strong>We examined gabapentin treatment patterns among older adults who initiated gabapentin within 30 days of discharge from hospitalization for acute ischemic stroke.</p><p><strong>Design: </strong>This is an observational, retrospective study of existing administrative claims data of Medicare beneficiaries with acute ischemic stroke (AIS) hospitalizations.</p><p><strong>Setting: </strong>A national 20% random sample of US Medicare beneficiaries.</p><p><strong>Participants: </strong>Patients aged 65 years and older who were hospitalized for their first acute ischemic stroke between 2013 and 2021.</p><p><strong>Exposures: </strong>Gabapentin initiation within 30 days of discharge.</p><p><strong>Main outcomes and measures: </strong>A novel approach that combines a time-varying proportion of days covered, calculated every two months, with a latent class mixed model to identify and characterize gabapentin treatment patterns during the first 12 months after initiation, accounting for prescription overlap and hospitalizations. An 80% proportion of days covered threshold was applied within each interval to distinguish high versus low medication coverage.</p><p><strong>Results: </strong>The analytic cohort (N=1,628) had a mean age of 76.4 (IQR 70-82) years and was 60% female and 76.5% non-Hispanic White. The latent class mixed model identified three distinct gabapentin treatment patterns: 692 patients (42.5%) experienced rapid low medication coverage (proportion of days covered <80%) within two months after initiation; 96 patients (5.9%) experienced gradually declining medication coverage over 8 months after initiation; and 840 patients (51.6%) maintained high and stable medication coverage for at least one year.</p><p><strong>Conclusions and relevance: </strong>In this nationwide sample, half of older adults hospitalized for acute ischemic stroke and who initiated gabapentin within 30 days of discharge had gabapentin coverage for 12 months or longer after initiation.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485974/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cohort profile: A community-based prospective cohort study of Alzheimer's disease and related dementias in the Democratic Republic of Congo.","authors":"Jean Ikanga, Caterina Obenauf, Saranya Sundaram Patel, Megan Schwinne, Guy Gikelekele, Emmanuel Epenge, Japhet Magolu Potshi, Topina Tomadia, Julie Kazadi, Immaculee Kavugho, Giovanni Luamba Santolini, Francine Manyonga Sabowa, Brenda Matungu Musewu, Elipsis Mawisa, Joseph Phuati Tsangu, Francis Muena Kondo Beya, Samuel Mampunza, Lelo Mananga, Justin Bukabau, Charlotte E Teunissen, Thomas Karikari, Alden L Gross, Julio C Rojas, Alvaro Alonso","doi":"10.1101/2025.09.23.25336499","DOIUrl":"https://doi.org/10.1101/2025.09.23.25336499","url":null,"abstract":"<p><strong>Introduction: </strong>The <i>Étude du Vieillissement Cognitif et de Démence en République Démocratique du Congo</i> (Study of Cognitive Aging and Dementia in the Democratic Republic of Congo, EVCD-RDC) was launched in 2024 to characterize cultural, biological, and environmental risk factors of cognitive aging and dementia in Kinshasa.</p><p><strong>Methods: </strong>The study is enrolling 800 adults aged ≥65 years across four diagnostic groups (cognitively unimpaired, mild cognitive impairment, Alzheimer's disease [AD], and other dementias). Recruitment occurs through community and clinical settings. Assessments include neuropsychological testing, neurological examination, social determinants, biospecimen collection, and air pollution exposure, with follow-up every two years.</p><p><strong>Results: </strong>To date, 506 participants have been enrolled (mean age: 73.4 years; 59.3% women). Dementia cases had greater prevalence of hypertension and other comorbidities, more neuropsychiatric symptoms, higher rates of smoking and alcohol use, lower body weight, reduced educational attainment and resilience, and increased exposure to air pollution, war, traumatic experiences, and poverty. The internal consistency of cognitive measures ranged from 0.44 to 0.91.</p><p><strong>Discussion: </strong>EVCD-RDC establishes the first large-scale dementia cohort in French-speaking Sub-Saharan Africa, providing critical infrastructure and insights into risk factors for Alzheimer's disease and related dementias.