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The Nihon Kohden Vital Sign Telemeter GZ-140P is intended to monitor and transmit physiological data from a patient to a Nihon Kohden monitor via radiofrequency in the 802.11 band for continuous monitoring. GZ-140P transmits electrocardiogram (ECG), respiration data, blood oxygen saturation (SpO2) and non-invasive blood pressure (NIBP). The device may generate an audible and or visible alarm when an arrhythmia exists, when a measured physiological rate falls outside preset limits, or when a technical error is detected. Furthermore, the device can be configured for use as a temporary simple monitor to display the patient's vital signs on the device screen and generate alarms without transmitting the data to other Nihon Kohden monitor.

The device is intended to be used by qualified medical facility, such as hospital or clinic, on all patient populations including adult, neonate, infant, child, and adolescent subgroups, with the exception of NIBP measurement which is not intended for use on neonates.

The Nihon Kohden Vital Sign Telemeter GZ-140P is mainly used as a telemetry system within a medical facility. The device transmits patient's vital signs (ECG, SpO2, respiration, and blood pressure) and alarm information via wireless LAN connection to the central monitoring station. The device can be configured to display the patient's vital signs on the screen and generate alarms and used as a temporary simple monitor.

The provided text describes the Nihon Kohden Vital Sign Telemeter GZ-140P and its substantial equivalence to predicate devices, but it does not contain the specific details required to complete all sections of your request related to acceptance criteria, device performance, and study methodology for an AI/algorithm-based device in the way you've outlined.

The document discusses the device's function (monitoring and transmitting physiological data), its indications for use, and a comparison of its technological characteristics to predicate devices. It mentions that the atrial fibrillation detection algorithm is the same as a previously cleared device (QP-039P, K152305) and that the iNIBP (Inflation Mode) measurement was "validated in the clinical testing (Attachment 015)". However, Attachment 015 and its contents are not provided in this text.

Therefore, I cannot extract specific quantitative acceptance criteria or detailed study results (like sample sizes, expert qualifications, or MRMC study details) for the GZ-140P's arrhythmia detection or NIBP measurement from the provided FDA 510(k) summary letter.

Here's what I can extract and what is missing based on the provided text:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or specific reported device performance metrics in a readily extractable table format for features like arrhythmia detection accuracy or NIBP measurement precision for the GZ-140P itself. It relies on substantial equivalence and reference to previously cleared algorithms/devices.

What is mentioned:

• Atrial Fibrillation Detection Algorithm: "is exactly same as that of Nihon Kohden Afib Detection Program QP-039P (K152305)." This implies that the performance of K152305 serves as the reference.
• iNIBP (Inflation Mode) Measurement: "was validated in the clinical testing (Attachment 015)." The details of this validation, including performance metrics and acceptance criteria, are contained within Attachment 015, which is not provided.

Study Details (Based on available information and inferences)

As the document is a 510(k) summary, it focuses on substantial equivalence rather than a full clinical study report for this specific device's de novo performance. The details you've requested are typically found in the full submission or predicate device's documentation.

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: Not specified for the GZ-140P directly. The iNIBP validation was done via "clinical testing (Attachment 015)," but sample size is not stated here.
   • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). Clinical testing implies prospective collection for that specific validation, but full details are missing.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not specified in this document. This would be part of the "clinical testing (Attachment 015)" or the study for K152305.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not specified in this document.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • Not indicated. This device is primarily a physiological data acquisition and transmission system with integrated algorithms (like AFib detection). The text does not describe an AI assistance role for human readers or an MRMC study. The AFib detection is a standalone algorithm.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, implicitly for the AFib detection algorithm. The document states, "The atrial fibrillation detection algorithm is exactly same as that of Nihon Kohden Afib Detection Program QP-039P (K152305)." This implies that the standalone performance of QP-039P was already established and used as justification.
   • Not explicitly detailed for NIBP or other measurements beyond mentioning "clinical testing."

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Not specified in this document. For physiological measurements like NIBP, ground truth is typically established by reference measurement devices or highly trained clinicians following specific protocols. For arrhythmia detection, it's typically expert-adjudicated ECG tracings.

7. The sample size for the training set:

   • Not specified. Given that the AFib algorithm is a previously cleared one (K152305), its training would have predated this submission. No information on training data for the GZ-140P itself is provided.

8. How the ground truth for the training set was established:

   • Not specified. This pertains to the development of the QP-039P algorithm or other internal algorithms; details are not in this summary.

In summary, this 510(k) summary relies on demonstrating substantial equivalence to predicate devices and previously cleared algorithms rather than presenting a de novo, detailed performance study for the GZ-140P's integrated functions. The key details about quantitative performance and study methodologies (especially for the atrial fibrillation detection and iNIBP validation) are either assumed based on prior clearances or are contained in referenced attachments not included here.

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The Spot Vital Signs Ultra automatically measures systolic and diastolic pressure, Mean Arterial Pressure (MAP), pulse rate, temperature (oral, adult axillary, pediatric axillary, rectal, and ear), and pulse oximetry (SpO2) of adult and pediatric patients. Furthermore, Spot Vital Signs Ultra allows the manual entry of height, weight, respiration, and pain level. Spot Ultra also calculates Body Mass Index (BMI) following height and weight entry.

The device is intended to be used by clinicians and medically qualified personnel. It is available for sale only upon the order of a physician or licensed health care provider.

