Medium-Term Adjunctive Predictive Cardiovascular Indicator (QNL) — FDA decisions, comparisons and evidence
The 2021–2025 analysis contains 5 selected substantially-equivalent FDA decisions under primary product code QNL. Use it to compare documented submissions and evidence with your product. A separate 2026 update contains 1 decisions through 2026-09-27. The latest selected decision across the acquired endpoint is dated 2026-09-18. Neither set establishes a suitable predicate or the route for your device. The complete-year window has 5 decisions; the separate all-observed-date count is 6. These denominators describe different date ranges.
Evidence retrieved 2026-10-07. Source versions and topic-specific limits are listed below.
Recorded scope and its declared regulatory reference
An exact FDA-record regulation_number match to one acquired Title 21 section. Records with the same normalized scope definition, class, regulation and recorded submission/GMP flags are grouped. Sparse definitions and generic exemption boilerplate do not qualify. No text-similarity equivalence or legal applicability is inferred.
What scope does the FDA record describe?
The adjunctive predictive cardiovascular indicator is a prescription device that uses software algorithms to analyze cardiovascular vital signs and predict future cardiovascular status or events within a defined medium-term period. This device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy.
Compare the proposed indication, user, anatomy, technology and operating principle with this actual scope; record differences and unresolved facts.
§ 870.2210 Adjunctive predictive cardiovascular indicator. (a) Identification. The adjunctive predictive cardiovascular indicator is a prescription device that uses software algorithms to analyze cardiovascular vital signs and predict future cardiovascular status or events. This device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy. (b) Classification. Class II (special controls). The special controls for this device are: (1) A software description and the results of verification and validation testing based on a comprehensive hazard analysis and risk assessment must be provided, including: (i) A full characterization of the software technical parameters, including algorithms; (ii) A description of the expected impact of all applicable sensor acquisition hardware characteristics and associated hardware specifications; (iii) A description of sensor data quality control measures; (iv) A description of all mitigations for user error or failure of any subsystem components (including signal detection, signal analysis, data display, and storage) on output accuracy; (v) A description of the expected time to patient status or clinical event for all expected outputs, accounting for differences in patient condition and environment; and (vi) The sensitivity, specificity, positive predictive value, and negative predictive value in both percentage and number form. (2) A scientific justification for the validity of the predictive cardiovascular indicator algorithm(s) must be provided. This justification must include verification of the algorithm calculations and validation using an independent data set. (3) A human factors and usability engineering assessment must be provided that evaluates the risk of misinterpretation of device output. (4) A clinical data assessment must be provided. This assessment must fulfill the following: (i) The assessment must include a summary of the clinical data used, including source, patient demographics, and any techniques used for annotating and separating the data. (ii) The clinical data must be representative of the intended use population for the device. Any selection criteria or sample limitations must be fully described and justified. (iii) The assessment must demonstrate output consistency using the expected range of data sources and data quality encountered in the intended use population and environment. (iv) The assessment must evaluate how the device output correlates with the predicted event or status. (5) Labeling must include: (i) A description of what the device measures and outputs to the user; (ii) Warnings identifying sensor acquisition factors that may impact measurement results; (iii) Guidance for interpretation of the measurements, including a statement that the output is adjunctive to other physical vital sign parameters and patient information; (iv) A specific time or a range of times before the predicted patient status or clinical event occurs, accounting for differences in patient condition and environment; (v) Key assumptions made during calculation of the output; (vi) The type(s) of sensor data used, including specification of compatible sensors for data acquisition; (vii) The expected performance of the device for all intended use populations and environments; and (viii) Relevant characteristics of the patients studied in the clinical validation (including age, gender, race or ethnicity, and patient condition) and a summary of validation results. [87 FR 8191, Feb. 14, 2022]
Read the identification, classification, conditions and referenced limitations in the cited section. A numeric reference match is not a buyer classification or exemption determination.
Deduplicate by official submission ID across the complete current manifest partitions. Select exact primary product code, K-number format and the stated SE decision codes with valid dates. Recent distributions use the five complete calendar years preceding the latest valid endpoint decision year. Partial-year counts compare equal January-to-cutoff periods. Quartiles use linear interpolation at (n-1)*p and are withheld below 20 valid date pairs. The analysis n describes only its declared complete-year window; selected_se_n separately counts all selected recorded dates through the cutoff.
6 selected records across all observed dates; 0 other/invalid identifier or decision-date records excluded. 0 missing or invalid date pairs in the five-year window.
Date fields: date_received → decision_date. Quantiles: Hyndman–Fan type 7: linear interpolation at (n − 1) × p; displayed to one decimal; n ≥ 20 valid pairs.
