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510(k) Data Aggregation

    K Number
    K083787
    Date Cleared
    2009-04-15

    (117 days)

    Product Code
    Regulation Number
    870.2700
    Reference & Predicate Devices
    Predicate For
    N/A
    Why did this record match?
    Reference Devices :

    K040214, K070732, K991410

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The BCI® model WW1000 handheld pulse oximeter is intended for spot-checking applications (non-continuous use). It monitors and displays a patient's functional oxygen saturation (%SpO2), pulse rate, pulse signal strength, and pulse amplitude index readings. It may be used by physicians, respiratory therapists, nurses, certified nurse assistants, emergency medical technicians, sleep technicians, clinicians, and home users. The intended patient population ranges from infant to adult. It can be used on patients with low perfusion. The WW1000 may be used in the hospital or clinical environment, during emergency land transport, and in the home.

    Device Description

    The BCI® model WW1000 handheld pulse oximeter is intended for spot-check applications. The WW1000 monitors and displays patient functional oxygen saturation (%SpO2), pulse rate, pulse amplitude index, and pulse signal strength information. It does not have audible or visual patient alarms. The user interface includes a red LED display and an ON/OFF button. The WW1000 comes with disposable AA batteries, the 3044S reusable pulse oximetry sensor and relevant manuals. Optional accessories include other oximetry sensors, docking station, thermal printer (attaches to dock), rechargeable battery pack, universal mains AC charger, patient isolated USB cable, universal mounting bracket and protective

    AI/ML Overview

    The provided text describes the BCI® model WW1000 Pulse Oximeter, its intended use, and the performance testing conducted to support its substantial equivalence. However, it does not explicitly state specific, quantifiable acceptance criteria in the form of a table for device performance (e.g., accuracy +/- X% with Y% confidence). Instead, it refers to general performance expectations and the results of clinical desaturation studies.

    Thus, I will synthesize the information provided to construct a response that best addresses your request, highlighting what is available and what is not.


    Here's an analysis of the acceptance criteria and study information for the BCI® model WW1000 Pulse Oximeter, based on the provided document:

    1. Table of Acceptance Criteria and Reported Device Performance

    The provided document does not explicitly state a table of quantifiable acceptance criteria with specific thresholds for accuracy, precision, or other performance metrics. Instead, it broadly states that "Results of the three individual clinical desaturation trials indicate that the WW1000 pulse oximeter performs as intended and is safe and effective for use." and that "The Micro-power OEM board produced the same readings (within ±1 digit) in all three host devices" during comparison testing.

    Without explicit acceptance criteria, it's impossible to create a direct comparison table. However, the document does imply that the device performance was deemed acceptable based on the clinical desaturation studies (Desat 24, 27, and 40) and comparison testing, which confirmed the expected functionality and consistency across different host devices.

    Implied Acceptance Criterion (based on comparison testing):

    • Deviation between Micro-power OEM board and host devices: <= ±1 digit for SpO2 and Pulse Rate readings.

    Reported Device Performance:

    • The Micro-power OEM board, which provides the complete SpO2 and Pulse Rate measurement for the WW1000, produced readings within ±1 digit across the Evaluation Kit (3375), OxiLink-I, and WW1000 host devices.
    • The clinical desaturation trials (Desat 24, 27, and 40) for the 31392B1 oximeter board (the core measurement component) indicated that the WW1000 pulse oximeter performs as intended and is safe and effective for use.

    2. Sample Size for the Test Set and Data Provenance

    • Sample Size (Clinical Desaturation Studies): The document mentions "three individual clinical desaturation trials" (Desat 24, Desat 27, and Desat 40) for the 31392B1 oximeter board. However, the specific number of subjects/cases used in each of these trials (i.e., the sample size for the test set) is not provided in this summary. Complete desaturation test reports in Section 11 are referenced as containing this detail, but are not included here.
    • Data Provenance: The studies are clinical desaturation studies, implying a prospective and controlled environment where patient oxygen levels are intentionally varied. The country of origin is not specified but given the manufacturer (Smiths Medical, USA) and the FDA submission, it's likely the studies were conducted in the USA or a region with comparable regulatory standards. The studies were conducted in July 2002 (Desat 24), September 2003 (Desat 27), and 2007/2008 (Desat 40).

    3. Number of Experts and Qualifications for Ground Truth

    • The document does not specify the number of experts used to establish the ground truth for the clinical desaturation studies, nor does it explicitly state their qualifications.
    • For pulse oximetry, the "ground truth" for oxygen saturation is typically established by arterial blood gas (ABG) analysis (co-oximetry) performed by trained clinical laboratory personnel. While experts (e.g., medical staff overseeing the study) are involved in patient management and data collection, the ground truth itself is an objective measurement from a reference device (co-oximeter).

    4. Adjudication Method for the Test Set

    • The document does not describe an adjudication method for the test set. This detail is usually relevant for studies involving subjective interpretations (e.g., image analysis by multiple readers). For objective measurements like pulse oximetry compared to co-oximetry, the ground truth is typically a direct measurement, not an expert consensus requiring adjudication.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    • No, an MRMC comparative effectiveness study was not done. The device is a pulse oximeter, not an AI-assisted diagnostic tool that would typically involve multiple human readers interpreting results. The studies focused on the accuracy of the device's measurements against a gold standard.

    6. Standalone Performance Study

    • Yes, a standalone performance study was done. The clinical desaturation studies (Desat 24, 27, and 40) evaluated the accuracy of the 31392B1 oximeter board (which forms the core of the WW1000) by comparing its SpO2 readings directly against a "ground truth" (presumably arterial blood co-oximetry). The comparison testing among the Evaluation Kit, OxiLink-I, and WW1000 host devices also assessed the standalone measurement consistency of the OEM board across different integrations.

    7. Type of Ground Truth Used

    • For the clinical desaturation studies, the ground truth for oxygen saturation (%SpO2) is inherently established by arterial blood gas analysis (co-oximetry), which is considered the gold standard for measuring arterial oxygen saturation. This is standard practice for pulse oximeter accuracy testing.

    8. Sample Size for the Training Set

    • The document describes the device as a pulse oximeter, which traditionally relies on established physiological algorithms and optical principles rather than machine learning or AI models that require "training sets" in the conventional sense. Therefore, no "training set" sample size is applicable or mentioned in this context. The "hardware and software enhancements" mentioned for Desat 40 were likely algorithm refinements based on engineering principles and prior testing, not machine learning model training.

    9. How the Ground Truth for the Training Set Was Established

    • As concluded in point 8, the concept of a "training set" for an AI algorithm is not applicable here. The device's underlying algorithms are based on established physiological models and signal processing, not a machine learning training process that requires a labeled dataset to learn patterns.
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