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The dataset is predominantly of European ancestry, providing a valuable tool for researchers and precision medicine developers to investigate disease etiology and risk stratification.", "tags": [ "medRxiv", "Genomics" ] }, { "brief": { "actionable_takeaways": [ "Implement local SLM-based pipelines for EHR feature extraction to maintain data sovereignty while scaling clinical research." ], "facts": [ { "label": "Accuracy", "value": "93.8" }, { "label": "Sensitivity", "value": "83.6" }, { "label": "Specificity", "value": "96.6" } ], "key_insights": [ "Patients progressing to acute pyelonephritis showed higher feature burdens (71.3% vs 55.8%) compared to non-progressing controls.", "Local deployment avoids cloud API costs and data privacy concerns associated with commercial LLMs." ], "tldr": "A local, privacy-preserving hybrid SLM-regex pipeline enables accurate extraction of uncoded clinical features from primary care EHR narratives.", "unresolved": [ "Lower sensitivity for narratively complex descriptions." ], "why_it_matters": "Provides a scalable, secure framework for clinical informatics teams to extract structured data from unstructured EHR notes without cloud dependency." }, "claim_count": 3, "claims": [ { "claim_id": "1790099949001698179", "claim_ref": "c1653233619ff64eaaceffeb88a0b4c1d87c252c", "snapshot": "{\"claim_id\":\"1790099949001698179\",\"claim_text\":\"The hybrid pipeline achieved 93.8% accuracy and 96.6% specificity in extracting uncoded UTI features from real-world EHR narratives.\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"Phi4-mini\",\"role\":\"mentioned\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Monitor this performance benchmark for local SLM-based EHR extraction tools in clinical informatics workflows.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "The hybrid pipeline achieved 93.8% accuracy and 96.6% specificity in extracting uncoded UTI features from real-world EHR narratives." }, { "claim_id": "1790099949003268694", "claim_ref": "ad9dd7404e131045dcba0a902e897d2da366f4f2", "snapshot": "{\"claim_id\":\"1790099949003268694\",\"claim_text\":\"Patients progressing to acute pyelonephritis exhibited a higher clinical feature burden (71.3%) compared to non-progressing controls (55.8%).\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"Catalonia\",\"role\":\"mentioned\",\"type\":\"place\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Use this clinical feature burden as a potential risk stratification signal for pyelonephritis in primary care EHR monitoring.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Patients progressing to acute pyelonephritis exhibited a higher clinical feature burden (71.3%) compared to non-progressing controls (55.8%)." }, { "claim_id": "1790099949007158795", "claim_ref": "ecf7066ff990bdf8e112fe80d930eaf920e05b99", "snapshot": "{\"claim_id\":\"1790099949007158795\",\"claim_text\":\"Local deployment of the Phi4-mini model within institutional firewalls eliminates data privacy risks and API costs associated with cloud-hosted LLMs.\",\"claim_type\":\"analysis\",\"confidence\":\"stated\",\"entities\":[{\"name\":\"Phi4-mini\",\"role\":\"mentioned\",\"type\":\"topic\"}],\"evidence\":\"derived\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Evaluate this deployment strategy for health systems seeking to reduce operational costs and maintain data sovereignty in AI implementation.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Local deployment of the Phi4-mini model within institutional firewalls eliminates data privacy risks and API costs associated with cloud-hosted LLMs." } ], "entities": [], "headline": "Uncoded Clinical Features from Multilingual Electronic Health Records in Catalonia: Development and Validation Study", "home_domain": null, "manifest_id": "1790099573510787246", "published_at": "2026-09-22", "significance": "medium", "source_channel": "medRxiv - Official Health AI Informatics", "source_name": "medrxiv-health-ai-informatics", "source_url": "https://medrxiv.org/content/10.64898/2026.09.16.26363030v1.full", "stream_id": null, "stream_ids": [ "17779881004510530" ], "summary": "Researchers developed a local, privacy-preserving pipeline using the Phi4-mini SLM and regular expressions to extract six uncoded UTI clinical features from primary care EHR narratives