Next Article in Journal
AI as a Procedural Equalizer: Performance Comparison in Programming-Based Engineering Coursework Following the Emergence of Generative AI
Previous Article in Journal
The Bridge Between Artificial Intelligence and Predictive Maintenance in Industry 4.0: A Systematic Review
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 16
Issue 10
10.3390/app16104883
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Fever Burden After Liver Surgery: From Infection Diagnostics to Phenotyping of the Immunometabolic Response

by
Barbara Pietrzyk
,
Paulina Majdak
,
Wiktor Pierzchała
,
Maksymilian Janeczek
and
Jedrzej Mikolajczyk
*
Department of Medical Biophysics, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-055 Katowice, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(10), 4883; https://doi.org/10.3390/app16104883
Submission received: 8 April 2026 / Revised: 8 May 2026 / Accepted: 12 May 2026 / Published: 14 May 2026
Browse Figures
Versions Notes

Abstract

The concept of “fever burden” represents a quantitative and dynamic expression of the host immunometabolic response, integrating the duration, intensity, and temporal characteristics of postoperative temperature alterations. This review discusses the biological rationale underlying postoperative fever and explores its potential clinical relevance in the context of liver surgery, particularly in distinguishing infectious complications from sterile postoperative inflammation. This narrative review was based on a structured literature search of PubMed and Embase (2000–2025) to identify clinical and translational studies addressing postoperative fever after hepatic resection and liver transplantation. The retrieved literature was narratively synthesized with emphasis on fever burden, temperature trajectories, and biologically plausible mechanisms potentially associated with postoperative recovery and infectious complications. Current evidence suggests that postoperative fever may reflect dynamic activation of innate immune and inflammatory pathways rather than representing a purely binary sign of infection. In liver surgery, clinically relevant information may be better captured by temporal fever characteristics, including timing of fever onset, peak temperature, and recurrent febrile episodes, than by isolated temperature measurements alone. However, direct liver-surgery-specific evidence remains limited, and broader concepts related to temperature trajectories and immunometabolic phenotyping should currently be regarded as hypothesis-generating. Fever burden and temperature trajectory analysis may therefore represent promising conceptual approaches for interpreting postoperative host-response patterns after liver surgery, although their diagnostic and prognostic value requires prospective validation in liver-specific clinical cohorts.

1. Introduction

Fever is an evolutionarily conserved defense response to infection and other disruptions of homeostasis, constituting a component of the innate immune response. Its development results from coordinated inflammatory and neuroendocrine signaling, leading to a shift in the hypothalamic thermoregulatory set point and the activation of organized physiological responses. In recent years, it has become increasingly well documented that the thermal component of the febrile response can modulate both innate and adaptive immune function, conferring upon temperature not only a symptomatic but also a regulatory role [1].
In the early postoperative period following liver surgery, fever is a common but clinically nonspecific finding. Although traditionally regarded as a marker of infection, accumulating evidence indicates that it often reflects a sterile inflammatory response related to surgical injury, parenchymal regeneration, and ischemia–reperfusion stress rather than infection per se. In a study involving patients undergoing liver resection, characteristics of the fever course—later fever onset, higher peak temperatures, and recurrent febrile episodes—were shown to be more informative for predicting infectious complications than the mere presence of postoperative fever [2].
In this context, a single temperature measurement proves insufficient as an assessment tool. Increasing attention has been directed toward the concept of fever burden, which encompasses not only peak temperature but also the duration of hyperthermia, the dynamics of its rise, the recurrence of febrile episodes, and the response to interventions.
Such an approach may more accurately reflect the complexity of the postoperative biological response and may better correlate with the risk of complications and postoperative recovery trajectories. Importantly, approaches based on the analysis of temperature over time (temperature trajectories) have demonstrated in other inflammatory conditions that the “shape of the curve” reveals clinically meaningful subphenotypes with distinct risk profiles and underlying physiology, providing a strong rationale for extending this framework to liver surgery [3]. At the biological level, fever results from activation of the innate immune response by infectious and sterile stimuli, leading to the release of proinflammatory cytokines and the synthesis of prostaglandin E2, which resets the thermoregulatory set point. This is accompanied by coordinated effector responses, while resolution involves activation of anti-inflammatory pathways. In the context of the liver, it is crucial that signaling mediated by interleukin-6 (IL-6) and its co-receptor glycoprotein 130 (gp130) leads to activation of the transcription factor STAT3 (signal transducer and activator of transcription 3), a key component of hepatocyte-protective and regenerative programs [4]. From a clinical perspective, it is particularly important that surgical injury can simultaneously trigger a robust inflammatory response and induce a transient reprogramming of immune function. In a complementary translational liver-surgery study, Chopra et al. compared postoperative immune responses after laparoscopic versus open liver resection by measuring monocyte HLA-DR expression and ex vivo-stimulated secretion of proinflammatory cytokines (TNF-α, IL-6, IFN-γ). The study found that laparoscopic resection, associated with less tissue trauma, preserved higher monocyte HLA-DR expression postoperatively, whereas open surgery was accompanied by a marked decrease in HLA-DR expression in the early postoperative period, consistent with greater postoperative immunosuppression following more extensive surgical injury [5]. Despite growing recognition of the complexity of the febrile response, postoperative practice still often relies on arbitrary temperature thresholds and static criteria, promoting overdiagnosis of infection and unnecessary antibiotic use without clear improvement in clinical outcomes.
In the era of precision medicine, increasing emphasis is placed on identifying measurable host-response phenotypes that integrate immunological and metabolic signals. In this context, fever may represent an accessible and low-cost biomarker of the immunometabolic axis when analyzed dynamically as burden and trajectory.
For fever burden and trajectories to be clinically actionable, high temporal resolution data, ideally from continuous temperature monitoring, are required. Measurement frequency significantly influences the detection of postoperative fever, and intermittent assessments may miss a substantial proportion of episodes [6]. Recent postoperative studies suggest that wireless continuous axillary temperature monitoring is feasible and demonstrates acceptable agreement with core temperature measurements after major surgery [7]. Non-invasive systems based on smart patches enabling frequent temperature measurements increase the detection of clinically relevant febrile episodes compared with traditional, intermittent infrared thermometer measurements, enhancing their potential as monitoring tools [8].
Coherent conceptual frameworks for interpreting postoperative fever remain lacking, with fever still primarily viewed as a sign requiring exclusion of infection rather than an adaptive signal reflecting the balance between inflammation and regeneration and the risk of complications. This is particularly relevant in liver surgery, where postoperative responses may mimic infection and lead to inappropriate clinical decision-making.
This review examines fever burden after liver surgery as a potential framework for interpreting postoperative host-response patterns, with particular emphasis on distinguishing direct evidence from hepatic surgery, mechanistic immunobiological data, and extrapolation derived from non-hepatic clinical settings.

