Less invasive and noninvasive methods are emerging for haemodynamic monitoring. Among them is Capstesia, a smartphone app that, from photographs of a patient monitor showing invasive arterial pressure, estimates advanced haemodynamic variables after digitising and analysing the pressure curves.OBJECTIVE
The aim of this study was to compare the level of agreement between the analysis of the signals obtained from the patient monitor and a photograph of the same images using the Capstesia app.DESIGN
Araba University hospital (Txagorritxu), Vitoria-Gasteiz, Alava, Spain, from January to February 2015.PATIENTS
Twenty patients (229 images) who had an arterial catheter (radial or femoral artery) inserted for haemodynamic monitoring.INTERVENTION
Snapshots obtained from the patient monitor and a photograph of these same snapshots using the Capstesia application were assessed with the same software (MATLAB, Mathworks, Natick, Massachusetats, USA) for evaluating the level of concordance of the following variables: pulse pressure variation (PPV), cardiac output (CO) and maximum slope of the pressure curve (dP/dt). Comparison was made using interclass correlation coefficients with corresponding 95% confidence intervals, and Bland–Altman plots with the corresponding percentages of error.MAIN OUTCOME MEASURES
(PPV). Secondary outcome: CO and maximum slope of the pressure curve [dP/dt].RESULTS
The interclass correlation coefficients for PPV, CO and max dP/dt were 0.991 (95% confidence interval 0.988 to 0.993), 0.966 (95% confidence interval 0.956 to 0.974) and 0.962 (95% confidence interval 0.950 to 0.970), respectively. In the Bland–Altman analysis, bias and limits of agreement of PPV were (0.50% ± 1.42) resulting in a percentage of error of 20% for PPV. For CO they were 0.19 ± 0.341, with a 13.8% of error. Finally bias and limits of agreement for max dP/dt were 1.33 ± 77.71, resulting in an error of 14.20%CONCLUSIONS
Photograph of the screenshots obtained with the Capstesia app show a good concordance with analysis of the original screenshots. Either approach could be used to monitor the haemodynamic variables assessed.