in Catalonia. The model demonstrated high performance, with 93.8% accuracy and 96.6% specificity in real-world clinician validation. This approach offers a cost-effective, secure alternative to cloud-based LLMs for clinical informatics and EHR-based research.", "tags": [ "Artificial Intelligence", "medRxiv" ] }, { "brief": { "actionable_takeaways": [ "Incorporate temporal behavioral changes into infectious disease transmission models to improve the accuracy of intervention evaluation.", "Public health surveillance teams should account for illness-associated contact reductions when modeling outbreak dynamics." ], "facts": [ { "label": "Household member cohort size", "value": "709" }, { "label": "Contact increase factor", "value": "2.0" } ], "key_insights": [ "Transmission models that ignore illness-associated behavioral changes produce significantly different outbreak trajectories.", "Empirical data from 1,000 cases and 709 household members provides a framework for refining infectious disease modeling." ], "tldr": "Acute infection triggers significant, time-dependent reductions in social contact that, if omitted, lead to substantial errors in infectious disease transmission modeling.", "unresolved": [ "No open-source code or dataset repository explicitly linked in the abstract.", "Generalizability of findings beyond the northwestern United States remains to be validated." ], "why_it_matters": "Public health modelers and policy teams must integrate these behavioral dynamics to avoid overestimating or underestimating the impact of non-pharmaceutical interventions." }, "claim_count": 3, "claims": [ { "claim_id": "1790122000927126256", "claim_ref": "1e0751327d7ecd7266b6df8d76dd04b41a08e87b", "snapshot": "{\"claim_id\":\"1790122000927126256\",\"claim_text\":\"Infected individuals substantially reduce social contacts during peak illness.\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"SickMix\",\"role\":\"subject\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Monitor for behavioral parameters in infectious disease transmission models; this confirms that peak illness is a period of reduced transmission potential.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Infected individuals substantially reduce social contacts during peak illness." }, { "claim_id": "1790122000966929392", "claim_ref": "530a5d543f863ae93563b27b74a937e66710b841", "snapshot": "{\"claim_id\":\"1790122000966929392\",\"claim_text\":\"Weighted mean number of contacts increased 2.0-fold (95% CI, 1.8-2.2) over the two-week follow-up period post-peak illness.\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"SickMix\",\"role\":\"subject\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Use this effect size to calibrate transmission models and adjust contact rate assumptions in post-infection recovery phases.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Weighted mean number of contacts increased 2.0-fold (95% CI, 1.8-2.2) over the two-week follow-up period post-peak illness." }, { "claim_id": "1790122000993156530", "claim_ref": "d45395ffd6d27b117a2a52904898fb7a17946e75", "snapshot": "{\"claim_id\":\"1790122000993156530\",\"claim_text\":\"Simulated outbreak trajectories and intervention effectiveness estimates differ substantially between models that account for temporal contact reductions and those that do not.\",\"claim_type\":\"analysis\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"SickMix\",\"role\":\"subject\",\"type\":\"topic\"}],\"evidence\":\"derived\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Alert public health modelers to potential bias in intervention evaluation if behavioral dynamics are omitted from simulation frameworks.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Simulated outbreak trajectories and intervention effectiveness estimates differ substantially between models that account for temporal contact reductions and those that do not." } ], "entities": [], "headline": "SickMix: Temporal Changes in Social Contact Patterns among People with Acute Infection and Their Close Contacts", "home_domain": null, "manifest_id": "1790119201499390250", "published_at": "2026-09-22", "significance": "high", "source_channel": "medRxiv - Official Epidemiology Public Health", "source_name": "medrxiv-epidemiology-public-health", "source_url": "https://medrxiv.org/content/10.64898/2026.09.21.26362162v1.full", "stream_id": null, "stream_ids": [ "17779881004510530" ], "summary": "This prospective longitudinal study of 1,000 medically attended acute gastroenteritis and respiratory infection cases quantifies how social contact patterns shift during acute illness. The data reveal a significant reduction in social contacts during peak illness, followed by a 2.0-fold increase over the two-week recovery period. These findings are essential for public-health agents and modelers, as failing to account for these behavioral dynamics leads to inaccurate transmission trajectories and biased evaluations of intervention effectiveness.", "tags": [ "medRxiv", "Public Health", "Acute Gastroenteritis" ] }, { "brief": { "actionable_takeaways": [ "Hospital administrators should prioritize interventions targeting staffing ratios and error-reporting workflows to improve safety culture." ], "facts": [ { "label": "Overall patient safety culture score", "value": "3.72" }, { "label": "Sample size", "value": "96" } ], "key_insights": [ "Highest scoring domains: Communication about Errors, Management Support for Patient Safety, and Teamwork.", "Allied health professionals reported more favorable safety culture perceptions compared to nursing staff." ], "tldr": "A cross-sectional assessment of an Indian tertiary hospital reveals a positive overall safety culture but identifies critical operational deficits in staffing and error response.", "unresolved": [ "No longitudinal data to assess safety culture trends", "Limited to a single tertiary care center" ], "why_it_matters": "Helps hospital operators and quality improvement teams identify specific cultural and operational domains requiring intervention to reduce patient harm." }, "claim_count": 3, "claims": [ { "claim_id": "1790104213209742224", "claim_ref": "d922bce132f491ecbef18109520899b506a1c42b", "snapshot": "{\"claim_id\":\"1790104213209742224\",\"claim_text\":\"The overall patient safety culture score at the studied tertiary care hospital was 3.72 \\u00b1 0.52.\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"I-HSOPSC 2.0\",\"role\":\"mentioned\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Baseline metric for hospital safety culture in an Indian tertiary care setting; useful for benchmarking similar health-system quality improvement initiatives.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "The overall patient safety culture score at the studied tertiary care hospital was 3.72 \u00b1 0.52." }, { "claim_id": "1790104213215255811", "claim_ref": "92c284798b4161c64abe284d23c150cea5e49069", "snapshot": "{\"claim_id\":\"1790104213215255811\",\"claim_text\":\"Staffing, work pace, and response to errors are the lowest-scoring domains in the I-HSOPSC 2.0 assessment at the study site.\",\"claim_type\":\"analysis\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"I-HSOPSC 2.0\",\"role\":\"mentioned\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Identifies specific operational domains for hospital administrators to target for quality improvement and resource allocation.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Staffing, work pace, and response to errors are the lowest-scoring domains in the I-HSOPSC 2.0 assessment at the study site." }, { "claim_id": "1790104213217367410", "claim_ref": "84c2af96a315bde5b931bf463061936147d918b8", "snapshot": "{\"claim_id\":\"1790104213217367410\",\"claim_text\":\"Allied health professionals reported more favorable patient safety culture perceptions than nursing staff.\",\"claim_type\":\"analysis\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"I-HSOPSC 2.0\",\"role\":\"mentioned\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Highlights inter-professional disparities in safety culture perception, suggesting a need for targeted engagement strategies for nursing staff.