2. Literature Search and Narrative Synthesis

This article was designed as a narrative review supported by a structured literature search strategy intended to enhance the transparency of literature identification and study selection. The review aimed to synthesize clinical and translational evidence concerning postoperative fever and fever burden following liver surgery, including hepatic resection and liver transplantation.
A narrative review approach was selected because the available evidence is heterogeneous and encompasses observational surgical studies, translational immunology research, and mechanistic data derived from both hepatic and non-hepatic clinical settings. Given this heterogeneity, a narrative synthesis was considered more appropriate than a formal systematic review or meta-analysis. The structured literature search was performed to ensure methodological transparency and to provide a reproducible framework for identifying relevant studies.
Studies were selected based on their relevance to postoperative temperature dynamics, fever burden, inflammatory host-response mechanisms, and infectious complications after liver surgery. The process of literature identification and selection is summarized in a flow diagram (Figure 1). The manuscript was prepared in accordance with the SANRA (Scale for the Assessment of Narrative Review Articles) principles for high-quality narrative reviews.

2.1. Scope of the Review and Study Selection Criteria

Study selection criteria were defined to structure the scope of this narrative review and to identify literature relevant to postoperative fever, fever burden, and temperature-pattern interpretation after liver surgery. The review focused on adult patients undergoing liver surgery, including hepatic resection and liver transplantation, in the early postoperative period.
Studies were considered relevant when they addressed postoperative fever, fever burden, fever duration, peak temperature, timing of fever onset, recurrent febrile episodes, temperature trajectories, or postoperative temperature monitoring. Publications discussing inflammatory, immunological, or metabolic mechanisms potentially related to postoperative fever were also considered when they contributed to the biological interpretation of fever as a host-response signal.
The main clinical outcome of interest was the association between postoperative fever characteristics and infectious complications after liver surgery. Additional clinically relevant outcomes were considered only when reported in the included studies, including postoperative morbidity, graft dysfunction after liver transplantation, mortality, antibiotic use, inflammatory markers, or indicators of postoperative recovery.
Because the available evidence was heterogeneous and limited, eligible publications included prospective and retrospective observational studies, comparative clinical studies, and relevant translational or mechanistic studies. Systematic reviews and guidelines were used only for contextual background and were not re-analyzed as primary evidence.
Studies were excluded if they involved pediatric populations, non-hepatic surgical procedures, non-surgical fever syndromes, case reports, conference abstracts, editorials, non-research publications, or studies without postoperative temperature data or fever-related outcomes. Preclinical studies were not used as direct clinical evidence but could be cited only to support mechanistic plausibility where appropriate.

2.2. Information Sources and Search Strategy

A structured literature search of PubMed and Embase was performed to identify publications relevant to postoperative fever and fever burden after liver surgery. The search included articles published between January 2000 and December 2025. Search terms combined controlled vocabulary and free-text terms related to liver surgery (“hepatectomy”, “liver resection”, “liver transplantation”), postoperative fever (“fever”, “hyperthermia”, “temperature”), and dynamic or quantitative temperature assessment (“fever burden”, “temperature trajectory”, “area under the curve”, “cumulative fever”).
Only peer-reviewed articles published in English were considered. In addition, reference lists of selected publications and relevant review articles were screened manually to identify further studies of potential relevance. The search strategy was intended to support transparent identification of clinically and conceptually relevant literature rather than to provide a fully systematic evidence synthesis.

2.3. Study Selection

The process of literature identification and study selection is summarized in a flow diagram (Figure 1). The structured literature search identified 117 records (PubMed, n = 57; Embase, n = 60). After removal of duplicate records and initial screening, full-text articles were assessed for their relevance to postoperative fever patterns, fever burden, temperature dynamics, and postoperative complications after liver surgery.
Following eligibility assessment, nine studies were considered sufficiently relevant to be included in the final narrative synthesis. Studies were included when they provided clinically or conceptually relevant information regarding postoperative fever after hepatic resection or liver transplantation. Publications were excluded if they focused on non-hepatic surgery, lacked postoperative temperature data or fever-related outcomes, involved very small study populations, or did not contribute directly to the clinical or mechanistic interpretation of postoperative fever after liver surgery (Figure 1).
To enhance the transparency of the narrative synthesis, Table 1 summarizes the principal studies informing this review according to study design, clinical setting, and evidentiary relevance to the concept of fever burden after liver surgery (Table 1).
Principal studies informing this narrative synthesis are summarized by clinical setting, study design, assessment method, and evidentiary relevance. The evidence is categorized as direct liver-surgery clinical or mechanistic evidence, liver-specific mechanistic evidence, non-hepatic postoperative monitoring evidence, supportive mechanistic immunology evidence, or hypothesis-generating extrapolation from critical care (Table 1).
This categorization was used to distinguish study-level evidence directly derived from liver-surgery populations from mechanistic or non-hepatic evidence used only to support biological plausibility or generate hypotheses.

2.4. Literature Synthesis

The included publications were analyzed with regard to postoperative fever characteristics after liver surgery, methods of temperature assessment, and reported associations between postoperative fever patterns and clinical outcomes. Particular attention was given to temporal characteristics of postoperative fever, including timing of onset, peak temperature, recurrent febrile episodes, and dynamic temperature patterns described in the included studies.
Findings were synthesized narratively with emphasis on clinically relevant observations, mechanistic interpretation, and distinctions between direct liver-surgery evidence and hypothesis-generating extrapolation from non-hepatic clinical settings.

2.5. Critical Appraisal of the Literature

Given the heterogeneity of the included literature, no formal risk-of-bias assessment was performed. Instead, studies were critically evaluated with regard to the clarity of postoperative fever assessment, methodological limitations, outcome reporting, and relevance to liver-surgery-specific clinical interpretation.
Particular caution was applied when interpreting findings derived primarily from mechanistic studies or extrapolation from non-hepatic clinical populations.

