Tyto Insights for Rhonchi Detection

K243567

Tyto Care , Ltd. · cleared 2025-04-07 · product code PHZ · Anesthesiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The Tyto Insights for Rhonchi Detection is a prescription-use artificial intelligence (AI) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older).”
Algorithmweb-based AI-enabled software system
source quote (p.6)
“The Tyto Insights for Rhonchi Detection is a web-based AI-enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Rhonchi is detected within the recorded sound data.”
Adaptive (vs locked)Yes
source quote (p.13)
“Re-training of the ML model with additional data to improve the performance) of the re-trained algorithm compared to the original device while the same type and range of input signal is used.”
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP).”
Cybersecurity addressedYes
source quote (p.10)
“Cybersecurity- all the applicable information to reflect effective cybersecurity management and to address the FDA's recommendations described in Cybersecurity in Medical Devices: Refuse to Accept Policy for Cyber Devices and Related Systems Under Section 524B of the FD&C Act, March 2023, September 2023.”

Validation studies (1)

Retrospective clinical

n=400 patients

endpoints: non-inferiority of AUC difference between device and clinical readers; repeatability of the software

standards: ANSI AAMI ISO 14971:2019, ANSI AAMI IEC 62304:2006/A1:2016, ISO 15223-1 Fourth edition 2021-07, ANSI AAMI IEC 62366-1:2015+AMD1:2020

Reported performance (5 observations)

sensitivity0.6CI 0.50-0.69
source quote (p.11)
“Sensitivity (Se) 0.60 (0.50-0.69)”
specificity0.99CI 0.97–1.00
source quote (p.11)
“Specificity (Sp) 0.99 (0.97–1.00)”
aurocas written: “auc”0.96CI 0.92-0.98
source quote (p.12)
“AUC Tyto Insights for Rhonchi Detection 0.96 (0.92-0.98)”
ppvas written: “Positive Predictive Value”0.74CI 0.41–1.00
source quote (p.11)
“Positive Predictive Value (PPV) 0.74 (0.41–1.00)”
npvas written: “Negative Predictive Value”0.99CI 0.98–0.99
source quote (p.11)
“Negative Predictive Value (NPV) 0.99 (0.98–0.99)”

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
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

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/K243567