Use of generalised additive models to categorise continuous variables in clinical prediction

13 P.

Aireztapenen maiztasunaren neurketa bihotz biriketako berpiztean kapnografia erabiliz.

[EN]Hyperventilation, which is common both in-hospital and out-of-hospital cardiac arrest, decreases coronary and cerebral perfusion contributing to poorer survival rates in both animals and humans. Current resucitation guidelines recommend continuous monitoring of exhaled carbon dioxide (CO2) during cardiopulmonary resucitation (CPR) and emphasize good quality of CPR, including ventilations at 8-10 min1. Most of commercial monitors/de- brilators incorporate methods to compute the respiratory rate based on capnography since it shows uctuations caused by ventilations. Chest compressions may induce artifacts in this signal making the calculation of the respiratory rate di cult. Nevertheless, the accuracy of these methods during CPR has not been documented yet. The aim of this project is to analyze whether the capnogram is reliable to compute ventilation rate during CPR. A total of 91 episodes, 63 out-of-hospital cardiac arrest episodes ( rst database) and 28 in-hospital cardiac arrest episodes (second database) were used to develop an algorithm to detect ventilations in the capnogram, and the nal aim is to provide an accurate ventilation rate for feedback purposes during CPR. Two graphic user interfaces were developed to make the analysis easier and another two were adapted to carry out this project. The use of this interfaces facilitates the managment of the databases and the calculation of the algorithm accuracy. In the rst database, as gold standard every ventilation was marked by visual inspection of both the impedance, which shows uctuations with every ventilation, and the capnography signal. In the second database, volume of the respiratory ow signal was used as gold standard to mark ventilation instants since it is not a ected by chest compressions. The capnogram was preprocessed to remove high frequency noise, and the rst di erence was computed to de ne the onset of inspiration and expiration. Then, morphological features were extracted and a decission algorithm built based on the extracted features to detect ventilation instants. Finally, ventilation rate was calculated using the detected instants of ventilation. According to the results obtained in this project, the capnogram can be reliably used to give feedback ventilation rate, and therefore, on hyperventilation in a resucitation scenario.

Proposal and validation of methodologies for the categorisation of continuous variables in the development of prediction models

158 p.

Pazienteen bihotz eta arnasketa maiztasunen monitorizazioa burmuineko infragorri hurbileko espektroskopia seinaleak erabiliz

Lan honen helburua, burmuineko oxigeno maila neurtzeko NIRS (Near Infrarred Spectroscopy) teknika ez-inbaditzaileaz baliatzen den sistema baten eraginkortasuna neurtzea da, pazientearen parametro fisiologikoak diren bihotz eta arnasketa maiztasunak neurtzerako orduan. Orain arte, pazientearen oxigenazioaren monitorizazioa gauzatzea beharrezkoa den egoeratan, atzamarreko oxigenazio maila neurtzea ahalbidetzen duen PPG (Photoplethysmogram) teknika erabili da. Emergentzia egoeratan, ordea, sistema kardiobaskularrak bizi irauteko nahitaezkoak diren organoei ematen die lehentasuna, garuna eta bihotzari, alegia. Bi organo hauek oxigeno jario jarraituaz hornituak direla egiaztatzeko, ezinbestekoa izango da burmuineko oxigenazio maila neurtzea eta berriki frogatu da NIRS teknikak esparru honetan etorkizun handiko emaitzak eskaini ditzakeela. Hau dela eta, azken urteotan, NIRS teknikak lekua hartu dio orain arte agertoki mediku gehienetan erabilitako PPG teknikari, gaur egun teknika hau aplikazio ugaritan erabiltzen hasia delarik, adibidez kirurgia kardiobaskularraren monitorizazioa edo anestesia orokorraren bitarteko monitorizazioa. NIRS teknikak, garuneko oxigenazio mailaz aparte, pazientearen beste hainbat parametro fisiologikoren neurketa ahalbidetuko balu (arnasketa eta bihotz maiztasuna), agertoki mediku asko erraztuko lituzke, gailu bakar batekin pazientearen bizi-konstante anitzen monitorizazio eramango baitzen aurrera. Tresna hau egingarria dela egiaztatzeko, lehenik eta behin, NIRS seinalea bizi-konstante hauen berri emateko gai dela balioetsi behar da eta hauxe da, hain zuzen, proiektu honen xede nagusia. Azken helburu hau lortzeko, hainbat azpi-helburu proposatzen dira hemen aurkeztuko den proiektuan: lehenik eta behin, NIRS seinaleak eta bizi konstante hauek era fidagarrian lortzea ahalbidetzen duten seinaleak biltegiratzen dituen datu base bat sortuko da. Datu base hau osatzeko, aurreko seinale guztiak aldi berean eskuratuko dituen neurketa sistema sinkrono bat sortzea ezinbestekoa izango da eta azkenik, NIRS seinaleen eraginkortasuna ebaluatzeko, seinaleen prozesaketan oinarritutako hainbat algoritmo garatuko dira.