3. Results

3.1. Fever as a Dynamic Immunometabolic Phenotype of Innate Immunity

Contemporary approaches advocate moving beyond a binary interpretation of fever towards its quantitative and dynamic assessment as a biomarker of the immunometabolic response [11]. Fever may represent a measurable phenotypic signal: it is objectively quantifiable, evolves over time, reflects the current biological state of the host, and integrates multiple concurrent biological processes rather than a single underlying cause. Fever is not merely a passive consequence of disease but a tightly regulated biological response integrating inflammatory, neuro-endocrine, and metabolic signaling pathways [12].
Elevation of body temperature modulates innate and adaptive immune responses by enhancing leukocyte activity, promoting cytokine signaling, and limiting pathogen proliferation, thereby supporting fever as an active host defense mechanism during infection and tissue injury [13]. Emerging evidence indicates that fever constitutes a functional component of the immunometabolic axis, modulating energy allocation and cellular resources towards host defense. The febrile response critically involves innate immune cells (including macrophages, neutrophils, dendritic cells, and natural killer cells), whose function is dynamically modulated by increasing body temperature [14]. Fever induces the expression of heat shock proteins, including heat shock protein 70 (HSP70), which modulate cytokine secretion—such as interleukin-1β (IL-1β) and interleukin-10 (IL-10)—in macrophages, thereby shaping their proinflammatory profile and potentially influencing their tissue distribution and antigen-presenting capacity, ultimately supporting the coordination of adaptive immune responses [15].
Such activation of innate immunity at the effector level involves not only enhanced pathogen clearance but also metabolic reprogramming of immune cells towards increased reactivity and functional efficiency [16].
Increasingly, fever is being conceptualized as a measurable phenotype of innate immune activation that reflects the extent of immunometabolic reprogramming of effector cells rather than a nonspecific manifestation of inflammation. In this framework, fever integrates immunological, neuroendocrine, and metabolic signals and manifests as characteristic temporal patterns of temperature change [17].
In liver surgery, postoperative fever may accompany sterile innate immune activation associated with tissue injury and ischemia–reperfusion stress. Clinical observations after liver resection suggest that fever dynamics, including timing, peak temperature, and recurrence, may help identify patients at increased risk of infectious complications [2]. At the mechanistic level, this response may involve Kupffer cells and recruited macrophages, whose activation and polarization participate in inflammatory regulation and regenerative processes [18]. Accordingly, postoperative fever may resemble infection clinically, while also reflecting sterile inflammatory and reparative host-response pathways.
As noted, the dynamics of temperature change, rather than isolated temperature measurements, may more accurately reflect the sequence of biological events following surgery, ranging from early inflammatory activation and metabolic reprogramming of immune cells to the initiation of tissue repair and regeneration. Within this framework, fever burden may be interpreted as a quantitative representation of the intensity of the host response and its associated immunometabolic demand, potentially providing a more informative characterization of the postoperative biological state than isolated temperature measurements alone (Figure 2).
Fever burden integrates both the intensity and temporal persistence of postoperative hyperthermia, potentially reflecting the transition from a predominantly proinflammatory, M1-biased macrophage response toward a more regulatory and pro-regenerative M2-like profile. In this context, fever burden may be interpreted as a potential indicator of the dynamic balance between inflammation and regeneration after liver surgery. Evidence derived from experimental models and observational studies suggests that temperatures within the fever range may modulate macrophage polarization, attenuating certain M1-associated inflammatory pathways while promoting M2-like phenotypes, including M2b phenotypes implicated in inflammation resolution and tissue repair [10].
In the context of liver ischemia–reperfusion injury, where the timing of macrophage reprogramming may influence postoperative recovery, temperature trajectories may therefore be associated with shifts in the immunological balance between tissue injury and regenerative responses. These processes are linked to immunometabolic reprogramming, in which cellular energy metabolism and cytokine signalling pathways are closely interconnected and contribute to macrophage functional plasticity during inflammatory and tissue-repair responses [19].
This perspective supports interpreting postoperative temperature patterns not merely as isolated clinical findings, but as dynamic biological signals potentially reflecting interactions between inflammatory activation, metabolic adaptation, and regenerative processes. Within this framework, temperature dynamics may contribute to distinguishing adaptive sterile inflammatory responses from patterns potentially requiring further diagnostic evaluation.

3.2. Temperature as a Regulator of Signaling Pathways and Effector Functions

Temperature may act as a biological regulator of neutrophil and macrophage migration, polarization, and effector activity, thereby influencing innate immune responses and inflammatory tissue regulation. Elevated body temperature has been shown to modulate neutrophil effector functions, including migratory activity and mechanisms involved in pathogen containment [20]. Under febrile conditions, neutrophils may exhibit enhanced migratory capacity together with increased production of reactive oxygen species and myeloperoxidase, promoting the formation of neutrophil extracellular traps (NETs), which contribute to pathogen immobilization and containment. At very high temperatures (above 42 °C), however, neutrophil adhesion becomes unstable, leading to impaired cellular attachment and suggesting the existence of a relatively narrow temperature range associated with potentially protective immunological effects [20].
Fever may additionally influence chemokine signalling pathways involved in neutrophil recruitment to inflammatory sites. Toll-like receptors (TLRs), expressed among others on dendritic cells, recognize molecular patterns associated with infection or tissue injury. Activation of TLR7 signalling pathways may induce production of the chemokine CXCL16, which functions as a chemoattractant signal for neutrophils expressing the CXCR6 receptor, thereby facilitating recruitment of inflammatory cells to affected tissues [21,22]. Experimental inflammatory models suggest that activation of the TLR7–MyD88–CXCL16 signalling axis may contribute to neutrophil migration and proinflammatory activity and could potentially participate in sterile inflammatory responses associated with postoperative fever [22].
Fever may also affect macrophage function, modulating their migration, phagocytosis, and cytokine secretion profile. Fever promotes the recruitment of macrophages from the bone marrow to inflamed tissues and dynamically influences their phenotypic polarization. Depending on the biological context, macrophages may adopt a proinflammatory (M1-like), anti-inflammatory (M2-like), or mixed (M2b) phenotype, secreting mediators such as tumor necrosis factor-alpha (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), cyclooxygenase-2 (COX-2), or interleukin-10 (IL-10). Evidence suggests that fever and moderate hyperthermia favor a shift toward M2 and M2b phenotypes, which is associated with reduced production of reactive oxygen species and nitric oxide, as well as protection against excessive inflammatory tissue damage [23].
Fever may selectively modulate macrophage phagocytic functions—enhancing pathogen clearance while limiting the efferocytosis of apoptotic cells by proinflammatory macrophages, likely due to reduced cell–cell interactions under elevated temperature conditions. These mechanisms underscore the functional plasticity of macrophages and indicate that fever does not act unidirectionally but rather fine-tunes the immune response to the prevailing inflammatory context. These observations underscore the functional plasticity of macrophages and suggest that fever may modulate immune responses in a context-dependent manner rather than acting through a single unidirectional mechanism.
Following hepatectomy and liver transplantation, hepatic macrophages (including Kupffer cells and monocyte-derived macrophages) undergo dynamic polarization, with a shift toward anti-inflammatory M2 phenotypes characterized by the expression of interleukin-10 (IL-10), arginase-1 (Arg-1), and the CD163 receptor. This transition promotes the resolution of inflammation, limits oxidative stress, and supports liver parenchymal regeneration after ischemia–reperfusion injury [9].
Temperature dynamics may therefore be associated with patterns of macrophage polarization and may potentially reflect shifts between proinflammatory activation and pathways involved in inflammation resolution and tissue repair (Table 2).
Table 2 presents a conceptual framework intended to illustrate potential relationships between postoperative fever patterns, macrophage polarization states, and host-response dynamics after liver surgery. This framework should not be interpreted as a clinically validated classification system. An early and transient proinflammatory phase, associated with activation of interleukin-1β (IL-1β), interleukin-6 (IL-6), and cyclooxygenase-2 (COX-2), may contribute to tissue repair and regenerative processes. Conversely, persistent hyperthermia or excessive pharmacological suppression of fever may interfere with the physiological transition from proinflammatory macrophage activation toward regenerative and inflammation-resolving phenotypes. Within this context, postoperative temperature patterns may reflect dynamic interactions between tissue injury, ischemia–reperfusion stress, inflammatory regulation, and the metabolic demands of liver regeneration.

