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The finger-cuff system CNAP (CNSystems Medizintechnik, Graz, Austria) allows non-invasive automated measurement of pulse pressure variation (PPV CNAP ). We sought to validate the PPV CNAP -algorithm and investigate the agreement between PPV CNAP  and arterial catheter-derived manually calculated pulse pressure variation (PPV INV ). This was a prospective method comparison study in patients having neurosurgery. PPV INV  was the reference method. We applied the PPV CNAP -algorithm to arterial catheter-derived blood pressure waveforms (PPV INV−CNAP ) and to CNAP finger-cuff-derived blood pressure waveforms (PPV CNAP ). To validate the PPV CNAP -algorithm, we compared PPV INV−CNAP  to PPV INV . To investigate the clinical performance of PPV CNAP , we compared PPV CNAP  to PPV INV . We used Bland–Altman analysis (absolute agreement), Deming regression, concordance, and Cohen's kappa (predictive agreement for three pulse pressure variation categories). We analyzed 360 measurements from 36 patients. The mean of the differences between PPV INV−CNAP  and PPV INV  was −0.1% (95% limits of agreement (95%-LoA) −2.5 to 2.3%). Deming regression showed a slope of 0.99 (95% confidence interval (95%-CI) 0.91 to 1.06) and intercept of −0.02 (95%-CI −0.52 to 0.47). The predictive agreement between PPV INV−CNAP  and PPV INV  was 92% and Cohen’s kappa was 0.79. The mean of the differences between PPV CNAP  and PPV INV  was −1.0% (95%-LoA−6.3 to 4.3%). Deming regression showed a slope of 0.85 (95%-CI 0.78 to 0.91) and intercept of 0.10 (95%-CI −0.34 to 0.55). The predictive agreement between PPV CNAP  and PPV INV  was 82% and Cohen’s kappa was 0.48. The PPV CNAP -algorithm reliably calculates pulse pressure variation compared to manual offline pulse pressure variation calculation when applied on the same arterial blood pressure waveform. The absolute and predictive agreement between PPV CNAP  and PPV INV  are moderate.

Non-invasive measurement of pulse pressure variation using a finger-cuff method (CNAP system): a validation study in patients having neurosurgery