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Allied health professionals reported more favorable patient safety culture perceptions than nursing staff." } ], "entities": [], "headline": "Assessing Patient Safety Culture Among Doctors, Nurses, and Allied Health Professionals Using the Indian Version of the Hospital Survey on Patient Safety Culture (I-HSOPSC 2.0)", "home_domain": null, "manifest_id": "1790103344706346224", "published_at": "2026-09-22", "significance": "medium", "source_channel": "medRxiv - Official Health Systems Policy Economics", "source_name": "medrxiv-health-systems-policy-economics", "source_url": "https://medrxiv.org/content/10.64898/2026.09.15.26363107v1.full", "stream_id": null, "stream_ids": [ "17779881004510530" ], "summary": "This study evaluates patient safety culture in an Indian tertiary care setting using the I-HSOPSC 2.0 survey across 96 practitioners. While the overall safety culture score was positive (3.72 \u00b1 0.52), the findings highlight critical operational vulnerabilities in staffing levels, work pace, and institutional responses to errors. These results provide actionable insights for hospital administrators and policy teams aiming to optimize safety protocols and address inter-professional disparities in safety perceptions.", "tags": [ "medRxiv", "Health Systems" ] }, { "brief": { "actionable_takeaways": [ "Integrate GFAP/NfL ratio normalization into future diagnostic assay development for remote TBI monitoring." ], "facts": [ { "label": "Normalization Strategy", "value": "GFAP/NfL ratio" } ], "key_insights": [ "Capillary DPS sampling is analytically feasible for GFAP and NfL quantification in TBI.", "The GFAP/NfL ratio serves as an effective internal-normalization strategy to improve concordance between capillary and venous samples.", "DPS sampling offers a pathway for longitudinal TBI biomarker monitoring outside of clinical settings." ], "tldr": "Capillary dried plasma spots combined with a GFAP/NfL ratio normalization strategy provide a feasible, less invasive alternative to venous blood draws for longitudinal TBI biomarker monitoring.", "unresolved": [ "Formal clinical validation", "Outcome linkage" ], "why_it_matters": "Enables remote monitoring and decentralized clinical trials for TBI, reducing patient burden and increasing data frequency." }, "claim_count": 3, "claims": [ { "claim_id": "1790103044532861292", "claim_ref": "2fd5ba9e20d17ef039b70a60346987780b5f75bc", "snapshot": "{\"claim_id\":\"1790103044532861292\",\"claim_text\":\"Capillary dried plasma spots (DPS) are analytically feasible for measuring GFAP and NfL in TBI patients.\",\"claim_type\":\"analysis\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"Traumatic Brain Injury\",\"role\":\"subject\",\"tag_id\":\"17801853484508220\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Monitor for adoption of DPS in decentralized TBI clinical trials and remote monitoring workflows.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Capillary dried plasma spots (DPS) are analytically feasible for measuring GFAP and NfL in TBI patients." }, { "claim_id": "1790103044543722529", "claim_ref": "45147370e35bc59bf3cb58636b86407ada6fc4b9", "snapshot": "{\"claim_id\":\"1790103044543722529\",\"claim_text\":\"The GFAP/NfL ratio improves concordance between capillary DPS and venous plasma compared to individual analyte measurements.\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"GFAP\",\"role\":\"mentioned\",\"type\":\"topic\"},{\"name\":\"NfL\",\"role\":\"mentioned\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Diagnostic developers should evaluate the GFAP/NfL ratio as a standard normalization method for capillary-based biomarker assays.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "The GFAP/NfL ratio improves concordance between capillary DPS and venous plasma compared to individual analyte measurements." }, { "claim_id": "1790103044551842112", "claim_ref": "ca47a22e81d5c9311c4831c49c84182ddb7e1522", "snapshot": "{\"claim_id\":\"1790103044551842112\",\"claim_text\":\"Absolute protein recovery from DPS is lower and more variable than from venous EDTA plasma.\",\"claim_type\":\"data\",\"confidence\":\"measured\",\"entities\":[{\"name\":\"Traumatic Brain Injury\",\"role\":\"subject\",\"tag_id\":\"17801853484508220\",\"type\":\"topic\"}],\"evidence\":\"observed\",\"featured\":true,\"key_point_index\":null,\"quote\":null,\"signal\":\"Clinical operators must account for higher variability in DPS samples when designing longitudinal monitoring protocols.