Nils Daum1,2
Daniel Bill1Moritz Thiele2Julian Felber2Dario von Wedel2
Claudia Spies1
Felix Balzer2Rudolf Mörgeli1
Oliver Hunsicker1
Anika Müller1Dennis Contag1Anne Pohrt3Annika Bald1
Max Kayser1
Sascha Treskatsch4
Maximilian Markus1*
- 1Department of Anesthesiology and Intensive Care Medicine (CCM/CVK), Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt, Universität zu Berlin, Berlin, Germany
- 2Institute of Medical Informatics, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- 3Institute for Biometry and Clinical Epidemiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- 4Department of Anesthesiology and Intensive Care Medicine (CBF), Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt, Universität zu Berlin, Berlin, Germany
Background: Intraoperative hypotension (IOH) presents a risk factor for postoperative organ dysfunction. However, as a unique definition of IOH is still missing, the influence of individual preoperative patient characteristics on IOH remains poorly understood. This systematic review aimed to examine the variability in IOH definitions and to identify preoperative risk factors associated with IOH.
Methods: A systematic literature search was conducted from inception to March 2, 2024. Studies reporting on IOH and from which the association between preoperative characteristics and IOH in cardiac and non-cardiac surgery could be derived were included. Odds ratios (ORs) were either extracted directly or calculated based on available patient-level data. Pooled estimates were generated using a random-effects model.
Results: Out of 7,361 screened studies, 78 met the inclusion criteria. Heterogeneity was high due to varying IOH definitions. 14 preoperative factors were included in the meta-analysis. Older age (OR 1.03, 95% CI 1.02–1.04) and female sex (OR 1.16, 95% CI 1.08–1.24) were associated with increased IOH risk. ASA-II was linked to lower risk compared to ASA-III (OR 0.80, 95% CI 0.70–0.91). Diabetes mellitus (OR 1.18, 95% CI 1.04–1.35) and arterial hypertension (OR 1.56, 95% CI 1.33–1.83) were independent predictors. ACE inhibitor use (angiotensin-converting enzyme inhibitor use; OR 1.63, 95% CI 1.42–1.88), angiotensin receptor blocker (ARB) use (OR 1.38, 95% CI 1.01–1.89), and emergent surgery (OR 1.25, 95% CI 1.09–1.42) also increased IOH incidence. The risk of bias was low to moderate.
Conclusion: The substantial variability in IOH definitions and several preoperative IOH influencing patient characteristics highlight the need for standardized criteria to improve comparability and guide personalized perioperative management.
Systematic Review Registration: identifier PROSPERO CRD42024514229.
Introduction
Intraoperative hypotension (IOH) presents a risk factor for serious postoperative complications, including major adverse cardiovascular events (MACE), stroke, acute kidney injury (AKI), and increased perioperative mortality (1, 2). Evidence indicates that postoperative organ dysfunction is not only associated with the occurrence of hypotension, but is even more strongly linked to its severity and duration, with both brief but profound hypotension as well as prolonged mild hypotension significantly contributing to risk (3).
As IOH is not yet uniformly defined, varying thresholds and durations applied across studies result in inconsistent incidence rates and limited comparability of findings (4). A comprehensive review highlighted the lack of a consensus definition and suggested a classification based on underlying mechanisms such as vasodilation, hypovolemia, or myocardial depression, emphasizing the need for individualized clinical interpretation (5). Other works have stressed the complex and multifactorial pathophysiology of IOH, calling attention to both systemic and patient-specific contributors (6). More recent perspectives have advocated for a symptom-oriented understanding of IOH, shifting the focus from fixed blood pressure thresholds to the broader hemodynamic impact, potentially redefining intraoperative blood pressure management (7).
In this context, emerging data suggest that specific patient-related factors may increase susceptibility to IOH. A retrospective cohort study identified preoperatively assessed functional status, measured using the Fried frailty criteria (8), as an independent predictor of IOH in elderly non-cardiac surgical patients (9). In addition, a systematic review demonstrated that preoperative volume status may also significantly influence the risk of IOH (10). A subgroup analysis pointed toward potentially relevant gender-related susceptibilities, suggesting that elderly female patients might be particularly vulnerable to IOH (11).