3.3. Clinical Significance of Fever and Fever Burden

In the postoperative setting, fever may represent more than a nonspecific manifestation of inflammation and could reflect a measurable component of the postoperative host-response pattern. The temporal characteristics of postoperative temperature elevation—including duration, intensity, and trajectory—may provide insight into the complex interplay between inflammatory activation, tissue injury, regenerative signaling, and metabolic adaptation after liver surgery. Within this context, quantitative assessment of fever burden may offer a more integrative interpretation of postoperative biological responses than isolated temperature measurements alone [24].
Despite this, postoperative fever is still frequently interpreted in binary terms (present versus absent), although its clinical significance after liver resection or liver transplantation appears to depend substantially on temporal dynamics and postoperative context. Available clinical observations suggest that the diagnostic relevance of postoperative fever may lie less in the presence of fever itself than in the temporal characteristics of temperature change over time. In patients undergoing liver resection, delayed fever onset after postoperative day 2 together with higher peak temperatures has been associated with increased risk of infectious complications [2]. From a physiological perspective, fever burden may be viewed as a dynamic representation of the postoperative host response, integrating cumulative thermal exposure, duration of temperature elevation, temporal progression of fever, and response to therapeutic interventions. Such an approach may allow a more integrated interpretation of postoperative hyperthermia by reflecting processes related to inflammatory activation, metabolic adaptation, and redistribution of energetic resources during postoperative recovery [25].
Recent studies have increasingly emphasized the potential relevance of temperature trajectory analysis for identifying distinct inflammatory and host-response patterns. In critical care and sepsis populations, clustering patients according to early temperature trajectories has revealed biologically and clinically distinct subgroups associated with different risk profiles and outcomes [26]. Although most currently available evidence derives from non-hepatic clinical settings, these observations provide a biologically plausible rationale for considering trajectory-based approaches in liver surgery, where postoperative temperature patterns may reflect differing contributions of sterile tissue injury, regenerative processes, and infectious complications rather than the mere presence or absence of fever.
This perspective is consistent with broader developments in data-driven and precision medicine, in which longitudinal analysis of routinely collected physiological parameters is increasingly used to characterize dynamic patient-specific response patterns over time [27].
In postoperative practice, fever frequently prompts extensive diagnostic investigation and empirical antimicrobial therapy. However, contemporary perioperative and critical care approaches increasingly emphasize structured clinical assessment and avoidance of unnecessary treatment escalation in the absence of objective findings that support infection [28].
In transplantation and abdominal surgery, antimicrobial stewardship is emphasized, particularly in high-risk patients, where inappropriate diagnosis of infection may contribute to antimicrobial resistance and treatment-related complications [29].
Fever burden may contribute to structuring clinical decision-making by helping to identify patients in whom postoperative fever patterns remain within the expected range of sterile inflammatory responses while also highlighting patterns that potentially require further diagnostic evaluation, including delayed fever onset, elevated peak temperatures, or recurrent febrile episodes. In this context, postoperative temperature patterns may be interpreted not merely as isolated symptoms, but as dynamic physiological signals requiring longitudinal clinical assessment over time.
In liver surgery, the concept of fever burden appears particularly relevant because of the complex interplay between inflammatory activation, ischemia–reperfusion stress, and regenerative processes within the hepatic parenchyma. Cytokine signaling involving the interleukin-6 (IL-6)/gp130–STAT3 axis has a well-established role in both acute-phase inflammatory responses and hepatocyte proliferation during liver regeneration, with IL-6-mediated STAT3 activation contributing to regenerative signaling pathways in hepatic tissue [30].
At the same time, exposure to fever-range temperatures can modulate innate immune cell function, enhance macrophage responsiveness and influence inflammatory activation pathways involved in host defense and tissue injury responses [31].
Fever is increasingly understood not merely as a secondary manifestation of inflammation, but as an integrated physiological response closely linked to the regulation of inflammatory and immunometabolic pathways. Available evidence suggests that transient postoperative hyperthermia may accompany coordinated inflammatory and regenerative processes, whereas persistent or disproportionate temperature elevation may be associated with dysregulated innate immune activation and a greater likelihood of postoperative complications [32]. From this perspective, the concept of fever burden underscores the limitations of isolated temperature measurements and supports consideration of postoperative temperature as a dynamic physiological variable requiring longitudinal interpretation. Advances in continuous temperature-monitoring technologies, including wearable and skin-mounted sensor systems, have enabled acquisition of high-temporal-resolution physiological data capable of detecting subtle temperature fluctuations that may remain unrecognized with conventional intermittent assessment strategies [33]. Wearable monitoring platforms, including systems such as Verily Patch [34] and smart sensor technologies such as SteadyTemp® [8], have been investigated in postoperative settings as non-invasive approaches for continuous temperature assessment. Beyond their technical role in fever detection, such monitoring systems may also support a more physiologically informed interpretation of fever, which is increasingly recognized as an active host-defense response rather than merely a passive symptom of infection [35]. These technologies may improve characterization of postoperative temperature dynamics and facilitate identification of evolving febrile patterns over time.
Integration of continuous temperature monitoring with longitudinal trajectory analysis may provide a more comprehensive assessment of postoperative host-response patterns, particularly when interpreted alongside clinical and laboratory parameters. In this context, dynamic temperature analysis may contribute to recognition of postoperative trajectories potentially associated with regenerative recovery, persistent inflammatory activation, or early deviation from the expected postoperative course.