\",\"source_urls\":[],\"supporting_quotes\":[]}", "text": "Absolute protein recovery from DPS is lower and more variable than from venous EDTA plasma." } ], "entities": [], "headline": "Concordance Between Capillary Dried Plasma Spot and Venous Plasma Biomarkers in Traumatic Brain Injury: An Analytical Feasibility Pilot Study", "home_domain": null, "manifest_id": "1790102496267587517", "published_at": "2026-09-22", "significance": "high", "source_channel": "medRxiv - Official Neurology Mental Health", "source_name": "medrxiv-neurology-mental-health", "source_url": "https://medrxiv.org/content/10.64898/2026.09.16.26361861v1.full", "stream_id": null, "stream_ids": [ "17779881004510530" ], "summary": "This study evaluates the feasibility of using fingerstick capillary dried plasma spots (DPS) to measure GFAP and NfL, key biomarkers for traumatic brain injury (TBI). Researchers found that while absolute protein recovery from DPS is lower than venous plasma, the measurements remain well-correlated, particularly when using a GFAP/NfL ratio for normalization. This approach could enable remote, longitudinal monitoring of TBI patients, reducing the burden of frequent venipuncture.", "tags": [ "medRxiv", "Diagnostics", "Traumatic Brain Injury" ] } ], "stories_per_domain": 24, "story_attempt": 1, "story_slot": 41, "story_units": [ { "paragraphs": [ { "citations": [ { "claim_id": "1790122000927126256", "kind": "claim", "manifest_id": "1790119201499390250" }, { "claim_id": "1790122000993156530", "kind": "claim", "manifest_id": "1790119201499390250" } ], "text": "Epidemiological models that rely on static social contact assumptions fail to capture how people actually behave when they get sick. New research shows that individuals dramatically cut their social circles during peak illness, followed by a rapid expansion of contacts during recovery. Failing to account for these temporal behavioral changes leads to inaccurate outbreak simulations and flawed evaluations of public health interventions." }, { "citations": [ { "claim_id": "1790122000927126256", "kind": "claim", "manifest_id": "1790119201499390250" }, { "claim_id": "1790122000966929392", "kind": "claim", "manifest_id": "1790119201499390250" } ], "text": "Data from a prospective study tracking acute infection cases and 709 household members shows that infected individuals substantially reduce their social contacts at the height of their illness. As they recover, their social interactions rebound quickly. The weighted mean number of contacts increases 2.0-fold over the two-week follow-up period after peak illness, with a 95% confidence interval spanning 1.8 to 2.2." } ], "single_source": false, "title": "Behavioral shifts during acute illness" }, { "paragraphs": [ { "citations": [ { "claim_id": "1790119581625934357", "kind": "claim", "manifest_id": "1790119201499492216" } ], "text": "A similar pattern of modeling errors emerges when researchers simplify biological factors. In malaria modeling, standard compartmental models rely on population-average immunity rather than tracking individual exposure histories. This simplification leads to significant errors in predicting disease burden, particularly by underestimating clinical malaria prevalence in children within high-transmission regions." }, { "citations": [ { "claim_id": "1790119581629370152", "kind": "claim", "manifest_id": "1790119201499492216" }, { "claim_id": "1790119581635854853", "kind": "claim", "manifest_id": "1790119201499492216" } ], "text": "These population-average assumptions also skew predictions for older demographics. Standard models overestimate the adult asymptomatic reservoirs for malaria, misallocating the true distribution of risk. By using the VECTRI-ABM framework calibrated with historical data from Senegal and The Gambia, researchers showed that the errors introduced by these simplified assumptions are highly climate-dependent." } ], "single_source": false, "title": "Individual-level immunity in malaria modeling" } ], "summary": "New research indicates that incorporating individual behavioral shifts and immunity histories into epidemiological models corrects significant errors in disease burden and transmission predictions.", "supply": { "briefs": 126, "manifests": 121, "mcp_servable": 78, "signals": 126 }, "supporting_evidence": [ { "home_domain": "health-medicine", "manifest_id": "1790099573510706655", "relevance_reasons": [ "same_source_host", "shared_stream" ], "score": 11.061538, "shared_tokens": [ "and", "medrxiv", "study", "the" ], "stream_ids": [ "17779881004510530" ] }, { "home_domain": "health-medicine", "manifest_id": "1790099573510787246", "relevance_reasons": [ "same_source_host", "shared_stream" 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