Objective
This systematic review aimed to examine the variability in IOH definitions used across studies, as inconsistent definitions may affect the identification and comparability of preoperative risk factors. Furthermore, we aimed to identify preoperative patient-related characteristics that serve as risk factors for the incidence of IOH. We hypothesized that patient-specific factors can be identified before surgery that are consistently associated with an increased risk of IOH.
Methods
Protocol and registration
The protocol for this systematic review was registered in PROSPERO on 01.03.2024 (CRD42024514229) (12). The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (13).
Selection criteria
Prior to the systematic search, inclusion criteria were established through a consensus-based approach using the PICOS framework (Participants, Interventions, Comparisons, Outcomes, and Study Design) (Table 1).
Table 1. PICOS criteria for the inclusion criteria of the systematic literature review.
Studies were excluded if they were not published in English or German language.
All authors collaboratively developed the systematic search strategy. Following its approval, the search was conducted in databases including Embase, MEDLINE (via Ovid) and the Cochrane Library. The detailed search strategy for each database is provided in Supplementary Table S1 in the Supplementary Appendix. The search covered all records available from the inception of each database up to March 2, 2024. Additionally, we manually screened the reference lists of relevant review articles to identify further eligible studies.
Study selection
Two independent and blinded reviewers screened all studies retrieved from the systematic search, assessing titles and abstracts based on the PICOS criteria. A third independent reviewer resolved discrepancies. After title and abstract screening, the same procedure was applied to the full-text assessment.
Data extraction process
The full texts of all included studies were reviewed by one researcher, who extracted all relevant information. A second researcher cross-checked the extracted data for accuracy and consistency. Extracted Information included the PICOS criteria as well as patient and study specific characteristics, and the definition of IOH used. Given the primary objective of this review to examine the variability in IOH definitions, we did not impose a uniform blood pressure threshold. Instead, IOH was extracted as reported in the original study, provided that the authors explicitly defined the event as intraoperative in nature. For meta-analytic pooling, IOH was therefore operationalized as a binary outcome (occurrence vs. no occurrence) based on the study's definition. This approach reflects the real-world heterogeneity of IOH definitions and enables comparison of patientś susceptibility rather than of specific hemodynamic thresholds.
Risk of bias assessment
The risk of bias was assessed using the RoB-2 tool (14) for randomized controlled studies, ROBINS-E tool (15) for prospective studies and the Newcastle-Ottawa Scale (16) for retrospective studies. Two raters independently evaluated each study. In case of discrepancies, a third rater determined the final overall risk of bias.
Statistical analysis
Statistical analysis was performed with MetaAnalysisOnline.com (17). The respective odds ratios (OR) for the incidence of IOH were pooled using a random-effects model, particularly for studies exhibiting high heterogeneity. Whenever available, ORs were extracted directly from the studies. In cases where ORs were missing, they were independently calculated using logistic regression models based on individual patient data, provided sufficient data was available.
Patient characteristics identified in individual studies as influencing the incidence of IOH were included in the meta-analysis, if data were available from at least five independent studies. This criterion was applied to mitigate potential bias and ensure the robustness of the analysis. Subgroup analyses were conducted for studies that exclusively investigated either general anesthesia or spinal anesthesia. Studies that included both anesthetic techniques or focused solely on regional anesthesia were categorized as “Other”. For the age-related meta-analysis, studies with age-restricted populations (e.g., cohorts limited to patients above a predefined age threshold) were excluded to prevent range restriction bias, unless sufficient within-study age variability was reported. To prevent demographic confounding, obstetric studies were excluded from the meta-analyses assessing sex and age, as these populations are uniformly female and younger. Obstetric studies were retained in other analyses, where demographic imbalance does not structurally bias effect estimates.
Inter-study heterogeneity was assessed using the I2 statistic (values > 75% indicating considerable heterogeneity, values <25% suggesting low heterogeneity) and τ2, estimated via the restricted maximum-likelihood method, and p-values derived from Cochran's Q test (18, 19). Potential publication bias was assessed using a funnel plot to visually examine left–right symmetry (20). A 95% confidence interval (95% CI) was applied, and statistical significance was defined as p < 0.05.