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic liability to meniscus degeneration and its comorbidity patterns: a phenome-wide association study in the UK Biobank.","authors":"Dong-Gi Lee, Yonghyun Nam, Jaehyun Joo, Se-Hwan Lee, Jaeun Jung, Su Chin Heo, Dokyoon Kim","doi":"10.1101/2025.09.23.25336468","DOIUrl":"https://doi.org/10.1101/2025.09.23.25336468","url":null,"abstract":"<p><p>Meniscus degeneration is a common knee pathology causing pain, disability, and osteoarthritis. While mechanical factors are established, the contribution of inherited genetic liability to its systemic disease patterns remains unclear. We applied a polygenic risk score (PRS) for meniscus degeneration, derived from FinnGen genome-wide association study (GWAS) results to 323,999 UK Biobank participants and conducted a phenome-wide association study (PRS-PheWAS) across 962 clinical phenotypes. The PRS-PheWAS revealed significant associations beyond musculoskeletal traits, extending to metabolic, cardiovascular, psychiatric, and gastrointestinal domains, indicating broad shared genetic architecture. To support these findings, linkage disequilibrium score regression confirmed strong genetic correlations with osteoarthritis and related arthropathies, and genotype-tissue expression (GTEx) analysis highlighted tissue-specific expression of lead genes (e.g., GDF5, SOX5, BMP6) in connective and metabolic tissues. The results demonstrate that genetic liability to meniscus degeneration extends beyond the knee, sharing pathways with systemic conditions. This systemic genetic architecture underscores the need for integrative management approaches that combine orthopedic care with metabolic and lifestyle interventions.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486030/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fall Frequency, Risk Factors, and Outcomes in Parkinson's Disease: A Cross-Sectional Analysis.","authors":"Joaquin A Vizcarra, Kat Hefter, David-Erick Lafontant, Michael Tran Duong, Ashkan Ertefaie, Brian Litt, Dani S Bassett, Andrew Siderowf","doi":"10.1101/2025.08.05.25332959","DOIUrl":"10.1101/2025.08.05.25332959","url":null,"abstract":"<p><strong>Background: </strong>Falls are a major source of morbidity in Parkinson's disease (PD), yet their evolution over time remains unclear.</p><p><strong>Objectives: </strong>To compare fall risk and outcomes among PD, prodromal alpha-synucleinopathy, (PAS) and healthy controls (HC); estimate fall frequency across PD progression; and characterize clinical features of PD faller subgroups.</p><p><strong>Methods: </strong>We analyzed fall-related outcomes in the Parkinson's Progression Markers Initiative. Yearly rates of rare and frequent falls were estimated by time since diagnosis. Unique PD participants were grouped as never, rare, or frequent fallers. Clinical variables included motor, cognitive, behavioral, sleep, and autonomic measures. Outcomes included injuries and healthcare utilization. Regression models adjusted for age, sex, and disease duration, with Benjamini-Hochberg correction.</p><p><strong>Results: </strong>Across 6,977 visits from 3,100 participants (937 PD, 1,926 PAS, 237 HC), PD participants had higher odds of falling than PAS (OR=1.66, 95% CI [1.46-1.87]) and HC (OR=4.03, 95% CI [3.14-5.23]). PD participants were also more likely to report fall-related injuries and healthcare use than PAS (OR=1.70, 1.71) and HC (OR=3.26, 3.81). Falls occurred in 15.5% of visits at diagnosis and 69.2% after 14 years, increasing across Neuronal Synuclein Disease-Integrated Staging System (NSD-ISS) stages. Frequent fallers had longer disease duration, higher NSD-ISS, and worse clinical profiles. Women were more likely to fall than men (46.1% vs 34.9%, p=0.002) despite milder symptoms.</p><p><strong>Conclusion: </strong>Falls and related morbidity increase with disease duration and NSD-ISS. Risk reflects sex and motor and non-motor factors, supporting a multifactorial model. Fall frequency may represent a practical marker of progression and guide prevention strategies in PD.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486038/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anticoagulant Benefit in Subclinical Atrial Fibrillation Accounting for Competing Risks: A Reanalysis of the ARTESIA Trial.","authors":"Shao-Wei Lo, Darae Ko, Dae Hyun Kim, Long H Ngo, Daniel E Singer, Sachin J Shah","doi":"10.1101/2025.09.19.25335927","DOIUrl":"https://doi.org/10.1101/2025.09.19.25335927","url":null,"abstract":"<p><strong>Background: </strong>The ARTESIA trial showed apixaban reduced the relative hazard of stroke/systemic embolism in subclinical atrial fibrillation (SCAF; 6 min-24 hr) by 37%, but did not report absolute risk reduction (ARR). The reported Kaplan-Meier analysis and incidence rate reduction did not account for the competing risk of death or 24-hour AF events. We reanalyzed ARTESIA accounting for competing risks to determine the ARR of apixaban vs. aspirin.