{"schema_version":1,"research_id":"eoa_inverse_innovation_exp04_external_evaluation_20260802","source_assessment_id":"invariant_mode_decomposition_design__medicine_healthcare:DISCARDED_AUDIT:H2:v0","cell_id":"invariant_mode_decomposition_design__medicine_healthcare","search_queries":["intradialytic hypotension ultrafiltration biofeedback randomized trial blood volume monitoring dialysis","hemodialysis intradialytic hypotension SVD modal control ultrafiltration machine learning personalized prescription","KDIGO intradialytic hypotension blood pressure ultrafiltration guideline","randomized trial automated ultrafiltration biofeedback hemodialysis Kt/V hypotension","site:pubmed.ncbi.nlm.nih.gov intradialytic hypotension prediction personalized ultrafiltration control model hemodialysis","site:pmc.ncbi.nlm.nih.gov hemodialysis model predictive control ultrafiltration intradialytic hypotension","hemodialysis patient-specific ultrafiltration profile algorithm blood volume control trial","intradialytic hypotension machine learning intervention ultrafiltration settings prospective trial","Individualization of Ultrafiltration in Hemodialysis authors 2019","Effectiveness of blood volume change-guided ultrafiltration control 2025","site:fda.gov clinical decision support software dialysis treatment recommendations device guidance 2025","site:fda.gov hemodialysis machine ultrafiltration control 510k software"],"sources":[{"source_id":"S1","title":"Blood pressure and volume management in dialysis: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference","publisher":"Kidney Disease: Improving Global Outcomes / Kidney International","url":"https://kdigo.org/wp-content/uploads/2017/05/KDIGO-BP-Volume-in-Dialysis-FINAL.pdf","source_class":"OFFICIAL_GUIDANCE","publication_date":"2020","accessed_at":"2026-08-02","claims_supported":["Intradialytic hypotension is associated with vascular-access thrombosis, inadequate dialysis dose, and mortality.","Reported prevalence ranges from 15% to 50% of hemodialysis treatments depending on definition.","A symptomatic blood-pressure decrease or nadir systolic pressure below 90 mmHg should prompt reassessment of ultrafiltration rate, treatment time, interdialytic weight gain, target weight, and medication use.","Avoiding hypotension should not compromise euvolemia or adequate dialysis time."]},{"source_id":"S2","title":"Randomized Crossover Trial of Blood Volume Monitoring–Guided Ultrafiltration Biofeedback to Reduce Intradialytic Hypotensive Episodes with Hemodialysis","publisher":"Clinical Journal of the American Society of Nephrology","url":"https://pubmed.ncbi.nlm.nih.gov/29018100/","source_class":"PRIMARY_RESEARCH","publication_date":"2017-10-16","accessed_at":"2026-08-02","claims_supported":["A randomized crossover trial tested automatic blood-volume-guided ultrafiltration-rate adjustment in hypotension-prone patients.","The intervention did not reduce symptomatic intradialytic hypotension relative to best clinical practice.","The trial demonstrates both technical feasibility and uncertainty about clinical benefit from a single-signal feedback strategy."]},{"source_id":"S3","title":"Automatic control of blood volume trends during hemodialysis","publisher":"ASAIO Journal / Wolters Kluwer","url":"https://pubmed.ncbi.nlm.nih.gov/8555549/","source_class":"PRIMARY_RESEARCH","publication_date":"1994","accessed_at":"2026-08-02","claims_supported":["A time-dependent dynamic regulator has already adjusted ultrafiltration rate and dialysate conductivity to track desired blood-volume trajectories.","A small study in five hypotension-prone patients reported fewer hypotensive episodes during automatic regulation.","Model-mediated, multivariable dialysis control therefore predates the audited hypothesis."]},{"source_id":"S4","title":"Individualization of Ultrafiltration in Hemodialysis","publisher":"IEEE Transactions on Biomedical Engineering","url":"https://pubmed.ncbi.nlm.nih.gov/30530307/","source_class":"PRIMARY_RESEARCH","publication_date":"2018-12-04","accessed_at":"2026-08-02","claims_supported":["Patient-specific ultrafiltration profiles have been designed using a nonlinear intravascular–interstitial fluid model with parameter uncertainty.","The optimization minimizes maximal ultrafiltration rate while meeting fluid-removal and hematocrit-safety constraints.","This is a close conceptual analogue to choosing settings from a patient-specific setting-to-physiology response model."]