4. Discussion

Early postoperative fever after liver surgery is a nonspecific signal that may reflect either a physiological sterile response or early infectious complications. The issue lies not in fever itself but in its interpretation based on single temperature measurements, which may lead to both unnecessary treatment escalation and delayed recognition of complications [2]. At present, broader interpretations of fever burden and temperature trajectories in liver surgery should be regarded as hypothesis-generating, as direct liver-surgery-specific evidence remains limited. In this setting, fever burden may represent a more informative interpretative framework for postoperative host-response assessment than binary evaluation of fever presence alone. After liver resection, available clinical observations suggest that temporal characteristics of postoperative fever, including timing, magnitude, and recurrence of febrile episodes, may help identify patients at increased risk of infectious complications more effectively than fever presence alone [2]. Accordingly, a further step is to move beyond static measures of fever burden toward the analysis of temperature trajectories, that is, the identification of temporal patterns such as rapid rise and resolution, gradual increase with persistence, or fluctuating profiles with intermittent temperature elevations. Studies in sepsis indicate that clustering patients based on early temperature trajectories reveals distinct subphenotypes with different risk profiles and underlying physiological characteristics, rather than simply different levels of fever [36]. Although sepsis is not a directly comparable model to hepatectomy or liver transplantation, a similar principle applies: the shape of temperature trajectories carries relevant biological and clinical information. This provides a biologically plausible rationale for exploring trajectory-based interpretation of postoperative fever in liver surgery. A similar trajectory-based approach to fever has also been demonstrated in postoperative populations, where modelling of temperature patterns allowed for improved stratification of infectious risk compared with assessments based on single thresholds [37]. Potential temperature-based phenotyping is of particular importance in liver physiology, particularly because cytokines (especially interleukin-6) and signaling involving the transcription factor STAT3 (signal transducer and activator of transcription 3) belong to key regenerative mechanisms while at the same time constituting elements of the broader inflammatory and metabolic response. Studies suggest that a similar temperature “peak” may indicate different processes in different patients: in some, a predominance of a regenerative-regulatory program; in others, a persistent dysregulation of the innate immune response [32]. Given the above, in clinical practice this implies that temperature may serve as a non-invasive physical integrator of immunological and metabolic signals that are difficult to measure in real time in the ward setting. However, for fever trajectories and burden to be assessed clinically, high temporal resolution data are required, namely continuous temperature monitoring. It has been shown that the schedule and frequency of measurements significantly affect the detection of fever, whereas intermittent measurements may miss a substantial proportion of febrile episodes [38]. Available postoperative validation studies suggest that continuous wireless temperature monitoring is feasible and may provide clinically relevant high-temporal-resolution temperature data. These previously mentioned technologies, including smart patches and wearable devices, increase the detection of fever episodes, reduce errors associated with sporadic measurements, and enable quantitative assessment of fever burden, as confirmed by reviews on the early detection of postoperative complications [39,40]. An example of such a solution is the SteadyTemp® system, validated as a non-invasive method for continuous axillary temperature measurement; its authors emphasize that an approach based solely on a single fever threshold may be insufficient and should be replaced by an assessment of individual temperature changes over time [8]. Quantitative assessment of fever burden may additionally constitute a component of prognostic models integrated with laboratory and clinical parameters for postoperative risk prediction.
The findings of Lai et al. provide an important reference point, indicating that specific features of fever dynamics, including late postoperative onset after postoperative day 2 (POD2), higher peak temperatures (>38.6 °C), and multiple temperature elevations, were associated with an increased risk of infectious complications following liver resection. These observations simultaneously highlight the limitations of traditional single-point temperature measurements as a diagnostic tool in the assessment of postoperative fever [2].
In a complementary translational liver-surgery study, Chopra et al. compared postoperative immune responses after laparoscopic versus open liver resection by measuring monocyte HLA-DR expression and ex vivo-stimulated secretion of proinflammatory cytokines (TNF-α, IL-6, IFN-γ). The study found that laparoscopic resection, associated with less tissue trauma, preserved higher monocyte HLA-DR expression postoperatively, whereas open surgery was accompanied by a marked decrease in HLA-DR expression in the early postoperative period, consistent with greater postoperative immunosuppression following more extensive surgical injury [5].
As discussed above, fever reflects activation of evolutionarily conserved inflammatory pathways in which proinflammatory cytokines mediate elevation of the hypothalamic temperature set point and coordinate immune responses [1]. This close coupling between temperature control and inflammatory signaling indicates that postoperative fever patterns may mirror underlying inflammatory states and aid in differentiating etiology and the risk of infectious complications after liver resection. After analysis of the available studies, it appears reasonable to interpret fever burden and its trajectory as a screening signal, albeit one that requires appropriate clinical context. At the same time, the limitations of this approach must be acknowledged: continuous skin temperature monitoring remains susceptible to environmental influences, peripheral perfusion, and nursing interventions, and the interpretation of temperature trajectories requires careful threshold calibration and consideration of modifying factors such as antipyretic therapy, post-transplant immunosuppression, blood transfusions, and vascular complications. Available evidence supports a hybrid approach in which continuous temperature monitoring serves as an early screening tool, complemented by targeted diagnostics (including early inflammatory markers, microbiological testing, and advanced imaging), particularly when temperature trajectories or fever burden deviate from the expected postoperative course. Continuous temperature monitoring may provide objective longitudinal temperature data and could support clinical decision-making when interpreted alongside clinical, laboratory, and imaging findings. In future validated protocols, predictable fever trajectories may help support observation, whereas late-onset, increasing-amplitude, or recurrent patterns may indicate a higher risk of complications, including infections, and prompt further diagnostic evaluation.
In this review, the authors present the view that technology is not an end in itself, but rather an important tool for phenotyping patients’ immunometabolic responses based on fever trajectories and fever burden.

Limitations

The limitations of this review consist of several methodological and conceptual factors. First, it was designed as a narrative review and therefore does not incorporate formal systematic review methodology, including standardized risk-of-bias assessment or quantitative meta-analysis. Second, direct liver-surgery-specific evidence regarding fever burden and postoperative temperature trajectories remains limited and is derived predominantly from observational studies. Third, several mechanistic and conceptual interpretations discussed in this review rely on extrapolation from sepsis, critical care, and non-hepatic postoperative literature. Consequently, the proposed interpretation of fever burden after liver surgery should currently be regarded as hypothesis-generating and requires prospective validation in liver-surgery-specific clinical cohorts.

5. Conclusions

Fever after liver surgery may reflect a clinically relevant component of the postoperative immunometabolic response rather than serving solely as a non-specific marker of infection. A quantitative approach incorporating fever burden and temperature trajectories may provide additional insight beyond isolated temperature measurements. Continuous temperature monitoring and temporal pattern analysis could support differentiation between adaptive postoperative inflammatory responses and patterns requiring further diagnostic evaluation. However, the clinical utility and prognostic relevance of fever burden after liver surgery require prospective validation in liver-specific patient cohorts.