The Welch Allyn Spot Ultra Vital Signs (Spot Vital Signs LXi) is not a monitor, but a one-time vital signs measurement device. This product will not have continuous monitoring capability with timed cycle intervals or any various programmable alarm features. Welch Allyn Spot Vital Signs LXi will include Blood Pressure with Temp, as the base feature, SpO2 is an option. A mobile stand, custom wall mount, an external printer, a barcode reader, weight scales and 802.11 a,b,g wireless communications are accessories that Welch Allyn Spot Ultra Vital Signs Device can be configured.

The Welch Allyn Spot Vital Signs LXi is designed to non-invasively measure systolic and diastolic blood pressure, pulse rate, temperature, and oxygen saturation (spO2) for adult and pediatric patients. The Welch Allyn Spot Vital Signs LXi will also calculate Mean Arterial Pressure (MAP). All blood pressure, pulse, temperature, and SpO2 values are displayed on a large, easy-to-read LCD display, and may be printed via an external thermal printer, as desired. The rechargeable battery and wide variety of mounting accessories make the Welch Allyn Spot Ultra Vital Signs Device convenient for many locations. The Spot Vital Sign LXi will also allow for data entry for weight, height, pain and will calculate Body Mass Index (BMI).

Here's an analysis of the provided text regarding the Welch Allyn Spot Ultra Vital Signs and Welch Allyn Spot Vital Signs LXi, focusing on acceptance criteria and the supporting study:

Important Note: The provided text is a 510(k) summary for a premarket notification. This document primarily focuses on demonstrating "substantial equivalence" to a predicate device (Welch Allyn Spot Ultra Vital Signs K040490) rather than presenting a comprehensive standalone clinical study report. Therefore, some of the requested information, particularly detailed acceptance criteria for a new clinical study and comprehensive study statistics, might not be explicitly stated for the current 510(k) submission but are instead referenced back to the predicate device's clearance.

Acceptance Criteria and Device Performance

The provided 510(k) pertains to a device, the Welch Allyn Spot Ultra Vital Signs (and LXi model), which is stated to have "no hardware or software modifications" from its predicate device (Welch Allyn Spot Ultra Vital Signs K040490). The core argument for this submission is that the new device is substantially equivalent to the predicate. Therefore, the "acceptance criteria" for this specific 510(k) are implicitly met by demonstrating that the device is functionally identical to a previously cleared device.

The essential performance required of the device in this submission is that it performs equivalently to the predicate device, which itself would have met specific performance standards. The key performance aspect highlighted is for Blood Pressure (BP) measurement.

Study Details

Given that the current 510(k) is based on substantial equivalence and states "There are no hardware or software modifications to the Spot Ultra Vital Signs Device," the detailed study information below refers to the validation study conducted for the predicate device (Welch Allyn Spot Ultra Vital Signs K040490), which the current device references for its performance claims.

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not explicitly stated in this 510(k) summary for the predicate device's validation. The summary refers to an "AAMI SP10 - validation report." AAMI SP10 (now ANSI/AAMI/ISO 81060-2) typically requires a minimum of 85 subjects for clinical validation of non-invasive sphygmomanometers.
   • Data Provenance: Not specified in this document. It would have been part of the original K040490 submission.
   • Retrospective or Prospective: Not specified in this document for the predicate's study. AAMI SP10 validations are typically prospective clinical studies.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable in the same way as AI/imaging studies. For blood pressure validation, an independent, "blinded" observer (or two for inter-observer variability checks) typically measures reference blood pressure according to a strict protocol (e.g., using a mercury sphygmomanometer or an oscillometric reference device simultaneously). The qualifications would typically be trained medical personnel, but not "experts" in the context of interpreting complex images or diagnoses.

3. Adjudication method for the test set:

   • Not directly applicable to blood pressure validation in the same way it is for imaging. The "ground truth" for blood pressure is established through a standardized, direct measurement protocol (e.g., AAMI SP10 protocol), not through expert consensus or adjudication of ambiguous cases.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No, an MRMC study was not done. This device is a vital signs measurement device, not an AI-assisted diagnostic imaging system. Therefore, the concept of "human readers improving with AI assistance" is not relevant here.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, in essence, the performance of the oscillometric blood pressure algorithm and other measurement modules is evaluated in a standalone manner. The "AAMI SP10 – validation report" would demonstrate the inherent accuracy of the device's measurements compared to a reference standard, independent of human interpretation improvements. The vital signs are automatically measured and displayed, meaning the device's accuracy is its standalone performance.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • Reference Standard Measurements: For blood pressure, the ground truth is established through simultaneous, highly accurate, auscultatory blood pressure measurements performed by a trained observer using a calibrated reference device (e.g., mercury sphygmomanometer) as per AAMI SP10 standards. For SpO2 and temperature, similar reference devices and protocols would be used.

7. The sample size for the training set:

   • Not specified. For a traditional medical device (not an AI/ML device in the sense of learning from data), there isn't a "training set" in the same way there would be for a machine learning algorithm. The algorithm for oscillometric BP is developed and refined based on engineering principles and physiological models, then validated on a test set.

8. How the ground truth for the training set was established:

   • Not applicable as there is no "training set" for the current device in the context of iterative algorithm learning from labeled data. The ground truth for validation (see point 6) is established through reference standard measurements.

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