(219 days)
The T3 Platform™ software features the T3 Data Aggregation & Visualization software module version 5.0 and the T3 Risk Analytics Engine software module version 9.0.
The T3 Data Aggregation & Visualization software module is intended for the recording and display of multiple physiological parameters of the adult, pediatric, and neonatal patients from supported bedside devices. The software module is not intended for alarm notification or waveform display, nor is it intended to control any of the independent bedside devices to which it is connected. The software module is intended to be used by healthcare professionals for the following purposes:
- To remotely consult regarding a patient's status, and
- To remotely review other standard or critical near real-time patient data in order to aid in clinical decisions and deliver patient care in a timely manner.
The T3 Data Aggregation & Visualization software module can display numeric physiologic data captured by other medical devices:
- · Airway flow, volume, and pressure
- · Arterial blood pressure (invasive and non-invasive, systolic, diastolic, and mean)
- Bispectral index (BIS, signal quality index, suppression ratio) .
- Cardiac Index
- Cardiac output .
- Central venous pressure .
- . Cerebral perfusion pressure
- End-tidal CO2 .
- · Heart rate
- Heart rate variability .
- Intracranial pressure .
- . Left atrium pressure
- Oxygen saturation (intravascular, regional, SpO2) .
- Premature ventricular counted beats .
- Pulmonary artery pressure (systolic, diastolic, and mean) .
- Pulse pressure variation
- · Pulse Rate
- · Respiratory rate
- Right atrium pressure .
- Temperature (rectal, esophageal, tympanic, blood, core, nasopharyngeal, skin)
- · Umbilical arterial pressure (systolic, diastolic, and mean)
The T3 Data Aggregation & Visualization software module can display laboratory measurements including arterial and venous blood gases, complete blood count, and lactic acid. T3 Data Aggregation & Visualization software module can display information captured by the T3 Risk Analytics Engine software module.
The T3 Risk Analytics Engine software module calculates four indices: the IDO2 Index™ for inadequate delivery of oxygen, the IVCO2 Index™ for inadequate ventilation of carbon dioxide, the ACD Index™ for acidemia, and the HLA Index™ for hyperlactatemia.
The IDO2 Index™ is indicated for use by health care professionals with post-surgical patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The IDO2 Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation & Visualization software module. When the IDO2 Index™ is increasing, it means that there is an increasing risk of inadequate oxygen delivery and attention should be brought to the patient. The IDO2 Index™ presents partial quantitative information about the patient's cardiovascular condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The IVCO2 Index™ is indicated for use by health care professionals with invasively ventilated patients 0 to 12 years of age under intensive care. The IVCO2 Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation and Visualization software module. When the IVCO2 Index™ is increasing, it means that there is an increasing risk of inadequate carbon dioxide ventilation and attention should be brought to the patient. The IVCO2 Index™ presents partial quantitative information about the patient's respiratory condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The ACD Index™ is indicated for use by health care professionals with invasively ventilated patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The ACD Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation and Visualization software module. When the ACD Index™ is increasing, it means that there is an increasing risk of acidemia and attention should be brought to the patient. The ACD Index™ presents partial quantitative information about the patient's respiratory condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The HLA Index™ is indicated for use by health care professionals with post-surgical patients 0 to 12 years of age and weighing 2 kg or more under intensive care. The HLA Index™ is derived by mathematical manipulations of the physiologic data and laboratory measurements received by the T3 Data Aggregation & Visualization software module. When the HLA Index™ is increasing, it means that there is an increasing risk of hyperlactatemia and attention should be brought to the patient. The HLA Index™ presents partial quantitative information about the patient's cardiovascular condition, and no therapy or drugs can be administered based solely on the interpretation statements.
The Tracking, Trajectory, Trigger (73) intensive care unit software solution allows clinicians and quality improvement teams in the ICU to aggregate data from multiple sources, store it in a database for analysis, and view the streaming data. System features include:
- Adjunctive status indicators ●
- Customizable display of physiologic parameters over the entire patient stay
- . Configurable annotation
- Web-based visualization that may be used on any standard browser
- Minimal IT footprint ●
- Software-only solution no new bedside hardware required ●
- Highly reliable and robust operation
- . Auditable data storage
The T3 Platform™ software calculates four indices: the IDO2 Index™ for inadequate delivery of oxygen, the IVCO2 Index™ for inadequate ventilation of carbon dioxide, the ACD Index™ for acidemia, and the HLA Index™ for hyperlactatemia. The document specifies that studies were performed to validate the IVCO2 Index.
Here's an analysis of the acceptance criteria and study proving the device meets them, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document explicitly states that the acceptance criteria for the IVCO2 Index™ are: discriminatory power, range utilization, resolution/limitation, and robustness. It is stated that "All results met the same acceptance criteria as the predicate device".