</p><p><strong>Methods: </strong>Individual time-to-event and time-to-censoring data were extracted from the published Kaplan-Meier curve. ARTESIA classified deaths and 24-hour AF events as censoring events. We probabilistically reclassified them to competing events to estimate the ARR accurately. We used the Aalen-Johansen estimator to estimate the cumulative risk of stroke/systemic embolism, accounting for competing events.</p><p><strong>Results: </strong>After reclassification of deaths and 24-hour AF to competing events, there were 1111 censoring and 852 competing events in the apixaban arm, and 1100 censoring and 816 competing events in the aspirin arm. At 6 years, the ARR was 2.09% (95% CI -0.17 to 4.34) when death and 24-hour AF events were treated as censoring events vs. 1.68% (95% CI 0.46 to 2.89) when they were treated as competing events.</p><p><strong>Conclusion: </strong>In SCAF, apixaban reduced the 6-year risk of stroke/systemic embolism by 1.68%, a 20% lower benefit when accounting for competing risks. Accounting for competing risks is essential to accurately measure the benefit of anticoagulants for SCAF.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486023/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of a White Matter Reference Region on the Relationship between Florbetapir PET Measurements of Amyloid Plaque Deposition and Measurements of Cognitive Decline.","authors":"V Bhargava, M Wang, Y Chen, J Luo, M Weiner, S Landau, W Jagust, M Sabbagh, Y Su, E M Reiman, K Chen","doi":"10.1101/2025.09.19.25336123","DOIUrl":"https://doi.org/10.1101/2025.09.19.25336123","url":null,"abstract":"<p><p>The objective of this study was to systematically investigate both cross-sectional and longitudinal associations between amyloid PET tracer, Florbetapir (FBP), and cognition when different reference regions of interest - whole cerebellum versus white matter - are used for Standardized Uptake Value Ratio (SUVR) semi-quantification of amyloid beta deposition. Baseline and 2.2±0.4 year follow-up Florbetapir PET scans from 1,238 mild AD dementia, mild cognitive impairment (MCI), and cognitively unimpaired (CU) participants from AD Neuroimaging Initiative (ADNI) were used to characterize and compare the impact of using a cerebral white matter versus whole cerebellar reference region on cross-sectional and longitudinal relationships between florbetapir SUVR indicators of amyloid plaque deposition and measurements of cognitive or clinical decline (ADAS-Cog-13, CDR-Sum Boxes, and AVLT-total) after covarying for age and education. In both cross-sectional and longitudinal comparisons, florbetapir PET measurements of amyloid plaque deposition using the cerebral white matter reference region were more closely related to each measure of cognitive or clinical decline in the aggregate mild dementia, MCI and CU group (P<1.3E-06). This study supports the potential use of a cerebral white matter reference region in the detection and tracking of amyloid plaque deposition using florbetapir PET. Additional studies are needed to clarify the generalizability of findings to other amyloid PET ligands.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485991/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Review of Spatial Epidemiological Modeling Approaches Applied During the COVID-19 Pandemic.","authors":"Kayode Oshinubi, Ye Chen, Eck Doerry, Esma S Gel, Crystal Hepp, Tim Lant, Sanjay Mehrotra, Samantha Sabo, Joseph Mihaljevic","doi":"10.1101/2025.09.24.25336493","DOIUrl":"https://doi.org/10.1101/2025.09.24.25336493","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;A wide range of epidemiological modeling approaches have been applied to the SARS-CoV-2 pan-demic, which presents an opportunity to assess common approaches applied to specific research questions. Spatial models interrogate how heterogeneities and host movement dynamics influence local and regional patterns of dis-ease, issues that were of great interest for understanding and controlling SARS-CoV-2.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Here we present a systematic review of spatial epidemiological modeling approaches of SARS-CoV-2. We describe common themes and highlight unique strategies, providing a foundation for researchers to devise spatial models most appropriate for future pathogens and epidemics. Our review also categorizes the research questions that were addressed with spatial models, highlights parameter estimation techniques, and describes the cyber infrastructure used for model development.