},{"source_id":"S5","title":"Effect of ultrafiltration profiling on outcomes among maintenance hemodialysis patients: a pilot randomized crossover trial","publisher":"Journal of Nephrology / Springer Nature","url":"https://pubmed.ncbi.nlm.nih.gov/32975783/","source_class":"PRIMARY_RESEARCH","publication_date":"2020-09-25","accessed_at":"2026-08-02","claims_supported":["A randomized crossover pilot compared declining ultrafiltration profiles with conventional ultrafiltration.","Profiling reduced some intermediate symptoms but did not demonstrate broad improvement across cardiovascular outcomes.","Feasible profile changes do not automatically yield the hypothesized clinical effect."]},{"source_id":"S6","title":"Effect of absolute blood volume measurement–guided fluid management on the incidence of intradialytic hypotension-associated events: a randomised controlled trial","publisher":"Clinical Kidney Journal / Oxford University Press","url":"https://academic.oup.com/ckj/article/17/5/sfae128/7658456","source_class":"PRIMARY_RESEARCH","publication_date":"2024-04-25","accessed_at":"2026-08-02","claims_supported":["Intradialytic hypotension-associated events arise through interaction among ultrafiltration, vascular refill, blood volume, and compensatory mechanisms.","Absolute-blood-volume-guided target-weight adjustment reduced hypotension-associated events by an adjusted 10.5 percentage points versus standard care in a 56-patient randomized trial.","Existing dialysis-machine sensors can support individualized volume-management interventions, although the proposed threshold showed only moderate predictive performance."]},{"source_id":"S7","title":"Effectiveness of blood volume change-guided ultrafiltration control (BV-UFC) in hemodialysis: a crossover comparative study","publisher":"Clinical Kidney Journal / Oxford University Press","url":"https://pubmed.ncbi.nlm.nih.gov/40400789/","source_class":"PRIMARY_RESEARCH","publication_date":"2025-05-06","accessed_at":"2026-08-02","claims_supported":["An existing system automatically adjusts ultrafiltration every two minutes from real-time blood-volume measurements and a target trajectory.","A 38-patient crossover study reported reduced intradialytic hypotension and improved plasma refilling without compromising target ultrafiltration volume.","Automated response-based ultrafiltration control is active clinical prior art."]},{"source_id":"S8","title":"Product Classification: Hemodialysis delivery machine with an automated ultrafiltration controller (QIR)","publisher":"U.S. Food and Drug Administration","url":"https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPCD/classification.cfm?id=QIR","source_class":"GOVERNMENT_OR_REGULATOR","publication_date":"2026-07-20","accessed_at":"2026-08-02","claims_supported":["Hemodialysis delivery machines with automated ultrafiltration controllers are Class II, life-supporting devices subject to 510(k) premarket review.","Software that directly changes ultrafiltration settings would require device-manufacturer integration, safety engineering, and regulatory analysis rather than unrestricted clinical deployment."]}],"problem_evidence":{"support":"STRONG","rationale":"Official guidance and multiple trials confirm that intradialytic hypotension is common, consequential, multifactorial, and linked to the balance among ultrafiltration, vascular refill, blood volume, cardiac/autonomic compensation, treatment time, and target weight. Blood pressure alone is therefore an incomplete control signal.","source_ids":["S1","S2","S4","S6","S7"]},"stakeholder_evidence":{"support":"MODERATE","rationale":"KDIGO expressly directs clinicians to reassess dialysis prescription variables after hypotension, and multiple centers have participated in trials of automated or measurement-guided adjustment. This establishes credible clinical adopters and authorizers, but no source expresses demand for SVD-defined modes specifically.","source_ids":["S1","S2","S5","S6","S7","S8"]},"prior_art":{"proximity":"SUBSTANTIAL_COLLISION","closest_analogues":[{"name":"Patient-specific optimized