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Very Low Cost Real-Time Recording of Intra-Operative Cardio-Respiratory Data over the Internet A Definite Reality?

Very Low Cost Real-Time Recording of Intra-Operative Cardio-Respiratory Data over the Internet A Definite Reality?

Anesthesiology Abstracts of Scientific Papers Annual Meeting (2001): Abstract No A-520

Introduction: Hand-written records have been continuously suspected for lack of accuracy, biasing and non-portability. Sampling frequencies that are clearly above the human limits (considering patient care) are required to faithfully record transient life threatening episodes during anesthesia. Therefore, computer-assisted recording systems have been developed to facilitate the anesthesiologist logging tasks. However, the majority of such systems are expensive or require a dedicated connection to every monitor. Our operating rooms are presently equipped with a GE-Marquette cardio-respiratory monitors, that are interconnected in an isolated data network called Marquette Unity Network (MUN). Over this network, they are able to interchange information using the UDP/IP stack with a well-defined proprietary protocol. A flexible and inexpensive (based on a single PC) system that allows simultaneous remote recording of cardio-respiratory parameters from unlimited operating rooms is presented. Methods: A connection from a personal computer (PC) through the MUN was installed. Two programs were developed using object-oriented programming techniques in C to allow recording of intra-operative information. One program acts as a daemon. It runs in the background and continuously captures information about every monitor in the network, such as location, type and IP address. This daemon does not introduce additional traffic into the MUN, it just listens to every packet circulating in the network, filtering and processing only those that offer information about the monitors. The second program acts as a client, sending data requests to the monitors, parsing the information received and logging the cardio-respiratory parameters into a delimited ASCII text file. The program receives as arguments the monitor's IP address (from the first program) and the sampling interval in seconds (defined by the user). In order to reduce CPU utilization between samples, the process is placed in a sleep mode (low CPU usage) between sampling intervals. Since every operating room has different needs, they offer different parameters to be monitored. Hence, the program detects the information offered by each monitor and formats the output file accordingly. In a remote recording system like this, it is imperative to recognize erroneous values due to artifacts, such as lead failure or operative events. Therefore, the client program retrieves such information directly from the monitors at the time of measurement, adding it to the log file as an annotation to the wrong value. Results: To demonstrate the system's low utilization of resources, the programs were tested on an Intel Pentium system (at 75 MHz) equipped with 16 Mbytes of RAM. The operating system used was Microsoft Windows 98. However, it should be noted that the code is portable between any Win32 operating system. Using a sampling interval of 10 seconds, heart rate, blood pressure (mean, systolic and diastolic), arterial pressure (mean, systolic and diastolic), mean central venous pressure, temperature, oxygen saturation, and cardiac output parameters were recorded during robot-assisted minimally invasive direct coronary artery bypass surgery. The resulting log file, without any type of compression, has a length of 358 Kbytes (less than 0.001% of the space available in most commercial hard disks). Simultaneously, processor load (percentage of time that the processor is not idle) was measured, obtaining average variations of 5% (+-1%) for the first instance of the client application and 2% (+-1%) for successive instances. Discussion: Cost-efficient computer assisted recording systems like this, offer the possibility for the creation of extensive high-quality intra-operative data sets that could increase the quality and reliability of anesthesia simulators and computer models, by eliminating bias, and detecting transient responses of extremely short duration. Even more, this information could be observed by any device currently used to access the Internet (since security can be ensured by several methods).

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