Receipt-to-decision calendar elapsed time includes time outside active FDA review; it is not FDA review time, a promised project timeline or an estimate of future clearance. This selected recorded cohort does not include all applications or establish a success probability, predicate suitability, market size, current market availability or legal authorization for another product.
Calculation fda-buyer-research-3 · database cutoff 2026-09-27. CSV rows identify each official K-number, cohort, date pair, exclusion reason and source version.
Separate partial-year update
2026 decisions through 2026-09-27
1 selected decisions from 2026-01-01 to 2026-09-27. The equivalent previous-year period contains 0 decisions through 2025-09-27. These counts describe the records; they are not market growth or submission success rates.
Named records to investigate
Latest decisions across the database
These dated records may come from 2026 or earlier years. They are a separate investigation list, not the five-year statistical cohort. Compare the actual indications and technology before considering a record as a comparator.
K231038 ↗Global Hypoperfusion Index (GHI) Algorithm
Edwards Lifesciences, LLC
2023-07-26
Traditional
105
K200717 ↗CLEWICU System (ClewICUServer and ClewICUnitor)
Clew Medical , Ltd.
2021-01-09
Traditional
297
Supporting documents actually acquired
Go beyond the database row
Read the source context, then compare the evidence with your design. Topic locations below are text matches, including possible limitations or negative statements; they are not a mandatory test list.
The adjunctive predictive cardiovascular indicator is a prescription device that uses software algorithms to analyze cardiovascular vital signs and predict future cardiovascular status or events within a defined medium-term period. This device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy. [1]
Use this checklist to gather your business or product details before speaking with a specialist. The items below explain what to record and suggest useful supporting documents. You can add your own answers in the editable project brief.
Which specific part of the recorded scope fits or differs?
Put your proposed label and design beside the quoted definition. Record matching facts, differences and missing facts separately; naming the category alone cannot resolve scope.
Useful evidence: Proposed indication/design and a definition-to-product comparison with source locators.
Have the cited section and its limitations been reviewed?
Record the applicable paragraph, conditions and cross-referenced limitations after specialist review. Keep a claimed exemption separate from actual establishment, listing and quality-system responsibilities.
Useful evidence: Dated classification/route rationale and the current provisions relied on, with unresolved conditions.
Compare your intended use with a named decision
Choose a named record above. Put your proposed claim beside its actual indications-for-use statement. Record different patients, users, anatomy, settings and output claims; do not treat a shared code as proof of equivalence.
Useful evidence: Your draft indications for use + the selected official summary and its exact page.
Explain the technology and evidence differences
For each comparison, record the different materials, hardware, software functions and operating conditions. Link each difference to existing evidence or an unresolved evaluation task.
Useful evidence: A three-column matrix: comparator fact / your design fact / evidence or unresolved gap.
Prepare a scope-based schedule without a sparse timing benchmark
This recent cohort has fewer than 20 valid date pairs, so it supplies no median or percentile benchmark. Ask for a schedule based on actual preparation, evidence gaps, interactions and response assumptions; keep any historical decision context separately dated.
Useful evidence: Document/test readiness, unresolved route/evidence tasks and the assumptions behind the specialist’s proposed sequence.
Work packages and dependencies
Conditional: FDA 510(k) Submission Services — Review the supplied facts and evidence gaps before confirming the service scope.
Optional: Find FDA US Agent Services | Compare & Get Quotes — Include only if your product, actor and delivery needs justify this additional scope. Confirm the responsibility and evidence handoff with the coordinating specialist.
Optional: FDA QMSR Transition & Inspection Readiness (ISO 13485 Alignment) — Include only if your product, actor and delivery needs justify this additional scope. Confirm the responsibility and evidence handoff with the coordinating specialist.
What needs to happen first
FDA 510(k) Submission Services → Find FDA US Agent Services | Compare & Get Quotes: Confirm the main product/actor scope and evidence gaps before deciding whether to commission this additional service.
FDA 510(k) Submission Services → FDA QMSR Transition & Inspection Readiness (ISO 13485 Alignment): Confirm the main product/actor scope and evidence gaps before deciding whether to commission this additional service.
Questions for providers
Which of the named QNL decisions are actually comparable to our proposed indications and technology, and which would you exclude?
Which evidence differences prevent us from using the comparison yet, and what deliverable resolves each one?
Does your schedule separate submission preparation, testing, FDA interactions and customer response time? What assumptions change it?
Sources and data dates
Read the official document in context. The audit details identify the precise locators and preserved versions used for this page.