ultrafiltration profiles","similarity":"Uses an individualized setting-to-physiology model to select an ultrafiltration trajectory under fluid-removal and hematocrit safety constraints.","remaining_difference":"It uses nonlinear constrained optimization rather than SVD-derived response modes, modal sensitivity ranking, and residual-based recommendation acceptance.","source_ids":["S4"]},{"name":"Automatic blood-volume trajectory control","similarity":"Uses a dynamic physiological model and feedback to adjust both ultrafiltration rate and dialysate conductivity in hypotension-prone patients.","remaining_difference":"It tracks a prescribed blood-volume trajectory rather than identifying and damping an outcome-sensitive latent mode.","source_ids":["S3"]},{"name":"Blood-volume-guided ultrafiltration biofeedback and BV-UFC","similarity":"Existing systems automatically modify ultrafiltration from measured physiological response and have been evaluated against usual dialysis.","remaining_difference":"They use blood-volume targets or curves rather than a multivariable SVD basis with sensitivity sweeps and out-of-sample reconstruction gates.","source_ids":["S2","S7"]},{"name":"Absolute-blood-volume-guided target-weight adjustment","similarity":"Individualizes a dialysis prescription using a physiological measurement associated with refill and compensatory failure and has randomized clinical evidence.","remaining_difference":"It changes target weight using a threshold rather than selecting among feasible machine-setting changes through modal decomposition.","source_ids":["S6"]}],"distinctive_claim_remaining":"The remaining differentiated claim is that an SVD of a patient-specific multivariable setting-to-physiology response map, followed by outcome-directed modal sensitivity ranking and an out-of-sample reconstruction gate, will outperform existing blood-volume feedback, target-trajectory control, optimized ultrafiltration profiling, and usual adjustment on symptomatic hypotension while preserving Kt/V. That incremental claim is explicit and testable but currently unsupported.","confidence":"HIGH"},"implementation_evidence":{"support":"MODERATE","rationale":"Existing machines measure blood-volume responses and can automatically vary ultrafiltration; prior work also demonstrates patient-specific physiological modeling and constrained profile optimization. However, no direct source validates stable session-level SVD modes, the proposed modal sensitivity workflow, the minimum number of prior sessions, independent controllability of identified modes, or reconstruction error as a clinical safety gate. Direct control would also enter a regulated life-supporting-device workflow.","source_ids":["S2","S3","S4","S6","S7","S8"]},"scores":{"meaningful_impact":{"score":4,"rationale":"A clinically meaningful reduction in symptomatic hypotension could reduce treatment burden and downstream morbidity while maintaining adequate dialysis.","source_ids":["S1","S6"]},"stakeholder_pull":{"score":3,"rationale":"Clinicians already adjust the relevant prescription variables and participate in trials of guided control, but demand for this modal formulation is not documented.","source_ids":["S1","S2","S6","S7"]},"incremental_advantage":{"score":2,"rationale":"The multivariable modal method could improve on single-trajectory feedback, but no comparative evidence shows that SVD modes add value over existing individualized optimization or blood-volume control.","source_ids":["S2","S3","S4","S7"]},"distinctiveness_plausibility":{"score":2,"rationale":"The exact SVD–sensitivity–residual combination was not found, but its functional objective substantially overlaps longstanding patient-specific optimization and closed-loop ultrafiltration control.","source_ids":["S3","S4","S7"]},"technical_implementability":{"score":3,"rationale":"Sensors, controllable settings, and automated ultrafiltration systems exist; stable identification of clinically meaningful patient-specific modes remains unproven.","source_ids":["S3","S4","S6","S7"]},"adoption_authority_feasibility":{"score":2,"rationale":"Nephrologists and dialysis organizations can authorize research use, but machine integration and automated treatment recommendations implicate manufacturers, institutional governance, and