SANSA HSAT

K252497

Huxley Medical · cleared 2025-12-10 · product code MNR · Anesthesiology

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.5)
“The SANSA HSAT collects multiple physiological signals using a single wearable patch worn on the chest. The SANSA device contains a reflective PPG sensor, a single-lead ECG sensor, and a 3-axis accelerometer. The signals from these sensors are passed into a cloud-based algorithm which utilizes a combination of signal processing and AI/ML components to compute time-series data for clinician review and summary metrics for report output. This submission updates the algorithm to update performance and add the ability to classify between Obstructive and Central Sleep Apnea events using an AI/ML classifier and present a summary metric, SANSA Apnea Hypopnea Index – Central (sAHIc). REM/NREM Classification and REM related sleep metrics were also added.”
Algorithmcloud-based algorithm which utilizes a combination of signal processing and AI/ML components to compute time-series data for clinician review and summary metrics for report output. This submission updates the algorithm to update performance and add the ability to classify between Obstructive and Central Sleep Apnea events using an AI/ML classifier and present a summary metric, SANSA Apnea Hypopnea Index – Central (sAHIc). REM/NREM Classification and REM related sleep metrics were also added.
source quote (p.5)
“The signals from these sensors are passed into a cloud-based algorithm which utilizes a combination of signal processing and AI/ML components to compute time-series data for clinician review and summary metrics for report output. This submission updates the algorithm to update performance and add the ability to classify between Obstructive and Central Sleep Apnea events using an AI/ML classifier and present a summary metric, SANSA Apnea Hypopnea Index – Central (sAHIc). REM/NREM Classification and REM related sleep metrics were also added.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=325 patients

endpoints: Sensitivity; Specificity

Reported performance (4 observations)

sensitivity100CI 95% CI 73.5, 100.0
source quote (p.10)
“The sensitivity of the Sansa device to detect AHIc ≥ 10 was 100.0% (95% CI 73.5, 100.0) and the specificity was 98.7% (95% CI 96.8, 99.7).”
specificity98.7CI 95% CI 96.8, 99.7
source quote (p.10)
“The sensitivity of the Sansa device to detect AHIc ≥ 10 was 100.0% (95% CI 73.5, 100.0) and the specificity was 98.7% (95% CI 96.8, 99.7).”
sensitivityas written: “REM/NREM epoch level classification sensitivity”74.6CI 95% CI 73.6%, 75.6%
source quote (p.10)
“The sensitivity and specificity of REM/NREM epoch level classification measured by Sansa against PSG was 74.6% (95% CI 73.6%, 75.6%) and 89.5% (95% CI 89.2%, 89.8%), respectively.”
specificityas written: “REM/NREM epoch level classification specificity”89.5CI 95% CI 89.2%, 89.8%
source quote (p.10)
“The sensitivity and specificity of REM/NREM epoch level classification measured by Sansa against PSG was 74.6% (95% CI 73.6%, 75.6%) and 89.5% (95% CI 89.2%, 89.8%), respectively.”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
37
MAUDE reports in code, 12mo
+171%
vs code's own 3-yr baseline
1
drift signals on this device
  • adverse_event_inflection

    MAUDE adverse-event reports for product code MNR: 37 in the 12 months ending 2026-06, vs a 13.7/12mo average over the prior 3 windows (+171%). Code-level count — reports are not attributed to this specific device.

    first seen 2026-07-08 · openFDA /device/event.json count=date_received product_code=MNR

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Anesthesiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

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