Results
Results of the literature search
Of the 7,361 screened studies, 78 met the inclusion criteria and were included in the statistical analysis (Figure 1). The included studies comprised a total of 934,021 patients, of whom one study followed a randomized controlled design, 46 a prospective study design, while 31 studies were retrospective (Table 2). A total of 45 studies investigated patients under general anesthesia, whereas six studies included both general and spinal anesthesia. An additional 21 studies exclusively focused on spinal anesthesia, while two studies examined a combination of general and regional anesthesia, and two studies solely assessed regional anesthesia. A total of 48 studies focused exclusively on elective surgeries, whereas 18 studies analyzed both elective and emergency procedures.
Figure 1. Flowchart of the systematic search.
Table 2. Study characteristics along with the respective definitions of intraoperative hypotension.
Definition of IOH
The definition of IOH varied across studies (Table 2). In 25 studies, IOH was defined based on an absolute threshold for systolic arterial pressure (SAP) or mean arterial pressure (MAP). 14 studies defined IOH as a relative reduction in SAP or MAP compared to baseline values. In 36 studies, a combination of these criteria was used, whereas three studies described IOH as a general decrease in blood pressure.
Patient characteristics
14 preoperative characteristics were identified and included in the analysis. These were then further classified into the following categories: patient-specific characteristics, pre-existing comorbidities, pre-existing medication, and emergency interventions. A meta-analysis was only feasible for the occurrence of IOH. For other outcomes—such as the rate, duration, and severity of IOH—the available data were too scarce and too heterogeneous to allow for meaningful synthesis.
In the patient-specific characteristics, increasing age was associated with a 3% higher risk of IOH (OR 1.03, 95% CI 1.02–1.04, 20 studies; see Figure 2(1A)]. This effect was found to be statistically significant in both the group that considered only general anesthesia (OR 1.03, 95% CI 1.02–1.05, 16 studies). Furthermore, female sex was found to be associated with a 16% increased risk of IOH [OR 1.16, 95% CI 1.08–1.24, 64 studies; see Figure 2[1B]). In the comparison of general anesthesia to spinal anesthesia, female sex was a significant influencing factor in the general anesthesia group (OR 1.14, 95% CI 1.02–1.28, 40 studies) as well as in the spinal anesthesia group (OR 1.52, 95% CI 1.05–2.19, 12 studies).
Figure 2. Meta-analysis of influencing factors regarding the probability of IOH occurrence. Section 1 (blue) presents specific patient characteristics: (1A) age, (1B) sex, (1C) ASA status I vs. II, and (1D) ASA status II vs. III. Section 2 (green) illustrates pre-existing comorbidities: (2A) arterial hypertension and (2B) diabetes mellitus. Section 3 (orange) depicts pre-existing medication: (3A) ACEI and (3B) ARB. Section 4 (red) highlights the impact of emergency surgery. Subgroups were defined as studies that exclusively investigated general anaesthesia, those that focused solely on regional anaesthesia, and studies that included both anaesthesia techniques or purely regional procedures. The latter were categorized under “Other”. ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; ASA, American society of anesthesiologists; IOH, intraoperative hypotension.
The assessment of preoperative health status based on ASA classification demonstrated a stepwise increase in IOH risk with higher ASA classes. Patients with ASA I had a 25% lower risk of IOH compared to patients with ASA II (OR 0.75, 95% CI 0.66–0.85; 34 studies; see Figure 2[1C]). Likewise, patients with ASA II had a 20% lower risk compared to patients with ASA III (OR 0.80, 95% CI 0.70–0.91; 20 studies; see Figure 2[1D]).
With regard to pre-existing comorbidities, patients with a known diagnosis of diabetes mellitus had an 18% higher likelihood of experiencing IOH (OR 1.18, 95% CI 1.04–1.35, 20 studies), whereas a history of hypertension was associated with a 56% increased probability of developing IOH (OR 1.56, 95% CI 1.33–1.83, 33 studies) (see Figures 2[2A/B]. These associations remained significant across all subgroup analyses. In contrast, body mass index (BMI) showed no significant impact on the risk of IOH (OR 1.00, 95% CI 0.99–1.02, 18 studies; see Supplementary Figure S1A).