Class II device oversight.","source_ids":["S1","S8"]},"evidence_readiness":{"score":2,"rationale":"The outcome and adequacy guardrail are measurable, but the proposed modal model lacks retrospective validation, comparator benchmarking, and prospective safety evidence.","source_ids":["S2","S4","S5","S7"]},"safety_net_benefit":{"score":3,"rationale":"The Kt/V guardrail and reconstruction gate could prevent underdialysis or poorly supported recommendations, but they do not by themselves address fluid overload, sodium balance, control instability, or abrupt physiological change.","source_ids":["S1","S2","S4"]},"scalability":{"score":2,"rationale":"Repeated sessions generate abundant data, but cross-machine integration, calibration, model drift, clinical oversight, and regulatory validation would constrain scale.","source_ids":["S4","S7","S8"]}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"50K_TO_250K","scope":"Single-center retrospective replay study using historical session data to estimate patient-specific response maps, test mode stability, compare against existing prediction/profile baselines, and quantify reconstruction failure.","confidence":"LOW","assumptions":["Existing high-frequency machine, blood-pressure, laboratory, symptom, and Kt/V data are accessible.","No prospective setting changes or device integration are included.","Approximately 100–300 patients with repeated sessions are available."],"source_ids":["S2","S4","S7"]},"initial_deployment_startup":{"band_2026_usd":"250K_TO_1M","scope":"Prospective silent-mode deployment at one or two dialysis centers, including data interfaces, clinician dashboard, software quality controls, security review, and usability testing.","confidence":"LOW","assumptions":["Recommendations remain advisory and do not directly control the dialysis machine.","Existing machine data interfaces can be accessed under institutional and vendor agreements.","Clinical and engineering personnel are partly contributed by partners."],"source_ids":["S4","S7","S8"]},"operational_launch":{"band_2026_usd":"1M_TO_5M","scope":"Powered multicenter randomized evaluation of mode-guided recommendations versus usual adjustment and an active blood-volume/profile comparator, with clinical monitoring, device-quality work, and regulatory consultation.","confidence":"LOW","assumptions":["Several hundred hypotension-prone participants are required to assess a 20% relative reduction.","Clinicians approve every recommendation during the trial.","Direct machine control, if pursued, requires manufacturer partnership and a formal FDA pathway."],"source_ids":["S2","S5","S6","S7","S8"]},"annual_recurring":{"band_2026_usd":"250K_TO_1M","scope":"Model monitoring, recalibration, software maintenance, cybersecurity, clinical governance, adverse-event surveillance, and support across an early multisite deployment.","confidence":"LOW","assumptions":["Deployment remains limited to a small network of centers.","Machine vendors provide supported interfaces.","Regulatory maintenance and quality-system costs are included but manufacturing costs are excluded."],"source_ids":["S7","S8"]}},"verified_pipeline_gates":{"externally_supported_problem":{"status":"YES","reason":"The prevalence, clinical consequences, and multifactorial physiology of intradialytic hypotension are supported by official guidance and primary trials.","source_ids":["S1","S2","S6","S7"]},"externally_credible_adopter_or_authorizer":{"status":"YES","reason":"Nephrologists, dialysis nurses, dialysis organizations, machine manufacturers, and regulators already authorize or operate comparable prescription-adjustment and automated-ultrafiltration workflows.","source_ids":["S1","S2","S7","S8"]},"distinct_testable_incremental_claim":{"status":"YES","reason":"The hypothesis specifies a modal intervention, an active usual-care comparison, a 20% symptomatic-hypotension effect threshold, and a Kt/V non-inferiority guardrail, making the incremental claim testable despite close prior art.","source_ids":["S2","S4","S7"]},"bounded_next_evidence_step":{"status":"YES","reason":"A retrospective repeated-session replay study followed by prospective silent-mode testing can evaluate mode stability, reconstruction validity, and counterfactual recommendation agreement without