RESUMO
BACKGROUND: The Hypotension Prediction Index is designed to predict intraoperative hypotension in a timely manner and is based on arterial waveform analysis using machine learning. It has recently been suggested that this algorithm is highly correlated with the mean arterial pressure itself. Therefore, the aim of this study was to compare the index with mean arterial pressure-based prediction methods, and it is hypothesized that their ability to predict hypotension is comparable. METHODS: In this observational study, the Hypotension Prediction Index was used in addition to routine intraoperative monitoring during moderate- to high-risk elective noncardiac surgery. The agreement in time between the default Hypotension Prediction Index alarm (greater than 85) and different concurrent mean arterial pressure thresholds was evaluated. Additionally, the predictive performance of the index and different mean arterial pressure-based methods were assessed within 5, 10, and 15 min before hypotension occurred. RESULTS: A total of 100 patients were included. A mean arterial pressure threshold of 73 mmHg agreed 97% of the time with the default index alarm, whereas a mean arterial pressure threshold of 72 mmHg had the most comparable predictive performance. The areas under the receiver operating characteristic curve of the Hypotension Prediction Index (0.89 [0.88 to 0.89]) and concurrent mean arterial pressure (0.88 [0.88 to 0.89]) were almost identical for predicting hypotension within 5 min, outperforming both linearly extrapolated mean arterial pressure (0.85 [0.84 to 0.85]) and delta mean arterial pressure (0.66 [0.65 to 0.67]). The positive predictive value was 31.9 (31.3 to 32.6)% for the default index alarm and 32.9 (32.2 to 33.6)% for a mean arterial pressure threshold of 72 mmHg. CONCLUSIONS: In clinical practice, the Hypotension Prediction Index alarms are highly similar to those derived from mean arterial pressure, which implies that the machine learning algorithm could be substituted by an alarm based on a mean arterial pressure threshold set at 72 or 73 mmHg. Further research on intraoperative hypotension prediction should therefore include comparison with mean arterial pressure-based alarms and related effects on patient outcome.
Assuntos
Pressão Arterial , Hipotensão , Complicações Intraoperatórias , Monitorização Intraoperatória , Valor Preditivo dos Testes , Humanos , Hipotensão/diagnóstico , Hipotensão/fisiopatologia , Estudos Prospectivos , Feminino , Masculino , Pressão Arterial/fisiologia , Pessoa de Meia-Idade , Complicações Intraoperatórias/diagnóstico , Complicações Intraoperatórias/fisiopatologia , Complicações Intraoperatórias/prevenção & controle , Monitorização Intraoperatória/métodos , IdosoRESUMO
OBJECTIVE: To study the effect of ERAS on a textbook outcome (TO) after elective renal surgery. PATIENTS AND METHODS: Retrospective study of all patients who underwent a robot-assisted laparoscopic partial or radical nephrectomy or robot-assisted laparoscopic radical nephroureterectomy in Medisch Spectrum Twente (MST), Enschede, the Netherlands. In total, 277 patients were included. 66 patients from 2018 to 2021 (pre-ERAS group) and 211 patients from 2021 to 2023 (ERAS group). TO is a maximum of two nights in the hospital after surgery, no severe complications during or after surgery ≥ grade IIIb, no blood transfusions, no intensive care, no readmissions, and no mortality within 30 days after surgery. Comparisons were made between the pre-ERAS and ERAS groups using unpaired t-test, Mann-Whitney U test, the chi-squared test or Fisher's exact test. Multivariate logistic regression was used to adjust for possible confounding. RESULTS: TO was significantly (p = 0.005) better in the ERAS group (TO = 76.8%) compared to the pre-ERAS group (TO = 59.1%). Compared to a pre-ERAS patient, the adjusted odds ratio for achieving a TO as an ERAS patient is 2.1 (95% CI 1.15-3.78). CONCLUSIONS: The implementation of ERAS showed a positive effect on the TO of elective renal surgery patients.