OrthoNext Platform System

K242270

Orthofix Srl · cleared 2024-12-19 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The subject OrthoNext™ Platform System is a web-based modular software system, indicated for assisting healthcare professionals in planning of orthopedic surgery and treatment both preoperatively and postoperatively, including deformity analysis and correction with several Orthofix products.”
AlgorithmAI/ML algorithm for automatic marker detection
source quote (p.10)
“In addition, considerations on accuracy, specificity and sensitivity of the AI/ML algorithm for the automatic marker detection have been included in the submission:”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

n=1,000 images

endpoints: zero false positives; precision; accuracy; TPR/recall; FPR; F1 Score

Bench

sample size not stated

endpoints: mean error for linear measurements; mean error for angular measurements; mean percentage error for linear measurements; mean percentage error for angular measurements

Reported performance (8 observations)

sensitivity0.75
source quote (p.10)
“AI/ML Algorithm Sensitivity (TPR): 0.75”
accuracyas written: “AI/ML Algorithm Accuracy”0.8
source quote (p.10)
“AI/ML Algorithm Accuracy: 0.8”
specificityas written: “AI/ML Algorithm Specificity (Precision)”1
source quote (p.10)
“AI/ML Algorithm Specificity (Precision): 1”
ppvas written: “Precision”1
source quote (p.11)
“Precision 1”
accuracyas written: “Accuracy”0.8
source quote (p.11)
“Accuracy 0.8”
sensitivityas written: “TPR/Recall”0.75
source quote (p.11)
“TPR/Recall 0.75”
f1as written: “F1 Score”0.86
source quote (p.11)
“F1 Score 0.86”
iouas written: “Intersection over Union (%)”79
source quote (p.12)
“Intersection over Union (%) 79”

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
3
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 Radiology 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/K242270