However, specific quantitative values for these criteria (e.g., a specific threshold for discriminatory power, or a defined range utilization percentage) and the exact performance metrics obtained are not provided in the given text. The document confirms that the device met these criteria without detailing the quantitative results of the performance.
2. Sample Size Used for the Test Set and Data Provenance
- Test Set 1 (Neonatal ICU patients):
- Sample Size: 180 patients, contributing 1108 PaCO2 measurements from arterial blood gases.
- Data Provenance: Retrospective, obtained from two Level IV regional NICUs in the US.
- Test Set 2 (Non-NICU patients):
- Sample Size: 2090 patients, contributing 29,841 PaCO2 measurements from arterial blood gases.
- Data Provenance: Retrospective, from clinical sites in the US.
- Demographics: 42% neonates, 32% infants, and 26% children. 46% female and 54% male.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
The document does not specify the number of experts or their qualifications used to establish the ground truth for the test set. It mentions "PaCO2 measurements from arterial blood gases," which implies that the ground truth was based on laboratory measurements rather than expert review.
4. Adjudication Method for the Test Set
The document does not mention an adjudication method for the test set. Given that the ground truth appears to be objective laboratory measurements (PaCO2 from arterial blood gases) and not subjective expert interpretations, a traditional adjudication process (like 2+1 or 3+1) would not be applicable or necessary.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC comparative effectiveness study was mentioned. The study described focuses on the device's performance against objective physiological measurements, not on its impact on human reader performance.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
Yes, a standalone performance study was done. The IVCO2 Index™ was "retrospectively computed on all de-identified patients" and "evaluated against the same acceptance criteria as the predicate device." This indicates an algorithm-only evaluation, without human-in-the-loop assistance.
7. Type of Ground Truth Used
The ground truth used was objective physiological data/laboratory measurements, specifically PaCO2 measurements from arterial blood gases.
8. Sample Size for the Training Set
The document mentions "Development test sets are used to evaluate the impact of the development changes during the development process." However, it does not specify the sample size for the training set(s) used to develop the IVCO2 Index™ model. It only provides details for the validation sets.
9. How the Ground Truth for the Training Set Was Established
The document states that the "adjunctive status indicators are produced by a model-based approach. The model-based approach is designed based on principles of physiology with parameters chosen to reflect those specified in the medical literature." It does not explicitly detail how ground truth was established for the training data beyond implying it was based on physiological principles and medical literature, and presumably also included patient data similar to the validation sets.
§ 870.2200 Adjunctive cardiovascular status indicator.
(a)
Identification. The adjunctive cardiovascular status indicator is a prescription device based on sensor technology for the measurement of a physical parameter(s). This device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Software description, verification, and validation based on comprehensive hazard analysis must be provided, including:
(i) Full characterization of technical parameters of the software, including any proprietary algorithm(s);
(ii) Description of the expected impact of all applicable sensor acquisition hardware characteristics on performance and any associated hardware specifications;
(iii) Specification of acceptable incoming sensor data quality control measures; and
(iv) Mitigation of impact of user error or failure of any subsystem components (signal detection and analysis, data display, and storage) on accuracy of patient reports.
(2) Scientific justification for the validity of the status indicator algorithm(s) must be provided. Verification of algorithm calculations and validation testing of the algorithm using a data set separate from the training data must demonstrate the validity of modeling.
(3) Usability assessment must be provided to demonstrate that risk of misinterpretation of the status indicator is appropriately mitigated.
(4) Clinical data must be provided in support of the intended use and include the following:
(i) Output measure(s) must be compared to an acceptable reference method to demonstrate that the output measure(s) represent(s) the predictive measure(s) that the device provides in an accurate and reproducible manner;
(ii) The data set must be representative of the intended use population for the device. Any selection criteria or limitations of the samples must be fully described and justified;
(iii) Agreement of the measure(s) with the reference measure(s) must be assessed across the full measurement range; and
(iv) Data must be provided within the clinical validation study or using equivalent datasets to demonstrate the consistency of the output and be representative of the range of data sources and data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment.
(5) Labeling must include the following:
(i) The type of sensor data used, including specification of compatible sensors for data acquisition;
(ii) A description of what the device measures and outputs to the user;
(iii) Warnings identifying sensor reading acquisition factors that may impact measurement results;
(iv) Guidance for interpretation of the measurements, including warning(s) specifying adjunctive use of the measurements;
(v) Key assumptions made in the calculation and determination of measurements;
(vi) The measurement performance of the device for all presented parameters, with appropriate confidence intervals, and the supporting evidence for this performance; and
(vii) A detailed description of the patients studied in the clinical validation (
e.g., age, gender, race/ethnicity, clinical stability) as well as procedural details of the clinical study.