Hypotension prediction index in the prediction of better outcomes: a systematic review and meta-analysis
Article information
Abstract
Background
The hypotension prediction index (HPI) is an algorithm designed to predict hypotension. Some studies have reported that HPI-guided hemodynamic management strategies decrease intraoperative hypotension and complications; however, the effect of HPI on reducing perioperative complications is controversial. This meta-analysis aimed to assess the efficacy of the HPI in reducing major complications and intraoperative hypotension.
Methods
We conducted this meta-analysis according to the PRISMA statement and Cochrane Handbook guidelines. A comprehensive literature review was conducted to identify studies focusing on the efficacy of HPI-guided management in reducing intraoperative hypotension and postoperative complications. The PubMed, Embase, Scopus, and Web of Science databases were searched, and the resulting data were combined to calculate the pooled mean differences or risk ratios (RRs) with 95% CIs of both randomized controlled trials (RCTs) and retrospective studies, as appropriate. Heterogeneity and potential publication bias were also assessed.
Results
Nineteen articles (12 RCTs and 7 retrospective studies) with 2570 recruited patients were included in this meta-analysis. The critical evaluation of the study quality revealed a low risk of bias in the included RCTs. Among the non-randomized trials, one was rated 7, two were rated 8, and the remaining four were rated 9 on the Newcastle-Ottawa Scale, indicating high quality and a low risk of bias. HPI-guided management significantly reduced intraoperative hypotension and associated major complications (RR = 0.79, 95% CI [0.69–0.90], I2 = 0, P < 0.001). Blood loss and length of hospital stay were comparable between the groups.
Conclusions
HPI-guided management significantly reduced intraoperative hypotension and major complications.
Introduction
Intraoperative hypotension has gained significant attention in recent years owing to its high incidence and associated harmful effects, including increased myocardial ischemia, neurological deficits, acute renal injury, prolonged hospital stay, and a higher rate of perioperative mortality. Poor prognosis increases with a prolonged mean arterial pressure (MAP) < 65–60 mmHg or with any exposure to an MAP < 55–50 mmHg [1–3].
The hypotension prediction index (HPI) analyzes arterial waveform features, including waveform time, amplitude, area, segment slopes, and complexity features, to predict hypotension, defined as an MAP < 65 mmHg for at least 1 min [4,5]. This index reportedly has high sensitivity and specificity for predicting perioperative hypotension [6].
Recent clinical trials have investigated the effect of HPI-guided management in reducing perioperative hypotension [7,8]. Additionally, a handful of systematic reviews and meta-analyses have confirmed that HPI-guided management effectively alleviates intraoperative hypotension [9–11]. However, subsequent studies have shifted their focus to exploring the potential impact of the HPI on postoperative complications [12–14]. Therefore, we conducted this meta-analysis to evaluate the effects of HPI-guided management on both perioperative hypotension and postoperative complications.
Materials and Methods
We conducted this meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and the guidelines of the Cochrane Handbook for Systematic Reviews (https://training.cochrane.org/handbook/current) [15].
The protocol for the meta-analysis was registered with the International Prospective Register of Systematic Reviews (CRD42024575142) in August 2024.
Study selection
We systematically searched the PubMed, Embase, Scopus, and Web of Science databases to identify relevant articles that (1) compared the HPI with other intraoperative monitoring methods, (2) were published since January 2019, and (3) were either randomized controlled trials (RCTs) or retrospective studies. The following keywords were used: “intraoperative hypotension”, “perioperative hypotension”, “surgery”, “hypotension prediction index”, “HPI”, and “early warning system”. No language restrictions were imposed. The final search was completed in February 2025.
Inclusion criteria
Only studies that met the following criteria were included: (1) clinical studies, (2) patients who underwent surgery with HPI-guided management, (3) standardized protocols for intraoperative hemodynamic management, (4) parallel control groups using other monitoring strategies, and (5) at least one of the following outcomes: postoperative complications or intraoperative hypotension.
Data extraction
Two authors (Y L and B L) primarily reviewed the articles to exclude irrelevant studies according to the inclusion criteria. Any disagreement at any stage was discussed with a third author (W X).