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a systematic review using Web of Science and a standardized set of key-words, followed by thorough examination of abstracts and full texts to determine which studies met our inclusion criteria. To guide our description and comparisons of models, we developed a Geography, Population, Movement (GPM) framework that conceptualizes the interactions between three distinct subcomponents of any spatial model. The geographic model represents the physical arena in which the model is implemented, the intra-population model describes the transmission and disease processes that occur within distinct spatial units of the geography, and the movement model describes the algorithms that dictate how hosts move among spatial units within the geography.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The search identified a total of 193 articles, of which 109 were included in our review. The most abundant intra-population modeling methods were agent-based (47.7%) and compartmental modeling (29.4%) approaches. Movement models ranged in complexity, with the most complex models implementing commuter movement among many points of interest in the geographic arena, which were sometimes parameterized by fine-scale mobility data. Geographic models ranged from describing microcosms, such as single classrooms, all the way up to multi-country models. Of the 63.3% of models studies that specified the programming language used, we detected ten different languages, with Matlab and Python being the most frequent, although only 30.6% of studies provided open-access code for their models. We also described eight specialized software systems that were used to construct agent-based or compartment models of COVID-19.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our review identified and characterized a variety of spatial modeling strategies and software that were usefully employed to address many relevant epidemiological questions for COVID-19. Future research is needed to quantitatively assess which modeling approaches are most appropria","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Disease Prognosis via Diagnostic Knowledge Preservation: A Sequential Learning Approach.","authors":"Haresh Rengaraj Rajamohan, Yanqi Xu, Weicheng Zhu, Richard Kijowski, Kyunghyun Cho, Krzysztof J Geras, Narges Razavian, Cem M Deniz","doi":"10.1101/2025.09.22.25336414","DOIUrl":"10.1101/2025.09.22.25336414","url":null,"abstract":"<p><p>Accurate disease prognosis is essential for patient care but is often hindered by the lack of long-term data. This study explores deep learning training strategies that utilize large, accessible diagnostic datasets to pretrain models aimed at predicting future disease progression in knee osteoarthritis (OA), Alzheimer's disease (AD), and breast cancer (BC). While diagnostic pretraining improves prognostic task performance, naive fine-tuning for prognosis can cause 'catastrophic forgetting,' where the model's original diagnostic accuracy degrades, a significant patient safety concern in real-world settings. To address this, we propose a sequential learning strategy with experience replay. We used cohorts with knee radiographs, brain MRIs, and digital mammograms to predict 4-year structural worsening in OA, 2-year cognitive decline in AD, and 5-year cancer diagnosis in BC. Our results showed that diagnostic pretraining on larger datasets improved prognosis model performance compared to standard baselines, boosting both the Area Under the Receiver Operating Characteristic curve (AUROC) (e.g., Knee OA external: 0.77 vs 0.747; Breast Cancer: 0.874 vs 0.848) and the Area Under the Precision-Recall Curve (AUPRC) (e.g., Alzheimer's Disease: 0.752 vs 0.683). Additionally, a sequential learning approach with experience replay achieved prognostic performance comparable to dedicated single-task models (e.g., Breast Cancer AUROC 0.876 vs 0.874) while also preserving diagnostic ability. This method maintained high diagnostic accuracy (e.g., Breast Cancer Balanced Accuracy 50.4% vs 50.9% for a dedicated diagnostic model), unlike simpler multitask methods prone to catastrophic forgetting (e.g., 37.7%). Our findings show that leveraging large diagnostic datasets is a reliable and data-efficient way to enhance prognostic models while maintaining essential diagnostic skills.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}