Music as Intervention Nursing in Ambulances

Overview

Background: Patients with acute cardiovascular disease require out-of-hospital care during the most critical and vulnerable periods of their illness. Objectives: To evaluate the influence of music intervention in patients with an acute cardiovascular condition during their transfer in Advanced Life Support (ALS) ambulances. Method: A controlled, randomized experimental analytical study of cases and controls. The intervention group was exposed to relaxing music with sounds from nature. Data related to demographic factors, comorbidities, clinical constants, and drugs administered were gathered. The qualitative variables were summarized using counts and percentages, and the quantitative variables through means and standard deviations.

Out-of-hospital Emergency Services are characterized by providing urgent health care, to patients in critical health circumstances, at the place where the event occurs. This fact means that the Advanced Life Support (ALS) ambulances are present when the patient presents a higher degree of stress and, therefore, where greater changes can be found at the physiological level. This is reflected in alterations in the vital signs, which a can increase the pathophysiological effects, as the patient is placed in a hostile and unfamiliar environment, such as the ambulance cabin, surrounded by noises produced by the electromedical equipment and the circumstances of the transport itself (sirens, potholes, speed bumps, …). In a cabin with these characteristics, the patient may feel claustrophobic, an effect that can be enhanced by the limitation of movement generated by the anchoring of the seat belts to the stretcher and the lack of family support. The implementation of ALS is relatively young, hence research in this emerging field, has been scarce in scientific production in the discipline of emergencies compared with other specialties in Spain Data were collected with regard to demographic data (age and gender), medical diagnosis, systolic and diastolic blood pressure (SBP and DBP), heart rate (HR), respiratory rate (RR), partial oxygen saturation (SpO2), the concentration of carbon dioxide at the end of exhalation (EtCO2), the pain perceived by means of the visual analog scale (VAS), the bispectral index (BIS) and the temperature (T) every 15 minutes during the transfer. Data related to administered drugs were also collected, grouped into: antiarrhythmics, antiemetics and opioids. In order to facilitate the collection and recording of data, the nursing report of Castilla La Mancha's Management of Emergencies and Medical Transport (GUETS) has been used, to which the parameters that are not usually collected are routinely added, such as the BIS and EtCO2. For the measurement of vital signs, a manual defibrillator of the Zoll® E-series brand was used. Temperature was recorded with a WelchAllyn brand Sure Temp® PLUS thermometer, the ambient temperature was maintained at around 22-23ºC for comfort. Hypnosis and pain level data were obtained with the BIS VISTA ™ Monitoring System. The music system used was a BTS dynamic mini speaker, model MS109. The decibels were measured in the passenger cabin during the transfer, being in a range of 48.6 - 59.5 dB reaching a maximum of 73.1 dB when driving over a speed bump, and a maximum of 77.7 dB when putting on the sirens. Consequently, the volume was adjusted between 65-70 dB, to mask the usual sounds of the cabin. The qualitative variables have been summarized using counts and percentages. The mean and standard deviation were used to summarize the quantitative variables. The Kolmogorov-Smirnov test was employed to verify the hypothesis of normality. Depending on the test result, a parametric test (t test for two independent samples) or a non-parametric test (Mann-Whitney U test) was used. For qualitative variables, the Chi-square test or Fisher's exact test were used according to the fulfillment of the approximation conditions. An adjusted multivariate logistic regression model was used to try to characterize the patients in each of the groups considered. For its construction, those variables that presented a p-value \<0.10 in the univariate study have been considered. The ODDS Ratio and its corresponding 95% confidence interval were calculated. To validate the model, the Hosmer and Lemeshow (HL) goodness of fit test was performed. Nagelkerke's R2 coefficient was used to estimate the proportion of the explained variance. The precision of the model was evaluated using the area under the curve (AUC). A p-value of less than 0.05 was considered significant. The analyses were performed with the IBM SPSS v25 statistical package.