The American Society of Anesthesiologists physical status scores, ages, types of surgery, and study types were extracted from the original articles. The following data were collected for analysis: (1) major complications (cardiac, neurological, renal injury, and mortality), (2) time-weighted average (TWA) of hypotension, (3) total duration of hypotension, (4) area under the hypotensive threshold (AUT), (5) intraoperative blood loss, and (6) length of hospital stay.
The methodological quality and risk of bias of the included RCTs were assessed by two authors (Y L and KX Y) using the Cochrane risk of bias tool (RoB), which consisted of the following seven aspects: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome reporting, and other sources of bias. The revised Cochrane Risk of Bias tool (RoB 2) was used to further judge the risk of bias, which consisted of the following five distinct domains: randomisation process, deviations from the intended interventions, missing outcome data, measurement of the outcome and selection of the reported result.
Non-randomized trials were assessed using the Newcastle-Ottawa Scale (NOS). The highest possible score on the NOS is a 9, and studies with scores ≥ 5 were considered adequate for further analysis (https://www.ohri.ca//programs/clinical_epidemiology/oxford.asp).
Statistical analysis
Statistical analyses were performed using Review Manager software (RevMan 5.4; the Cochrane Collaboration) or R software (version 4.1.3, The R Foundation), as appropriate.
When the original data were expressed as continuous variables, the meta-analysis was performed using mean differences (MDs). When data were reported as medians and interquartile ranges (IQRs), authors or statisticians of the articles were contacted to obtain means and standard deviations [16–18]. Dichotomous variables were determined using risk ratios (RRs) calculated using the Mantel-Haenszel method.
Major complications and intraoperative hypotension were analyzed through a trial sequential analysis (TSA; version 0.9 Beta, Copenhagen Trial Unit) to quantify the statistical reliability of the included data in this meta-analysis. To minimize the heterogeneity among different designed researches and avoid a higher risk of bias, only RCTs were included in the TSA analysis. Specifically, a TSA was conducted to estimate the required information size and assess the risk of type I and II errors [19]. The TSA method is used in meta-analyses to control for the risk of random errors resulting from repetitive testing. This helps determine whether the available evidence is sufficient to draw reliable conclusions or if more studies are needed. The TSA plot showed that the conventional Z-value (Z=1.96) corresponded to the standard significance level (P < 0.05) of a two-sided test. If the cumulative Z-curve crosses this line, this suggests statistical significance in conventional meta-analyses. The TSA monitory boundaries (TSA Z-values) are more stringent thresholds adjusted for the risk of random errors. Crossing these boundaries provides firm evidence that accounts for repeated testing and data sparsity. The cumulative Z-curve plots the Z-values from the meta-analyses as studies are sequentially added in chronological order.
When the cumulative Z-curve of the results exceeds the TSA boundary, a sufficient level of evidence for the anticipated intervention effect has likely been reached at the current condition and same population. However, if the Z-curve does not exceed the TSA boundary, the amount of information is insufficient to reach a firm conclusion. Two-sided tests with a type I error of 5% and a power of 80% were used.
Study heterogeneity was determined by estimating the I2 statistic, which describes the percentage of total variation across studies due to heterogeneity as opposed to chance. Outcome data with low heterogeneity (I2 ≤ 50%) were analyzed using a fixed-effects model. For outcome data with high heterogeneity (I2 > 50%), a random-effects model was used.
Publication bias was evaluated visually using a funnel plot.
Results
Search results
We searched the PubMed, Scopus, Embase, and Web of Science databases. A total of 559 investigations were retrieved. After removing duplicates, 236 articles remained. An additional 17 reviews and meta-analyses, six case reports, nine protocols, and 137 articles without surgery or an HPI apparatus were excluded after screening the titles and abstracts. Sixty-seven full-text articles were thus retrieved.