The analysis of preoperative hemodynamic parameters revealed that SAP, MAP, and diastolic arterial pressure (DAP), as well as heart rate, had no significant influence on the risk of developing IOH (see Supplementary Figure S1). In contrast, the evaluation of preoperative long-term medication use indicated that the intake of ACEI was associated with a 63% increased probability of IOH (OR 1.63, 95% CI 1.42–1.88, 7 studies), whereas the use of ARBs was linked to a 38% increased likelihood of IOH (OR 1.38, 95% CI 1.01–1.89, 8 studies) (see Figure 2[3A,B]). Regarding the likelihood of IOH occurring during emergency surgeries, a significant increase of 25% was observed (OR 1.25, 95% CI 1.09–1.42, 14 studies; see Figure 2[4]).
A comprehensive overview of all results, including the corresponding overall ORs, is presented in Figure 3.
Figure 3. Overview of factors influencing the likelihood of intraoperative hypotension. In panel (a), significant factors are shown in stronger colours, while in panel (b), non-significant factors are displayed in lighter shades, each with their respective odds ratios. (Blue) represents specific patient characteristics, (green) illustrates pre-existing comorbidities, (orange) depicts pre-existing medication, and (red) highlights the impact of emergency surgery. ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; ASA, American society of anesthesiologists; BMI, body mass index; Ca, calcium; CI, confidence Interval; OR, odds rat.
Heterogeneity and risk of bias
Overall heterogeneity was remarkably high, with an I2 > 75%. However, when examining the significant influencing factors ASA status II vs. III and ACEI, heterogeneity was moderate (I2 < 50%) and low (I2 = 0%), respectively (see Figure 2 and Supplementary Figure S1). Regarding publication bias, only a minor distortion of the published data was observed (see Supplementary Figure S2). The risk of bias was assessed as low to moderate in most studies; four prospective studies demonstrated a high risk of bias (see Supplementary Tables S2–S4).
Discussion
Our systematic review confirmed that IOH remains inconsistently defined across the literature, with substantial variability in threshold values and measurement methods. This lack of a uniform definition was consistently reflected in the included studies and represents a central challenge in synthesizing evidence. Accordingly, in our analysis we adopted a definition-inclusive approach, retaining the original IOH definitions used by individual studies. This allowed us to investigate patientś susceptibility to IOH across real-world practice variation. Therefore, our results should be interpreted as reflecting vulnerability to intraoperative hypotensive episodes, rather than referencing a single fixed pressure threshold. Despite this heterogeneity, the meta-analysis identified several patient-related factors that are significantly associated with a higher likelihood of IOH, including increasing age, female sex, higher ASA classification, preexisting hypertension, diabetes mellitus, chronic use of ACEIs or ARBs, and emergency surgical procedures.
Despite its high clinical relevance, IOH remains without a universally accepted definition, which continues to impede both clinical standardization and scientific advancement. The variability in thresholds and diagnostic criteria limits comparability across studies and complicates the development of evidence-based treatment protocols. Notably, even major clinical guidelines reflect this lack of consensus. This inconsistency highlights the urgent need for a harmonized, evidence-based definition of IOH to enable coherent risk stratification, intraoperative decision-making, and outcome evaluation across clinical settings within an individual patient treatment approach (98, 99).
Intraoperative hemodynamics result from a complex interplay of systemic, pharmacological, surgical, and patient-specific factors and should therefore be understood as a multimodal concept. Rather than focusing on isolated variables, it is essential to consider the dynamic interaction of multiple risk components, which may collectively contribute to the onset and severity of IOH.
Several studies have demonstrated that IOH can lead to severe organ dysfunction (1–3, 100). In this context, the identification of individual patient preoperative risk factors may become a crucial first step targeting precision medicine. However, it still remains scarce which preoperative patient characteristics are associated with an increased risk of developing IOH. Dana et al., in their systematic review, investigated the role of preoperative ultrasound in predicting IOH and identified the preoperative inferior vena cava collapsibility index (IVC-CI) as a surrogate for volume responsiveness as a strong predictor of post-induction hypotension (10). However, other metanalysis doubt the usefulness of IVC evaluation at all (101). Importantly, IOH should be regarded not as a disease entity but as a clinical symptom indicative of diverse underlying intraoperative pathophysiological mechanisms (5). This heterogeneity necessitates a structured intraoperative diagnostic pathway to distinguish between different hemodynamic causes, such as vasodilation, hypovolemia, or myocardial depression, which can be conceptualized as distinct endotypes (6). Accurate intraoperative interpretation is thus essential for effective and individualized management. While MAP thresholds provide practical surrogate targets, they do not account for interindividual differences in vascular tone, autoregulatory capacity and pulse pressure propagation. In addition, postoperative complications are more closely related to impaired organ oxygen distribution/consumption relying on both adequate blood flow and arterial pressure according to the law of Ohm. Thus, future perioperative monitoring and clinical practice must incorporate more than only pressure-related targets to improve patientś outcome.