changing treatment.","source_ids":["S2","S4","S7"]},"no_unresolved_safety_or_authority_stop":{"status":"NO","reason":"The hypothesis does not specify clinician override, hard bounds for fluid removal and dialysate changes, failure fallback, drift handling, manufacturer integration, or the regulatory pathway for recommendations affecting a life-supporting Class II device.","source_ids":["S1","S8"]},"credible_cost_scope_and_range":{"status":"UNCERTAIN","reason":"Order-of-magnitude ranges can be bounded by retrospective, silent-mode, and multicenter phases, but no site count, data-interface agreement, vendor scope, trial power calculation, or regulatory strategy is supplied.","source_ids":["S2","S6","S7","S8"]}},"next_evidence_step":"Conduct a preregistered retrospective repeated-session replay study in hypotension-prone patients. Estimate each patient's setting-to-physiology map using only prior sessions; predefine mode-stability, spectral-conditioning, and out-of-sample reconstruction thresholds; compare predicted setting choices against usual adjustment, blood-volume trajectory control, and nonlinear individualized ultrafiltration optimization; and advance only if the modal method improves held-out symptomatic-hypotension prediction or safe-control simulation without worsening simulated fluid removal or observed Kt/V. A subsequent prospective phase should run in silent mode before any clinician-facing or machine-controlling trial.","blocking_evidence":["No direct evidence shows that the proposed SVD-derived modes are stable or physiologically interpretable across dialysis sessions.","No evidence establishes how many prior sessions are required for reliable patient-specific response-map estimation.","No head-to-head evidence shows incremental benefit over blood-volume biofeedback, optimized ultrafiltration profiles, or absolute-blood-volume-guided adjustment.","The proposed reconstruction test has not been validated as a clinical safety criterion for dialysis-setting recommendations.","Independent controllability and safe bounds for ultrafiltration, dialysate sodium/conductivity, temperature, and other candidate settings are unspecified.","The 20% symptomatic-hypotension effect and Kt/V change of no more than 0.1 have no supporting pilot estimate for this intervention.","Clinician override, failure fallback, mode-drift monitoring, manufacturer integration, and regulatory responsibilities remain unresolved.","Cost ranges lack externally verified site, interface, trial, and regulatory budgets."],"research_disposition":"PARTNERED_RESEARCH_PROGRAM","world_novelty_boundary":"This evaluation does not establish or claim world novelty. It is a bounded search-based assessment: substantial functional prior art was found for individualized physiological modeling, optimized ultrafiltration profiles, and closed-loop blood-volume-guided control, while the exact SVD–modal-sensitivity–reconstruction-gate combination was not verified in the reviewed sources. Absence from this search is not evidence of worldwide novelty or patentability.","arm":"DISCARDED_AUDIT","candidate_version":0,"controller_recommendation":{"action":"STOP_EMPIRICAL_RESEARCH_NEEDED","repairable":true,"material_progress_observed":false,"progress_targets":["Demonstrate stable, well-conditioned patient-specific modes on held-out sessions.","Benchmark against individualized nonlinear optimization and existing blood-volume feedback rather than usual care alone.","Validate reconstruction failure as a safety-relevant rejection criterion.","Specify clinician override, hard setting limits, fallback behavior, drift monitoring, and regulatory ownership.","Obtain prospective silent-mode evidence before treatment recommendations or machine integration.","Externally validate trial and deployment cost assumptions."],"reason":"As written, the hypothesis does not satisfy the preregistered strict differentiated-opportunity endpoint. The problem, stakeholders, and falsifiable outcome are credible, but substantial prior-art collision weakens differentiation, the claimed incremental benefit is untested, and unresolved safety, authority, and cost evidence prevent a strict-success determination. The appropriate outcome is a partnered empirical research program, not adoption or rescue."}}