After a detailed review, we excluded 27 reports with a lack of clinical outcomes and effective control groups, 17 articles that were not research articles, and two that were letters to the editor. Two additional studies were excluded because they did not focus on intraoperative observations. A review of the relevant literature revealed an additional article conducted by Lorente et al. [20]; however, the study population overlapped with that of Ripollés-Melchor et al. [14] and was thus excluded. A total of 19 distinct articles (12 RCTs and 7 retrospective studies) with a total of 2570 recruited patients were thus selected for final analysis in the current study (Fig. 1) [14,21–38].
Flow diagram of the study.
Description of included studies
The key characteristics of the included studies are summarized in Table 1. We compared HPI-guided management with other monitoring strategies. For the control groups, 17 studies defined standard or conventional care, while the remaining two conducted goal-directed fluid therapy (GDFT) and a predefined goal-directed therapy (GDT) strategy. Schneck et al. [28] and de Keijzer et al. [29] conducted three-arm studies, and data from the HPI group and routine anesthetic care were collected for analysis.
Study and Population Characteristics
Methodological quality
A critical evaluation of study quality was performed by two reviewers (Y L and W X), and any disagreement was discussed with another co-author (B L). The risk of bias is shown in Supplementary Figs. 1 and 2 and in Table 1.
As the HPI was used to guide management, the investigators and anesthesiologists could not be blinded during the study; however, the patients participating in the study were blinded. As the HPI was used to guide management, the investigators and anesthesiologists could not be blinded during the study; however, the patients participating in the study and analyzers were blinded. Since the primary outcomes were hypotension and complications, which were unlikely to be influenced by observation bias, we considered the risk of blinding in the included RCTs to be unclear risk of bias. The included RCTs showed minimal risk of bias due to their careful design and execution, as noted in previous systematic reviews. Overall, the risk of bias in these included RCTs was judged as low. RoB2 assessment also showed unclear risk for the blinding related domains and low risk for the most of remaining domains.
Among the non-randomized trials, one was rated 7, two were rated 8, and the remaining four were rated 9 on the NOS scale, indicating high quality and low risk of bias.
Primary outcomes
The primary outcome for this review was the incidence of major complications, including cardiac, neurological, renal injury, and mortality. Fifteen articles reported complications (Fig. 2A). As no complications were observed in the study conducted by Yoshikawa et al. [34], only the complications in the remaining 14 studies were analyzed. Andrzejewska et al. [31] reported a case of transient limb paresis in a patient who underwent posterior spinal fusion for adolescent idiopathic scoliosis. Given that this patient underwent this procedure at such a young age, transient limb paresis was more likely attributable to the surgical procedure itself than intraoperative hypotension. A total of 265 events in the HPI group and 329 events in the control group were reported. The pooled relative risk (RR) was 0.79 (95% CI [0.69–0.90], I2 = 0, P < 0.001). This indicates that the HPI group experienced a 21% reduction in the RR of postoperative complications compared with the control group.
HPI-guided management reduced postoperative complications. (A) HPI-guided management significantly reduced postoperative complications (RR = 0.79, 95% CI [0.69–0.90], I2 = 0, P < 0.001). (B) the TSA in RCTs showed that the estimated n was 2088. The Z-curve crossed both the conventional and TSA Z-curves, indicating significant differences between groups, and further investigations under the same design and same population are unlikely to affect this conclusion under the current conditions. HPI: hypotension prediction index, TSA: trial sequential analysis.
We then performed a TSA for major complications using the included RCTs (Fig. 2B). According to the results, the Z-curve crossed both the conventional and TSA Z-curves before the estimated pooled sample size (2088). It indicated that the pooled complications in the HPI group were different from the control group, and the result was reliable at the current design in the same population.
To elucidate the effects of HPI-guided management on surgical procedures, we conducted a subgroup analysis to mitigate bias due to the study design. The results for RCTs (RR = 0.83, 95% CI [0.72–0.96], I2 = 0, P = 0.01) and non-RCTs (RR = 0.61, 95% CI [0.42–0.89], I2 = 0, P = 0.01) were presented. A robust reduction in complications was found in the HPI group. This indicates that HPI-guided management effectively reduces complications during the perioperative period, regardless of the trial design.
