Clinical Report: Neurology Diagnostic Pathway Analysis

Day 1 Clinical Report: Neurology Diagnostic Pathway Analysis

Introduction

This report presents an analysis of a neurology-related diagnostic challenge using Framesift’s Adaptive Disclosure Framework (ADF). Framesift’s approach, which reframes complexity and ambiguity into actionable clarity, has been applied to a document summarising diagnostic findings from a 67-year-old patient under the care of Neurology at John Radcliffe Hospital.

The results demonstrate the power of structured, AI-driven methodologies in driving insight, prioritising next steps, and aligning stakeholders. This report also contrasts Framesift’s unique approach with other AI techniques, highlighting its broader potential in clinical decision-making.

Diagnostic Findings: Key Insights

The analysis revealed critical findings across three domains:

Neurological Findings:

Progressive bilateral lumbosacral radiculoplexus neuropathy (LRPN).
Severe denervation of the ankle extensors with atypical pain patterns.
MRI findings rule out nerve root compression, suggesting systemic or infiltrative processes.

Vascular Findings:

Contradictory imaging: CTA shows a lack of arterial inflow, while Doppler indicates normal arterial flow.
Patent proximal tibial vessels with possible embolic phenomena, requiring resolution through further imaging.

Systemic Findings:

Matched oligoclonal bands (OGBs) in CSF and serum, coupled with elevated CSF protein levels (1247).
PET findings reveal no active vasculitis, with a normal white cell count.

Working Hypotheses

Autoimmune Process: Suggested by matched OGBs and elevated CSF protein, likely contributing to the neurological symptoms.
Paraneoplastic Syndrome: Systemic involvement and progression warrant investigation.
Embolic-Vascular Contribution: Conflicting vascular findings point to possible embolic phenomena.

Proposed Diagnostic Actions

The findings have been prioritised into actionable pathways:

Immediate Testing:

Autoimmune panel (ANA, ANCA, ESR, CRP).
Paraneoplastic screen.
Thrombophilia studies.

Procedures:

Colonoscopy to evaluate an ascending colonic focus.

Consultations:

Vascular Medicine, Immunology, Oncology.

Monitoring:

Serial NCS studies to track disease progression.

Visualisations and Clinical Context

These are Visualisations the Framesift Team thinks may be useful to Clinicians - we'd love to hear your thoughts and to incorporate your feedback into the next Experiment Loop.

📊 Interactive visualisations cannot be rendered in PDFs. Click here to view this Clinical Report online. Click here to explore all the visualisations created by the Framesift Team on Day 1—delivered within hours of being asked to assist.

Concept Map of Findings, Hypotheses, and Actions

graph TB
    subgraph Findings["Key Findings"]
        N[Neurological]
        V[Vascular]
        S[Systemic]
    end

    subgraph Hypotheses["Working Hypotheses"]
        H1[Autoimmune Process]
        H2[Paraneoplastic Syndrome]
        H3[Embolic-Vascular]
    end

    subgraph Actions["Required Actions"]
        A1[Autoimmune Panel]
        A2[Paraneoplastic Screen]
        A3[Colonoscopy]
        A4[Thrombophilia Studies]
    end

    N --> H1
    S --> H1 & H2
    V --> H3

    H1 --> A1
    H2 --> A2 & A3
    H3 --> A4

Reasoning: This visualisation may help clinicians connect findings to diagnostic hypotheses and prioritised actions.

Temporal Progression of Findings

gantt
    title Disease Progression Timeline
    dateFormat  YYYY-MM
    axisFormat %Y-%m
    
    section Neurological
    MRI LS (DDD, no compression)      :2023-06, 1M
    Initial NCS (Left LRPN)           :2023-10, 1M
    Repeat NCS (Progressive)          :2024-07, 1M
    Final NCS (Bilateral LRPN)        :2025-01, 1M

    section Vascular
    CTA (↓ arterial flow)             :2024-12, 1M
    Doppler (normal flow)             :2024-12, 1M

    section Systemic
    First LP (Matched OGBs)           :2024-07, 1M
    Second LP (↑↑ Protein)            :2024-12, 1M
    PET Scan                          :2025-01, 1M

Reasoning: This timeline highlights disease progression and diagnostic milestones.

Why Framesift Stands Out

Unlike conventional applied AI tools, Framesift enables:

Reframing Ambiguity into Opportunity:

Instead of relying on explicit objectives, Framesift builds understanding incrementally through layered decomposition and stakeholder simulation.

Stakeholder-Centric Design:

Simulating perspectives of medical professionals, caregivers, and administrators ensures insights are tailored to actionable needs.

Iterative Refinement:

Framesift’s feedback loops reduce cognitive overload, translating complexity into structured outputs that clinicians can act on confidently.

Potential Applications in Medicine

Framesift’s methodology can drive positive outcomes in:

Diagnostic Investigations: Clarifying ambiguous cases, identifying priorities, and aligning multidisciplinary teams.
2.Care Pathway Optimisation: Creating shared narratives among stakeholders for improved decision-making.
Medical Education: Training clinicians in navigating complex, multi-system cases.

Conclusion

Framesift transforms how clinicians engage with ambiguity, aligning diagnostic complexity with actionable clarity. This case study exemplifies the potential of Framesift to enhance medical investigations and multidisciplinary collaboration.

We welcome your feedback on the findings and visualisations to refine this methodology further.

danbarua/day_1_clinical_report.md