Author Contributions

Conceptualization, M.J., B.P., J.M., W.P. and P.M.; methodology, W.P., P.M., M.J., B.P. and J.M.; software, P.M., J.M., B.P., M.J. and W.P.; validation, B.P., M.J., W.P., P.M. and J.M.; formal analysis, J.M., W.P., P.M., B.P. and M.J.; investigation, M.J., P.M., J.M., W.P. and B.P.; resources, W.P., B.P., M.J., J.M. and P.M.; data curation, P.M., J.M., B.P., W.P. and M.J.; writing—original draft preparation, B.P., W.P., M.J., P.M. and J.M.; writing—review and editing, J.M., B.P., P.M., W.P. and M.J.; visualization, M.J., W.P., J.M., B.P. and P.M.; supervision, W.P., M.J., P.M., J.M. and B.P.; project administration, P.M., B.P., W.P., M.J. and J.M.; funding acquisition, J.M., P.M., B.P., M.J. and W.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
IL-6Interleukin-6
HSP70Heat shock protein 70
IL-1βInterleukin-1β
IL-10Interleukin-10
COX-2Cyclooxygenase-2
IFN-γInterferon-gamma
TNF-αTumor necrosis factor-alpha
STAT3Signal transducer and activator of transcription 3

References

  1. Evans, S.S.; Repasky, E.A.; Fisher, D.T. Fever and the thermal regulation of immunity: The immune system feels the heat. Nat. Rev. Immunol. 2015, 15, 335–349. [Google Scholar] [CrossRef]
  2. Lai, H.F.; Chau, I.Y.; Lei, H.J.; Chou, S.C.; Hsia, C.Y.; Kao, Y.C.; Chau, G.Y. Postoperative fever after liver resection: Incidence, risk factors, and characteristics associated with febrile infectious complication. PLoS ONE 2022, 17, e0262113. [Google Scholar] [CrossRef]
  3. Bhavani, S.V.; Carey, K.A.; Gilbert, E.R.; Afshar, M.; Verhoef, P.A.; Churpek, M.M. Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories. Am. J. Respir. Crit. Care Med. 2019, 200, 327–335. [Google Scholar] [CrossRef]
  4. Ma, X.; Huang, T.; Chen, X.; Li, Q.; Liao, M.; Fu, L.; Huang, J.; Yuan, K.; Wang, Z.; Zeng, Y. Molecular mechanisms in liver repair and regeneration: From physiology to therapeutics. Signal Transduct. Target. Ther. 2025, 10, 63. [Google Scholar] [CrossRef] [PubMed]
  5. Chopra, S.S.; Haacke, N.; Meisel, C.; Unterwalder, N.; Fikatas, P.; Schmidt, S.C. Postoperative immunosuppression after open and laparoscopic liver resection: Assessment of cellular immune function and monocytic HLA-DR expression. J. Soc. Laparoendosc. Surg. 2013, 17, 615–621. [Google Scholar] [CrossRef]
  6. Wang, S.; Ji, G.; Feng, X.; Huang, L.; Luo, J.; Yu, P.; Zheng, J.; Yang, B.; Wang, X.; Zhao, Q. Temperature Measurement Timings and the Fever Detection Rate After Gastrointestinal Surgery: Retrospective Cross-Sectional Study. Interact. J. Med. Res. 2024, 13, e50585. [Google Scholar] [CrossRef]
  7. Nathansen, A.B.; Mølgaard, J.; Meyhoff, C.S.; Aasvang, E.K. Comparison of Wireless Continuous Axillary and Core Temperature Measurement after Major Surgery. Sensors 2024, 24, 4469. [Google Scholar] [CrossRef]
  8. Boyer, J.; Eckmann, J.; Strohmayer, K.; Koele, W.; Federspiel, M.; Schenk, M.; Weiss, G.; Krause, R. Investigation of Non-invasive Continuous Body Temperature Measurements in a Clinical Setting Using an Adhesive Axillary Thermometer (SteadyTemp®). Front. Digit. Health 2021, 3, 794274. [Google Scholar] [CrossRef] [PubMed]
  9. Wang, H.; Xi, Z.; Deng, L.; Pan, Y.; He, K.; Xia, Q. Macrophage Polarization and Liver Ischemia-Reperfusion Injury. Int. J. Med. Sci. 2021, 18, 1104–1113. [Google Scholar] [CrossRef]
  10. Kozłowski, H.M.; Sobocińska, J.; Jędrzejewski, T.; Maciejewski, B.; Dzialuk, A.; Wrotek, S. Fever-Range Hyperthermia Promotes Macrophage Polarization towards Regulatory Phenotype M2b. Int. J. Mol. Sci. 2023, 24, 17574. [Google Scholar] [CrossRef] [PubMed]
  11. Maloney, E.; Duffy, D. Deciphering the relationship between temperature and immunity. Discov. Immunol. 2024, 3, kyae001. [Google Scholar] [CrossRef] [PubMed]
  12. Cantet, J.M.; Yu, Z.; Ríus, A.G. Heat Stress-Mediated Activation of Immune-Inflammatory Pathways. Antibiotics 2021, 10, 1285. [Google Scholar] [CrossRef] [PubMed]
  13. Hasday, J.D.; Fairchild, K.D.; Shanholtz, C. The Role of Fever in the Infected Host. Microbes Infect. 2000, 2, 1891–1904. [Google Scholar] [CrossRef]
  14. Pietrzyk, B.; Mikolajczyk, J.; Joniec, A.; Fajferek, T.; Kaczara, S. The Role of Thermal Immunomodulation in Postoperative Wound Repair with a Focus on Hepatic Surgery. Int. J. Mol. Sci. 2026, 27, 1473. [Google Scholar] [CrossRef]
  15. Chong, D.L.W.; Shah, S.A.; Kutschenreuter, J.; Cusman, R.; Pillai, M.M.; Kirwan, D.E.; Gilman, R.H.; Friedland, J.S. Fever-Induced Heat Shock Protein-70 Regulates Macrophage IL-1β and IL-10 Secretion During Mycobacterium Tuberculosis Infection. Eur. J. Immunol. 2025, 55, e51963. [Google Scholar] [CrossRef]
  16. Wang, L.; Wang, D.; Zhang, T.; Ma, Y.; Tong, X.; Fan, H. The role of immunometabolism in macrophage polarization and its impact on acute lung injury/acute respiratory distress syndrome. Front. Immunol. 2023, 14, 1117548. [Google Scholar] [CrossRef]
  17. Lu, A.H.; Jain, V.; Chen, P.H.; Churpek, M.M.; Verhoef, P.A.; Quyyumi, A.A.; Bhavani, S.V. Temperature Trajectories Correlate with Cardiac Function in Patients with Sepsis. Crit. Care Explor. 2025, 7, e1282. [Google Scholar] [CrossRef]
  18. Wang, N.; Liang, H.; Zen, K. Molecular mechanisms that influence the macrophage m1-m2 polarization balance. Front. Immunol. 2014, 5, 614. [Google Scholar] [CrossRef]
  19. O’Neill, L.A.; Pearce, E.J. Immunometabolism Governs Dendritic Cell and Macrophage Function. J. Exp. Med. 2016, 213, 15–23. [Google Scholar] [CrossRef] [PubMed]
  20. Keitelman, I.A.; Sabbione, F.; Shiromizu, C.M.; Giai, C.; Fuentes, F.; Rosso, D.; Ledo, C.; Miglio Rodriguez, M.; Guzman, M.; Geffner, J.R.; et al. Short-Term Fever-Range Hyperthermia Accelerates NETosis and Reduces Pro-inflammatory Cytokine Secretion by Human Neutrophils. Front. Immunol. 2019, 10, 2374. [Google Scholar] [CrossRef]
  21. Kawai, T.; Ikegawa, M.; Ori, D.; Akira, S. Decoding Toll-like receptors: Recent insights and perspectives in innate immunity. Immunity 2024, 57, 649–673. [Google Scholar] [CrossRef]
  22. Lu, J.; Zhong, X.; Guo, C.; Tang, L.; Yu, N.; Peng, C.; Ding, Y.; Bao, X.; Zhou, J.; Shi, Y. TLR7-MyD88-DC-CXCL16 axis results neutrophil activation to elicit inflammatory response in pustular psoriasis. Cell Death Dis. 2023, 14, 315. [Google Scholar] [CrossRef]