Subgroup analyses were performed to investigate the specific clinical impact of HPI-guided management on each complication (cardiac, neurological, renal injury, and mortality) (Supplementary Fig. 4). Cardiac complications were significantly decreased in the HPI group (RR = 0.68, 95% CI [0.50–0.92], I2 = 0, P = 0.01). Additionally, neurological (RR = 0.72, 95% CI [0.42–1.25], I2 = 0, P = 0.24) and renal (RR = 0.85, 95% CI [0.70–1.01], I2 = 0, P = 0.07) complications showed decreasing trends in the HPI group. No statistically significant difference in mortality was found between the groups under the current conditions (RR = 0.88, 95% CI [0.51–1.52], I2 = 0, P = 0.64).
Secondary outcomes
Intraoperative hypotension
We calculated the TWA of hypotension, AUT, and duration of hypotension as secondary outcomes (Figs. 3–5).
HPI-guided management lowered the TWA. (A) The TWA was significantly lower in the HPI group (MD = −0.15, 95% CI [−0.19 to −0.10], I2 = 65%, P < 0.001). (B) The TSA for the TWA showed an estimated sample size of 1614 patients while we included a total of 812 patients in RCTs. The Z-curve crossed the conventional and Z curve and closed to TSA Z-curve, indicating the required information size was not reached, and further large sample RCTs will help to draw a firm conclusion.
HPI-guided management decreased hypotension duration. (A) HPI-guided management significantly reduced hypotension duration (MD = −8.53, 95% CI [−11.19 to −5.87], I2 = 89%; P < 0.001). (B) The TSA for the duration of hypotension included 10 RCTs involving 801 patients. The Z-curve crossed both the conventional and TSA Z-curves, with an estimated sample size of 541.
HPI-guided management reduced the area under the hypotensive threshold. The area under the hypotensive threshold was significantly reduced in the HPI group (MD = −70.88, 95% CI [−98.22 to −43.54], I2 = 89%, P < 0.001).
Sixteen studies (1545 patients) reported TWA (Fig. 3A). The pooled results indicated that HPI-guided management contributed to a significant reduction in the TWA (MD = −0.15, 95% CI [−0.19 to −0.10], I2 = 65%, P < 0.001). The TSA for the TWA (Fig. 3B) showed an estimated sample size of 1614 patients while we included a total of 812 patients in RCTs. The Z-curve crossed the conventional and Z curve and closed to TSA Z-curve, indicating the required information size was not reached, and further large sample RCTs will help to draw a firm conclusion.
The duration of hypotension and AUT were significantly reduced in the HPI group (MD = −8.53, 95% CI [−11.19 to −5.87], I2 = 89%, P < 0.001 and MD = −70.88, 95% CI [−98.22 to −43.54], I2 = 89%, P < 0.001, respectively) (Figs. 4A and 5).
We performed a TSA on the 10 RCT articles (801 patients) that reported on the duration of hypotension. As shown in Fig. 4B, the Z-curve crossed both the conventional and TSA Z-curves, with an estimated sample size of 514. Therefore, HPI management can significantly decrease the duration of hypotension at the current condition and population. It seems the further investigations might not change the conclusion under exactly the same conditions. Cautious interpretation is needed to use this conclusion due to the heterogeneity and random errors of included researches.
Intraoperative blood loss and length of hospital stay
As shown in Fig. 6A, the pooled results of the 15 included articles indicated no difference in intraoperative blood loss between the groups (MD = 0.01, 95% CI [−0.57 to 0.59], I2 = 49%, P = 0.98).
HPI-guided management on blood loss and length of hospital stay. (A) Blood loss was comparable between the groups (MD = 0.01, 95% CI [−0.57 to 0.59], I2 = 49%, P = 0.98). (B) Nine studies reported the length of hospital stay. Pooled analysis indicated that HPI-guided management tended toward a reduction in hospital stays (MD = −0.76, 95% CI [−2.10 to 0.57], I2 = 83%, P = 0.26).