Our findings now contribute to a more comprehensive understanding of IOH susceptibility and support the use of structured preoperative risk stratification to identify vulnerable patients. It will be essential to adopt a patient-specific approach based on individual characteristics to develop and implement tailored therapeutic strategies aimed at preventing IOH more effectively (102). Such an approach enables individualized intraoperative management and may ultimately improve postoperative outcomes.
Chen et al. were among the first to systematically explore patient characteristics in relation to IOH, suggesting that older age, female sex, antihypertensive medication use, and emergency procedures may increase IOH risk (103). However, their conclusions were based solely on descriptive data from 12 included studies, without conducting a meta-analysis. In contrast, our review included 78 studies, as we applied a broader search strategy and were additionally able to incorporate results from studies using patient-level data, thereby enabling, for the first time, a robust meta-analysis within a large and heterogeneous surgical patient cohort. Our findings corroborate the initial hypotheses by Chen et al., confirming significant associations between IOH and the above-mentioned factors.
Bos et al. also examined age and sex as risk factors in their systematic review (11). While they did not find a significant influence of female sex on IOH exposure in the general cohort (OR 1.10, 95% CI 0.98–1.23), a subset analysis of studies with an average age ≥65 years showed increased IOH exposure in females (OR 1.17, 95% CI 1.01–1.35). Similarly, in our analysis, female sex was associated with a 16% higher likelihood of experiencing IOH. Prior studies have emphasized the need to consider sex-specific factors in clinical decision-making (104, 105). It has been demonstrated that, even under the same therapeutic regimen, female sex is an independent risk factor for increased mortality and that different safety cut-offs may be necessary (105). Whether comparable safety cut-offs for IOH are adequate among male and female patients remains unknown and should be investigated in the future. Linked to this, the sex of the anesthesia provider may play a role in addition to the patient's sex: a recent study demonstrated that female anesthesia providers more effectively prevented IOH, intraoperative desaturation, and hyper- or hypocapnia (106).
Our data identified patients with preexisting arterial hypertension and chronic use of Renin-Angiotensin-Aldosterone System (RAAS)–modulating medications (e.g., ACEIs) as particularly vulnerable, with a more than 50% higher probability of IOH. Duceppe et al. reported that in patients undergoing major vascular surgery, long-term antihypertensive therapy was independently associated with increased risk of postoperative AKI (107). On the contrary, others stated that current evidence is insufficient to recommend routine discontinuation of ACEIs/ARBs on the day of surgery but stressed the need for anesthesiologists to remain vigilant for IOH and manage it proactively (108, 109). Discontinuation has also been found to increase the likelihood of clinical significant hypertension in non-cardiac surgery (110). Moreover, it is important to note that the influence of surgical extent on the risk of IOH has not yet been adequately addressed, even in randomized controlled trials (7). While several of these associations have been reported previously, the available evidence has remained fragmented. Importantly, our findings confirm the physiologically expected increased susceptibility to IOH in patients with chronic hypertension, which is likely related to impaired baroreflex sensitivity and altered vascular compliance, and refine the magnitude of this association through pooled effect estimation. The novelty of our analysis lies in aggregating and meta-analytically quantifying these associations across 78 worl-wide studies and more than 930,000 patients. Moreover, by evaluating hypertensive disease and chronic RAAS-modulating medication use separately, our results suggest that these represent related but distinct contributors to IOH risk. Demonstrating that these effects are consistent across diverse anesthesia techniques and surgical specialties strengthens their validity as preoperative risk surrogates and supports their use in a structured, individualized perioperative hemodynamic management.
Limitations
One of the key strengths and primary objectives of our study is its comprehensive inclusion of the wide variability in IOH definitions present in the literature. Though this heterogeneity has already been suggested (4), our systematic review now provides a unique and thorough meta-analytical synthesis that captures the full spectrum of IOH definitions used up to date. While this complexity presents challenges, it also represents an important advance by reflecting real-world variability and enhancing the generalizability of our findings. To account for between-study differences, we applied a random-effects model, yielding more conservative and broadly applicable effect estimates. Importantly, despite the diversity, most studies employed comparable thresholds for absolute or relative blood pressure reductions, supporting the overall interpretability of the results.
