TipTraQ (TTQ001)

K243268

PranaQ Pte. Ltd. · cleared 2025-02-03 · product code MNR · Anesthesiology

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.5)
“TipTraQ is a prescription-only medical device aiding in sleep apnea evaluation/diagnosis comprising a fingertip wearable device, a companion mobile app, a cloud-based AI analysis and an information display system.”
Algorithmcloud-based AI analysis and an information display system. The TipTraQ Algorithm System determines Total Sleep Time (TST), Total REM Time (TREMT), Oxygen Desaturation Index (ODI), and Apnea-Hypopnea Index (AHI) from the recorded waveform signals. TQ-AHI calculation tuned to the AASM's '1A Rule' for the scoring of hypopnea AND TQ-AHI calculation tuned to the AASM's '1B Rule' for the scoring of hypopnea
source quote (p.5)
“TipTraQ is a prescription-only medical device aiding in sleep apnea evaluation/diagnosis comprising a fingertip wearable device, a companion mobile app, a cloud-based AI analysis and an information display system. It collects essential physiological waveform information, including Photoplethysmogram (PPG) and accelerometer data. The TipTraQ Algorithm System determines Total Sleep Time (TST), Total REM Time (TREMT), Oxygen Desaturation Index (ODI), and Apnea-Hypopnea Index (AHI) from the recorded waveform signals. The TipTraQ Algorithm System determines Total Sleep Time (TST), Total REM Time (TREMT), Oxygen Desaturation Index (ODI), and Apnea-Hypopnea Index (AHI) from the recorded waveform signals. TQ-AHI calculation tuned to the AASM's '1A Rule' for the scoring of hypopnea AND TQ-AHI calculation tuned to the AASM's '1B Rule' for the scoring of hypopnea”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (6)

Bench

sample size not stated

standards: ISO 80601-2-61:2019

Bench

sample size not stated

standards: FDA guidance, Content of Premarket Submission for Device Software Functions, Guidance for Industry and Food and Drug Administration Staff

Bench

sample size not stated

standards: IEC 60601-1:2020, IEC 60601-1-2:2014 +AMD1:2021, IEC 60601-1-11:2020, IEC 62133-2:2017

Bench

sample size not stated

standards: ISO 10993-1:2018, FDA Guidance on the Use of International Standard ISO 10993-1

Standalone

n=12 patients · 1 site(s)

endpoints: SpO2 accuracy; Pulse rate accuracy

standards: FDA guidance, Pulse Oximeters- Premarket Notification Submissions [510(k)s], Guidance for Industry and Food and Drug Administration Staff, ISO 80601-2-61:2019

Retrospective clinical

n=147 patients · 1 site(s)

endpoints: Total Sleep Time (PCC); Epoch-wise Sleep Stage sensitivity; Epoch-wise Sleep Stage specificity; Epoch-wise Sleep Stage accuracy; AHI sensitivity; AHI specificity

Reported performance (25 observations)

sensitivity0.924
source quote (p.14)
“AHI 1b cutoff = 5 Sensitivity: 0.924”
specificity0.933
source quote (p.14)
“AHI 1b cutoff = 30 Specificity: 0.933”
accuracyas written: “SpO2 Accuracy (Overall Arms)”1.41
source quote (p.14)
“SpO2 Accuracy (Overall Arms) 1.41”
accuracyas written: “PR Accuracy (Arms)”1.04
source quote (p.14)
“PR Accuracy (Arms) 1.04”
sensitivityas written: “Epoch-wise Sleep Stage Wake sensitivity”0.655
source quote (p.16)
“Wake (0) sensitivity 0.655”
specificityas written: “Epoch-wise Sleep Stage Wake specificity”0.901
source quote (p.16)
“Wake (0) specificity 0.901”
accuracyas written: “Epoch-wise Sleep Stage Wake accuracy”0.837
source quote (p.16)
“Wake (0) accuracy 0.837”
sensitivityas written: “Epoch-wise Sleep Stage REM sensitivity”0.713
source quote (p.16)
“REM (1) sensitivity 0.713”
specificityas written: “Epoch-wise Sleep Stage REM specificity”0.93
source quote (p.16)
“REM (1) specificity 0.930”
accuracyas written: “Epoch-wise Sleep Stage REM accuracy”0.905
source quote (p.16)
“REM (1) accuracy 0.905”
sensitivityas written: “Epoch-wise Sleep Stage NREM sensitivity”0.824
source quote (p.16)
“NREM (2) sensitivity 0.824”
specificityas written: “Epoch-wise Sleep Stage NREM specificity”0.738
source quote (p.16)
“NREM (2) specificity 0.738”
accuracyas written: “Epoch-wise Sleep Stage NREM accuracy”0.791
source quote (p.17)
“accuracy 0.791”
sensitivityas written: “AHI 1a cutoff 5 sensitivity”0.868
source quote (p.17)
“AHI cutoff 5 sensitivity 0.868”
specificityas written: “AHI 1a cutoff 5 specificity”0.741
source quote (p.17)
“AHI cutoff 5 specificity 0.741”
sensitivityas written: “AHI 1a cutoff 15 sensitivity”0.876
source quote (p.17)
“AHI cutoff 15 sensitivity 0.876”
specificityas written: “AHI 1a cutoff 15 specificity”0.755
source quote (p.17)
“AHI cutoff 15 specificity 0.755”
sensitivityas written: “AHI 1a cutoff 30 sensitivity”0.806
source quote (p.14)
“AHI cutoff 30 sensitivity 0.806”
specificityas written: “AHI 1a cutoff 30 specificity”0.905
source quote (p.14)
“AHI cutoff 30 specificity 0.905”
sensitivityas written: “AHI 1b cutoff 5 sensitivity”0.924
source quote (p.14)
“AHI cutoff 5 sensitivity 0.924”
specificityas written: “AHI 1b cutoff 5 specificity”0.801
source quote (p.14)
“AHI cutoff 5 specificity 0.801”
sensitivityas written: “AHI 1b cutoff 15 sensitivity”0.909
source quote (p.14)
“AHI cutoff 15 sensitivity 0.909”
specificityas written: “AHI 1b cutoff 15 specificity”0.908
source quote (p.14)
“AHI cutoff 15 specificity 0.908”
sensitivityas written: “AHI 1b cutoff 30 sensitivity”1
source quote (p.14)
“AHI cutoff 30 sensitivity 1.000”
specificityas written: “AHI 1b cutoff 30 specificity”0.933
source quote (p.14)
“AHI cutoff 30 specificity 0.933”

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.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K243268