Nine studies reported the length of hospital stay (Fig. 6B). Pooled analysis indicated that HPI-guided management trended toward a reduction in the hospital stay. However, a significant difference was not found between the groups under the current conditions (MD = −0.76, 95% CI [−2.10 to 0.57], I2 = 83%, P = 0.26).
A funnel plot analysis was performed to evaluate publication bias across the included studies (Supplementary Fig. 5). The distribution of effect sizes showed approximate symmetry, suggesting no substantial evidence of bias.
Discussion
In this study, we analyzed the incidence of major complications and intraoperative hypotension in patients undergoing HPI-guided management. We found that HPI-guided management significantly reduced the incidence of postoperative major complications with the TSA showing that the Z-curve crossed both the conventional and adjusted significance boundaries before the estimated sample size. In addition, HPI-guided management was found to robustly reduce perioperative hypotension.
The HPI has stimulated widespread discussion. A large number of studies have validated its sensitivity and specificity for predicting hypotension [39–41]. However, the cutoff point (varying from 80 to 90), hypotension threshold, and surgical type varied across these studies, potentially affecting the heterogeneity and variability in conclusions [42]. Whether HPI-guided management can reduce the incidence of intraoperative hypotension has been broadly investigated. Recent systematic reviews and meta-analyses have consistently demonstrated the efficacy of HPI-guided management in reducing intraoperative hypotension [9–11].
Further investigations have thus shifted their focus to major postoperative complications associated with perioperative hypotension. In our review, we included additional studies and conducted a TSA to assess the strength of the conclusions. Interestingly, our data indicated that HPI-guided management dramatically reduced various indicators of perioperative hypotension.
To the best of our knowledge, this is the first meta-analysis to assess the effects of HPI-guided management on postoperative complications. The pooled results of these high-quality articles showed a significant reduction in major complications in the HPI group. Severe hypotension can have detrimental effects on the heart, brain, and kidneys, with subsequent damage worsening the patient’s overall condition. Thus, we defined major complications as cardiac, neurological, renal injury, and mortality, as previously described [21,37,43].
The TSA of major complications in RCTs showed that the included articles surpassed both the conventional and TSA Z-curves, with an estimated sample size of 2088. This result agreed with our pooled results in forest plot, that the HPI reduced complications in the determined population. However, the TSA analysis was conducted by a statistical calculation, and the different designs of studies in different populations may result in different outcomes. Thus even the current TSA analysis regarding complication calculation indicated the current conclusion is unlikely to change in further investigations within the current condition and similar population, we appealed for an interpretation of our results with caution. Luckily, protocols for large-sample investigations have been published [44], and we believe that these large-sample RCTs on postoperative outcomes would provide considerable insight into how HPI affects clinical outcomes.
In this study, HPI-guided management was based on an invasive arterial waveform. Interestingly, we have recently noticed a growing interest in non-invasive HPI-guided management [41,45]. Frassanito et al. [46] conducted an investigation showing that non-invasive HPI-guided management could effectively predict hypotension, with a sensitivity of 0.86 (95% CI [0.78–0.93]) and specificity of 0.86 (95% CI [0.77–0.94]), which is comparable to invasive HPI-guided management. This allows for the prediction and potential prevention of hypotension in a much larger patient population, particularly when arterial cannulation is used less frequently.
Given the limitations of retrospective studies, including potential outcome underestimation and observational bias, we conducted subgroup analyses to compare RCTs and non-RCTs for all outcomes. Subgroups consistently demonstrated a significant reduction in complications in the HPI group, indicating that HPI-guided management effectively lowers perioperative complications, regardless of the trial design. While the meta-analysis demonstrated a trend towards reduced hospital stays with HPI-guided management, the marked contrast between the overall heterogeneity of the non-RCT subgroup (I2 = 74%) and the RCT subgroup (I2 = 6%) highlights the fundamental differences across study designs.
To better understand HPI-guided perioperative management, we also performed subgroup analyses of the different types of complications (Supplementary Fig. 4). Consistent with that for the overall major complications, our subgroup analysis revealed a significant decrease in cardiac complications in the HPI group and a trend toward decreasing neurological and renal complications. The fact that the HPI was associated with a significant reduction in all indicators of intraoperative hypotension may indicate that perioperative hypotension could cause different incidences of complications in different organs. Recently, several multi-center, large-sample RCTs have measured complications in various populations [14,35]. We believe that future multi-center, large-sample RCTs will enhance our insights into how the HPI affects different postoperative complications.