Additionally, our analysis included both cardiac and non-cardiac surgery populations. Given the distinct hemodynamic profiles and perioperative management strategies between these groups, this broad inclusion adds another layer of real-world heterogeneity, which in turn might be considered a further strength by capturing a wider clinical spectrum and improving external validity.
A notable limitation of our meta-analysis is the heterogeneity and incomplete reporting of key clinical context variables across studies. In particular, type of surgery, intraoperative medication strategies (e.g., vasopressors, vasodilators, beta-blockers), and patient-specific pathophysiological profiles (e.g., trauma, frailty, myelopathy) were reported inconsistently or aggregated into broad categories, which did not allow for statistically robust subgroup analyses. Therefore, the associations identified in this review should be interpreted as reflecting general patientś susceptibility to IOH rather than interactions between patient characteristics and specific surgical or pharmacologic management strategies, especially in the context of underlying cardiovascular comorbidity. Moreover, considerable variability in study inclusion criteria and frequent underreporting of clinically relevant subgroups (e.g., patients with heart failure or atrial fibrillation) may limit the generalizability of our findings and introduce selection bias.
Beyond commonly assessed factors like age, sex, and comorbidities, functional status has been identified in previous research as a significant predictor of IOH. Specifically, preoperative frailty or functional impairment independently increases IOH risk, even after adjusting for age and ASA classification (9). Unfortunately, due to inconsistent reporting, this important parameter could not be included in our quantitative synthesis. Similarly, certain high-risk populations remain underrepresented in current literature. Future investigations, such as the ongoing PeriopCAreHF trial, are expected to address these gaps, thereby refining patient stratification and perioperative management strategies (111).
Due to considerable heterogeneity and insufficient reporting of IOH episode duration and severity across studies, we were unable to incorporate these important parameters within a time-weighted area under the curve approach into our analysis and were therefore restricted to only a binary consideration of IOH occurrence. Yet, existing studies suggest that the duration and depth of IOH episodes play a pivotal role in the development of organ dysfunction (3). Bijker et al. demonstrated that the more severe the hypotension, the shorter the threshold duration for a significant increase in mortality (2). Although heterogeneity was primarily driven by differences in IOH definitions, additional variability in effect estimates due to studies with mixed or regional anesthesia approaches (categorized as “Other” in the Methods section) cannot be excluded. Finally, the hemodynamic influence of neuraxial techniques such as thoracic epidural anesthesia (TEA) could not be analyzed separately due to limited subgroup data; future studies should therefore evaluate TEA and combined general–epidural approaches as distinct anesthetic strategies with potentially unique IOH risk profiles.
As the evidence base expands, meta-regression techniques could help systematically explore potential effect modifiers. Further research is also needed to investigate whether the patient-related risk factors identified in our analysis not only influence the incidence but also the duration and severity of IOH. Incorporating these aspects could enhance perioperative risk stratification and support more targeted hemodynamic management strategies.