  23. Cutolo, M.; Campitiello, R.; Gotelli, E.; Soldano, S. The Role of M1/M2 Macrophage Polarization in Rheumatoid Arthritis Synovitis. Front. Immunol. 2022, 13, 867260. [Google Scholar] [CrossRef]
  24. Singer, M.; Deutschman, C.S.; Seymour, C.W.; Shankar-Hari, M.; Annane, D.; Bauer, M.; Bellomo, R.; Bernard, G.R.; Chiche, J.D.; Coopersmith, C.M.; et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016, 315, 801–810. [Google Scholar] [CrossRef]
  25. Beadle, J.L.; Perman, S.M.; Pennington, J.; Gaieski, D.F. An investigation of temperature and fever burdens in patients with sepsis admitted from the emergency department to the hospital. Acute Med. Surg. 2023, 10, e902. [Google Scholar] [CrossRef]
  26. Yehya, N.; Fitzgerald, J.C.; Hayes, K.; Zhang, D.; Bush, J.; Koterba, N.; Chen, F.; Tuluc, F.; Teachey, D.T.; Balamuth, F.; et al. Temperature Trajectory Sub-phenotypes and the Immuno-Inflammatory Response in Pediatric Sepsis. Shock 2022, 57, 645–651. [Google Scholar] [CrossRef]
  27. Drewry, A.M.; Fuller, B.M.; Bailey, T.C.; Hotchkiss, R.S. Body temperature patterns as a predictor of hospital-acquired sepsis in afebrile adult intensive care unit patients: A case-control study. Crit. Care 2013, 17, R200. [Google Scholar] [CrossRef] [PubMed]
  28. Nohra, E.; Appelbaum, R.D.; Farrell, M.S.; Carver, T.; Jung, H.S.; Kirsch, J.M.; Kodadek, L.M.; Mandell, S.; Nassar, A.K.; Pathak, A.; et al. Fever and infections in surgical intensive care: An American Association for the Surgery of Trauma Critical Care Committee clinical consensus document. Trauma Surg. Acute Care Open 2024, 9, e001303. [Google Scholar] [CrossRef] [PubMed]
  29. So, M.; Hand, J.; Forrest, G.; Pouch, S.M.; Te, H.; Ardura, M.I.; Bartash, R.M.; Dadhania, D.M.; Edelman, J.; Ince, D.; et al. White paper on antimicrobial stewardship in solid organ transplant recipients. Am. J. Transplant. 2022, 22, 96–112. [Google Scholar] [CrossRef] [PubMed]
  30. Wang, M.J.; Zhang, H.L.; Chen, F.; Guo, X.J.; Liu, Q.G.; Hou, J. The double-edged effects of IL-6 in liver regeneration, aging, inflammation, and diseases. Exp. Hematol. Oncol. 2024, 13, 62. [Google Scholar] [CrossRef]
  31. Lee, C.T.; Zhong, L.; Mace, T.A.; Repasky, E.A. Elevation in Body Temperature to Fever Range Enhances and Prolongs Subsequent Responsiveness of Macrophages to Endotoxin Challenge. PLoS ONE 2012, 7, e30077. [Google Scholar] [CrossRef]
  32. Derwin, R.; Patton, D.; Strapp, H.; Moore, Z. The effect of inflammation management on pH, temperature, and bacterial burden. Int. Wound J. 2023, 20, 1118–1129. [Google Scholar] [CrossRef]
  33. Liu, Y.; Zhao, Q.; Li, K.; Dowding, D. Use of continuous temperature data from wearable devices for fever or infection management in acute hospital settings: A scoping review protocol. BMJ Open 2025, 15, e103630. [Google Scholar] [CrossRef]
  34. Verma, N.; Haji-Abolhassani, I.; Ganesh, S.; Vera-Aguilera, J.; Paludo, J.; Heitz, R.; Markovic, S.N.; Kulig, K.; Ghoreyshi, A. A Novel Wearable Device for Continuous Temperature Monitoring & Fever Detection. IEEE J. Transl. Eng. Health Med. 2021, 9, 2700407. [Google Scholar] [CrossRef] [PubMed]
  35. Roberts, N.J., Jr.; Sarria, J.C. Recognizing the roles of fever in host survival and in medical intervention in infectious diseases. Am. J. Med. Sci. 2024, 368, 85–89. [Google Scholar] [CrossRef] [PubMed]
  36. Prescott, H.C. Identifying Sepsis Subtypes from Routine Clinical Data. Am. J. Respir. Crit. Care Med. 2019, 200, 272–273. [Google Scholar] [CrossRef]
  37. Grant, J.; Mcnulty, M.C.; Kinnard, K.; Nagin, D.; Robicsek, A.; Bashyal, R.; Padman, R.; Shah, N. Using Group-Based Trajectory Temperature Modeling to Predict Postoperative Infections after Total Knee Arthroplasty. Open Forum Infect. Dis. 2017, 4, S338–S339. [Google Scholar] [CrossRef][Green Version]
  38. Pile, J.C. Evaluating postoperative fever: A focused approach. Cleve. Clin. J. Med. 2006, 73, S62–S66. [Google Scholar] [CrossRef]
  39. Schäfer, L.; Dickel, F.; Strohmayer, K.; Koele, W.; Leber, B.; Sucher, R.; Stiegler, P. Early Detection of Postoperative Infections Using Continuous Temperature Monitoring: A Prospective Clinical Trial. J. Clin. Monit. Comput. 2025. [Google Scholar] [CrossRef]
  40. Fajferek, T.; Joniec, A.; Kaczara, S.; Mażul Kulesza, E.; Mikolajczyk, J.; Pietrzyk, B. Temperature Monitoring for Early Detection of Postoperative Wound Infections: A Narrative Review. Appl. Sci. 2025, 15, 12856. [Google Scholar] [CrossRef]
Applsci 16 04883 g001
Figure 1. Flow diagram of literature identification and study selection.
Figure 1. Flow diagram of literature identification and study selection.
Applsci 16 04883 g001
Applsci 16 04883 g002
Figure 2. Conceptual framework of fever burden and temperature trajectories after liver surgery.
Figure 2. Conceptual framework of fever burden and temperature trajectories after liver surgery.
Applsci 16 04883 g002
Table 1. Evidence base for fever burden after liver surgery.
Table 1. Evidence base for fever burden after liver surgery.
Author, YearSettingStudy TypeFever/Temperature or Immune AssessmentKey Finding Relevant to This ReviewEvidence Category
Lai et al., 2022 [2]Liver resectionRetrospective clinical cohort studyPostoperative fever characteristics, including timing of fever onset, peak temperature, and recurrent febrile episodesDelayed fever onset after postoperative day 2, peak temperature > 38.6°C, and recurrent febrile episodes were associated with febrile infectious complications after liver resection. This is the strongest direct liver-surgery-specific clinical evidence supporting the relevance of fever dynamics.Direct liver-surgery clinical evidence
Chopra et al., 2013 [5]Open versus laparoscopic liver resectionExperimental translational liver-surgery studyMonocytic HLA-DR expression and ex vivo-stimulated cytokine response after liver resectionLaparoscopic liver resection showed a trend toward better preservation of postoperative immune function compared with open surgery. These findings support biological plausibility linking surgical injury with postoperative host-response changes, but do not validate fever burden as a diagnostic or prognostic marker.Direct liver-surgery mechanistic evidence