Blood loss was also calculated as an outcome. Recently, HPI-guided management has been challenged for overestimating hypotension, potentially leading to unnecessary hypertension and increased blood loss [32,42]. We therefore calculated intraoperative blood loss; however, we found it to be statistically insignificant. This suggests that the cautious use of HPI is safe and does not increase intraoperative blood loss.
One of the limitations of our meta-analysis was that it included both RCTs and retrospective studies, which may have led to high heterogeneity and observational bias. Although we conducted subgroup analyses to mitigate these effects, the inherent limitations of retrospective studies should be considered when interpreting our results. Of the 19 trials, two used GDFT and predefined GDT as controls, while the others utilized conventional monitoring, which may have led to statistical heterogeneity. Second, blood loss and the length of hospital stay showed high heterogeneity. Probable causes include variations in surgical procedures, patient populations, and clinical centers. Large-sample multi-center RCTs are needed to provide better insights into HPI-guided management compared to a precise design, which may minimize the bias on outcomes.
In conclusion, the results of this meta-analysis indicated that HPI-guided management significantly reduces major postoperative complications and dramatically decreases intraoperative hypotension.
Acknowledgements
We thank Wenyi Zhou at Sun Yat-sen memorial hospital for the support of the coding. We thank Yuqin Zhang at Sun Yat-sen University for the statistical support.
Notes
Funding
None.
Conflicts of Interest
No potential conflict of interest relevant to this article was reported.
Data Availability
All data generated or analyzed during this study are included in this published article and its supplementary information files.
Author Contributions
Yi Liu (Conceptualization; Formal analysis; Writing – original draft)
Bei Liu (Formal analysis; Visualization; Writing – original draft)
Wei Xiong (Data curation; Formal analysis)
Chen Wang (Software; Visualization)
Kunxin Yang (Resources; Validation)
Wudi Ma (Data curation; Formal analysis)
Liangtian Lan (Data curation; Formal analysis)
Ming Wei (Investigation; Software)
Nan Jiang (Investigation; Project administration; Validation)
Xia Feng (Conceptualization; Project administration; Writing – review & editing)
Supplementary Materials
Risk of bias graph. All studies showed a low risk of selection bias (random sequence generation), attrition bias, and reporting bias. Most exhibited a low risk of other biases, detection bias, and selection bias (allocation concealment). The overall performance bias was unclear.
Risk of bias summary. The judgment matrix for the 12 studies (x-axis) and seven bias domains (y-axis) is shown. The respective bias assessments for each investigation are classified as low risk (green), unclear risk (yellow), and high risk (red).
Search strategy.
Subgroup analyses of major complications. Cardiac complications were significantly decreased in the HPI group (RR = 0.68, 95% CI [0.50–0.92], I2 = 0, P = 0.01). The pooled analysis indicated that HPI-guided management trended toward a reduction in neurological (RR = 0.72, 95% CI [0.42–1.25], I2 = 0, P = 0.24) and renal (RR = 0.85, 95% CI [0.70–1.01], I2 = 0, P = 0.07) complications. No statistically significant difference in mortality between the groups was found under the current conditions (RR = 0.88, 95% CI [0.51–1.52], I2 = 0, P = 0.64).
Funnel plot of publication bias. The distribution of the effect sizes showed approximate symmetry, suggesting no apparent publication bias.
Risk of bias graph assessed by RoB2. All studies showed a low risk of missing outcome data, measurement of the outcome and selection of the reported result. Most of the RCTs exhibited a low risk of randomization process. The deviation from intended intervention bias was unclear. The overall bias was low.
Risk of bias summary assessed by RoB2. Risk of bias summary. The judgement matrix for the 12 studies using five bias domains is shown. The respective bias assessments for each investigation are classified as low （green）, unclear risk (yellow), and high risk (red).