Conclusion
Our analysis underscores the considerable variability in definitions of IOH across studies, which complicates comparisons and the interpretation of findings. Establishing standardized IOH definitions in the future is crucial to enable more consistent research and improve clinical decision-making. Despite this variability, we identified a significant impact of patient characteristics, such as age, sex, comorbidities, and chronic medication use, on the incidence of IOH. However, further research is needed to explore how these factors may also influence the duration and severity of IOH episodes. To guide future clinical implementation and research, a standardized and physiologically informed definition of IOH are needed that allow distinguishing different mechanisms of intraoperative hypotensive episodes.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Author contributions
ND: Writing – original draft, Formal analysis, Visualization, Data curation, Resources, Project administration, Validation, Investigation, Software, Methodology, Supervision, Writing – review & editing, Funding acquisition, Conceptualization. DB: Data curation, Resources, Validation, Project administration, Conceptualization, Visualization, Methodology, Formal analysis, Writing – review & editing, Supervision, Investigation, Funding acquisition, Software, Writing – original draft. MT: Methodology, Investigation, Writing – original draft. JF: Data curation, Methodology, Writing – review & editing, Investigation. DW: Writing – review & editing, Investigation, Writing – original draft, Data curation, Software. CS: Methodology, Supervision, Conceptualization, Writing – review & editing, Project administration, Funding acquisition. FB: Conceptualization, Supervision, Methodology, Writing – review & editing, Formal analysis. RM: Investigation, Resources, Writing – review & editing, Formal analysis. OH: Project administration, Methodology, Supervision, Writing – review & editing, Conceptualization. AM: Conceptualization, Funding acquisition, Supervision, Writing – review & editing, Project administration. DC: Methodology, Data curation, Investigation, Writing – review & editing. AP: Validation, Methodology, Investigation, Software, Writing – review & editing. AB: Investigation, Software, Resources, Writing – review & editing, Methodology. MK: Methodology, Writing – review & editing, Formal analysis, Investigation. ST: Conceptualization, Supervision, Formal analysis, Writing – review & editing, Investigation. MM: Writing – review & editing, Methodology, Formal analysis, Validation, Project administration, Data curation, Supervision, Investigation, Writing – original draft, Conceptualization, Software, Funding acquisition, Visualization, Resources.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
ST reports honoraria for lectures and workshops by Orion Pharma, Edwards Lifesciences, AOP Health, Cytosorbents, Chiesi, and Philips as well as research funding or grants by the German ministry on Research, Technology and Space, the German ministry for Economic Affairs and Energy, the German Science Foundation, Queen Mary Hospital, Orion Pharma, Becton Dickinson, Cytosorbents, the B. Braun Foundation, and Charité; all outside the presented work. CS received grants or contracts and non-financial support from German Research Society, German Aerospace Center, Einstein Foundation Berlin, Federal Joint Committee (G-BA), Inner University Grants, Project Management Agency, Non-Profit Society Promoting Science and Education, European Society Of Anaesthesiology and Intensive Care, BMWI—Federal Ministry for Economic Affairs and Climate Action, Georg Thieme Verlag, Dr. F. Köhler Chemie GmbH, Sintetica GmbH, MaxPlanck-Gesellschaft zur Förderung der Wissenschaften e.V., Stifterverband für die deutsche Wissenschaft e.V., Metronic, Philips Electronics Nederland BV, BMBF (Federal Ministry of Education and Research, RKI, The European Commission Horizont Europa, Prothor, Takeda Pharmaceutical Company Limited, Lynx Health Science GmbH, Association of the Scientific Medical Societies in Germany, German Research Foundation, German National Academy of Sciences—Leopoldina, Berliner Medizinische Gesellschaft, European Society of Intensive Care Medicine, European Society of Anaesthesiology and Intensive Care, German Society of Anaesthesiology and Intensive Care Medicine, German Interdisciplinary Association for Intensive Care and Emergency Medicine, German Sepsis Foundation and holds various international patents; these holdings have not affected any decisions regarding his research or this study.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcvm.2025.1709004/full#supplementary-material
Supplementary File 1 | Visual abstract. Created in BioRender. Markus, M. (2025), https://BioRender.com/a6gg90v.
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Keywords: intraoperative hypotension, preoperative risk factors, patient characteristics, perioperative management, cardiovascular risk, meta-analysis
Citation: Daum N, Bill D, Thiele M, Felber J, von Wedel D, Spies C, Balzer F, Mörgeli R, Hunsicker O, Müller A, Contag D, Pohrt A, Bald A, Kayser M, Treskatsch S and Markus M (2025) Preoperative patient risk factors for intraoperative hypotension: a systematic review and meta-analysis. Front. Cardiovasc. Med. 12:1709004. doi: 10.3389/fcvm.2025.1709004
Received: 19 September 2025; Revised: 15 November 2025;
Accepted: 20 November 2025;
Published: 5 December 2025.
Edited by:
Hong Liu, UC Davis Health, United StatesReviewed by:
Christian Bohringer, UC Davis Medical Center, United StatesCristina Barboi, Indiana University Hospital, United States
Copyright: © 2025 Daum, Bill, Thiele, Felber, von Wedel, Spies, Balzer, Mörgeli, Hunsicker, Müller, Contag, Pohrt, Bald, Kayser, Treskatsch and Markus. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Maximilian Markus, bWF4aW1pbGlhbi5tYXJrdXNAY2hhcml0ZS5kZQ==