Wang et al., 2021 [9]Liver ischemia–reperfusion injuryReview of experimental and translational evidenceMacrophage polarization in liver ischemia–reperfusion injuryMacrophage polarization is closely involved in liver ischemia–reperfusion injury and tissue repair. This supports the biological relevance of linking postoperative inflammatory temperature patterns with macrophage-mediated liver injury and regeneration, but remains mechanistic rather than clinical fever-burden evidence.Liver-specific mechanistic evidence
Wang et al., 2024 [6]Gastrointestinal surgeryRetrospective cross-sectional postoperative studyFever detection according to different temperature measurement timingsFever detection after gastrointestinal surgery depended strongly on timing and frequency of temperature measurements. This supports the methodological limitation of intermittent postoperative temperature assessment.Non-hepatic postoperative monitoring evidence
Nathansen et al., 2024 [7]Major abdominal surgeryPostoperative validation studyWireless continuous axillary temperature monitoring compared with urinary bladder core temperature measurementWireless continuous axillary temperature monitoring was feasible after major abdominal surgery and was compared with urinary bladder core temperature measurement in 40 postoperative patients. This supports feasibility of high-temporal-resolution monitoring but does not validate fever burden in liver surgery.Non-hepatic postoperative monitoring evidence
Boyer et al., 2021 [8]Clinical temperature monitoringProspective multicentre validation studyContinuous non-invasive axillary temperature monitoring using SteadyTemp®Adhesive axillary thermometer enabled continuous non-invasive temperature assessment in a clinical setting, supporting feasibility of wearable temperature monitoring technologies.Temperature-monitoring technology evidence
Bhavani et al., 2019 [3]Sepsis/critical careRetrospective temperature-trajectory modelling study with validationLongitudinal temperature trajectoriesTemperature-trajectory clustering identified distinct sepsis subphenotypes with different clinical risk profiles. This supports the conceptual value of trajectory-based interpretation but represents hypothesis-generating extrapolation from non-hepatic critical illness.Hypothesis-generating extrapolation from sepsis/critical care
Evans et al., 2015 [1]Fever biology and immune regulationMechanistic narrative reviewThermal regulation of immune responses during feverFever-range temperatures modulate innate and adaptive immune responses and support interpretation of fever as an active biological response rather than a passive symptom.Supportive mechanistic immunology evidence
Kozlowski et al., 2023 [10]Fever-range hyperthermia and macrophage phenotypeExperimental mechanistic studyFever-range hyperthermia exposure and macrophage polarizationFever-range hyperthermia promoted macrophage polarization toward a regulatory M2b-like phenotype. This supports biological plausibility linking temperature elevation with macrophage phenotype modulation, but it is not direct liver-surgery clinical evidence.Supportive mechanistic immunology evidence
Table 2. Conceptual, hypothesis-generating associations between postoperative fever patterns and macrophage polarization states in the regenerating liver.
Table 2. Conceptual, hypothesis-generating associations between postoperative fever patterns and macrophage polarization states in the regenerating liver.
FeatureM1-Like Macrophages (Early Inflammatory Phase)M2-Like Macrophages (Regulatory/
Regenerative Phase)
Dominant triggersTissue injury, damage-associated molecular patterns (DAMPs), ischemia–reperfusion stressResolution signals, apoptotic cells, regenerative cues
Association with feverEarly increase in postoperative temperature, more pronounced febrile response, or persistent/recurrent fever episodesDeclining or moderate fever response accompanying resolution of postoperative inflammation
Cytokine profileIL-1β, IL-6, TNF-α, COX-2IL-10, TGF-β, reduced IL-1β signalling
Metabolic stateGlycolysis-dominant metabolism with increased reactive oxygen species productionOxidative phosphorylation and lipid metabolism predominance
Functional roleAmplification of inflammatory signalling, pathogen control, and clearance of damaged tissueResolution of inflammation, tissue repair, and support of regenerative processes
Potential impact
on liver tissue		Persistent activation may contribute to exacerbation of ischemia–reperfusion injuryMay support hepatocyte proliferation and tissue remodelling
Potential clinical
interpretation		Potential association with persistent inflammatory activation and prolonged postoperative fever patternsPotential association with regulated postoperative inflammatory response and recovery processes
Interpretation
in liver surgery		May reflect an adaptive early inflammatory response, although persistent activation could indicate dysregulated postoperative inflammationMay reflect transition toward inflammation resolution and regenerative recovery processes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Pietrzyk, B.; Majdak, P.; Pierzchała, W.; Janeczek, M.; Mikolajczyk, J. Fever Burden After Liver Surgery: From Infection Diagnostics to Phenotyping of the Immunometabolic Response. Appl. Sci. 2026, 16, 4883. https://doi.org/10.3390/app16104883

AMA Style

Pietrzyk B, Majdak P, Pierzchała W, Janeczek M, Mikolajczyk J. Fever Burden After Liver Surgery: From Infection Diagnostics to Phenotyping of the Immunometabolic Response. Applied Sciences. 2026; 16(10):4883. https://doi.org/10.3390/app16104883

Chicago/Turabian Style

Pietrzyk, Barbara, Paulina Majdak, Wiktor Pierzchała, Maksymilian Janeczek, and Jedrzej Mikolajczyk. 2026. "Fever Burden After Liver Surgery: From Infection Diagnostics to Phenotyping of the Immunometabolic Response" Applied Sciences 16, no. 10: 4883. https://doi.org/10.3390/app16104883

APA Style

Pietrzyk, B., Majdak, P., Pierzchała, W., Janeczek, M., & Mikolajczyk, J. (2026). Fever Burden After Liver Surgery: From Infection Diagnostics to Phenotyping of the Immunometabolic Response. Applied Sciences, 16(10), 4883. https://doi.org/10.3390/app16104883

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop