Increased tissue water in patients with severe sepsis affects tissue oxygenation measured by near-infrared spectroscopy: a prospective, observational case-control study

Introduction

Severe sepsis is a life-threatening disease characterised by severe systemic inflammation, unstable haemodynamics, and multiple organ failure (1,2). Current treatment guidelines recommend fluid resuscitation to expand the intravascular volume and the use of vasopressors to achieve a target systemic arterial pressure level for the normalisation of unstable haemodynamics (3,4). However, excessive fluid administration, leading to tissue oedema and deterioration of tissue perfusion, remains a major concern (5). In addition, due to microcirculatory alterations in the presence of severe sepsis, loss of coherence between the macrocirculation and microcirculation occurs (6). Therefore, achieving the recommended systemic arterial pressure target may not guarantee an improvement in peripheral tissue perfusion and oxygenation (6-9). Sepsis with normal blood pressure may still show abnormal microcirculation (10,11). The primary function of the circulatory system is to deliver nutrients and oxygen to the organs and tissues and remove waste products. The ultimate goal of treating sepsis-related circulatory dysfunction is to restore microcirculation to provide adequate tissue perfusion and oxygenation to prevent eventual multiple organ failure (12,13). Therefore, monitoring tissue perfusion and oxygenation is essential for managing sepsis-related circulatory dysfunction.

Near-infrared spectroscopy (NIRS), a non-invasive and indirect method, has been developed and applied to measure tissue oxygenation (14). NIRS can detect the tissue content of haemoglobin (Hb) and myoglobin (Mb) in different oxygenation states (15). The estimation of tissue Hb oxygen saturation (StO₂) is based on the differential absorption properties of oxy-Hb (HbO₂) and deoxy-Hb (HbR) under different spectra of near-infrared wavelength light (16). In limb skeletal muscle at rest, light absorption is mainly from Mb, which contributes 50% to 70% of the total light absorption potential for NIRS in skeletal muscle (17). However, Hb rather than Mb can be altered by limb perfusion (18). In the presence of sepsis, the baseline thenar StO₂ is low and changes in StO₂ recovery after an ischaemic challenge are related to the survival of patients in the intensive care unit (ICU) (19). Low StO₂ in early resuscitation is associated with poor outcomes and high mortality rates (20,21). However, sepsis-related tissue oedema caused by endothelial dysfunction and vascular leak has been determined to have a confounding effect on the assessment of StO₂ with NIRS (22,23). To date, the impact of tissue water (H₂O) on tissue HbO₂ and HbR has not been comprehensively investigated.

In our previous study, we used NIRS to detect tissue Hb and H₂O in the extremities of children with Kawasaki disease. We found that tissue H₂O was significantly higher, but tissue Hb was lower in patients with Kawasaki disease than in healthy controls (24). In the present study, we applied NIRS to simultaneously detect and quantify regional tissue Hb and H₂O content in adult patients with severe sepsis and healthy volunteers. In addition, we compared the differences in regional tissue oxygenation and H₂O content between patients and healthy controls, as well as evaluated the relationships among systemic arterial pressure, regional tissue oxygenation, and H₂O content in patients with severe sepsis. We present the following article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-22-127/rc).

Methods

Near-infrared diffuse optical technique and wireless optical monitoring system

The fundamental principle of the near-infrared diffuse optical technique is based on the unique absorption and scattering properties of different tissue components corresponding to different wavelengths of light (15,25-29) For red and near-infrared wavelength light (range, 600–1,200 nm), HbO₂, HbR, Mb and H₂O are the major absorbers in human tissue. Under the assumption that the Mb concentration during the short term is constant, we only monitor the change of HbO₂, HbR, and H₂O in this study. Based on the apparent difference in the absorption spectra of HbO₂, HbR, and H₂O corresponding to different wavelengths, we used a tri-wavelength light (700, 910, and 950 nm)-emitting diode to assemble a wireless optical monitoring system comprising an optical probe, a wireless signal acquisition module, and a back-end host system (Figure 1). The optical probe was positioned on the volar surface of the right leg of the patients and healthy volunteers, at the level of the anterior tibial muscle, to estimate the relative tissue concentrations of HbO₂ ([HbO₂]), HbR ([HbR]), total Hb ([HbT]), and H₂O ([H₂O]) from the change in the optical density corresponding to different wavelengths. For the wavelength λ, the optical density attenuation of red or near-infrared light in human tissue can be simply expressed as

OD(λ)=(εHbO2(λ)⋅[HbO2]+εHbR(λ)⋅[HbR]+εH2O(λ)⋅[H2O])⋅d⋅B(λ)[1]

Figure 1 Schematic diagram of the near-infrared spectroscopy system configuration and the position of the optical probe. The wireless optical monitoring system consists of an optical probe, a wireless signal acquisition module, and a back-end host system. The optical probe contains a tri-wavelength LED and a PD, which serve as the light emitter and receiver, respectively. The wireless signal acquisition module consists of several parts: an LED-driving circuit, a PD-sensing circuit, a microprocessor, and a wireless transmission circuit. It is designed to drive and switch the tri-wavelength LED, receive, amplify, and filter the optical signal obtained from the PD, and wirelessly transmit the optical signal to the back-end host system. The tri-wavelength light emitter provides a tri-wavelength light that penetrates through the tissue, and the light receiver receives the penetrated light. The optical signal received from the PD was digitised and transmitted to the back-end host system. A commercial laptop was used as the platform of the back-end host system and estimated the relative tissue concentrations of oxy-haemoglobin, deoxy-haemoglobin, and water from the change in the optical density corresponding to different wavelengths. LED, light-emitting diode; PD, photodiode.

where d is the distance between the light source and detector, B(λ) is the differential path-length factor, and ε_HbO2(λ), ε_HbR(λ), and ε_H2O(λ) denote the molar extinction coefficient of [HbO₂], [HbR], and [H₂O]. Then, [HbO₂], [HbR], and [H₂O] can be estimated by the approach of least-squares approximation, as followings,

[{HbO2},{HbR},{H2O}]=((ET⋅E)−1⋅ET⋅A)/dwhereE=[{εHbO2(λ1),εHbR(λ1),εH2O(λ1)},{εHbO2(λ2),εHbR(λ2),εH2O(λ2)},{εHbO2(λ3),εHbR(λ3),εH2O(λ3)}]andA=[OD(λ1)B(λ1),OD(λ2)B(λ2),OD(λ3)B(λ3)][2]

StO₂ was calculated as

StO2=[HbO2][HbO2]+[HbR]×100%[3]

Study design and participants

This prospective, observational case-control study was approved by the Institutional Review Board of Chang Gung Medical Foundation (approval No. 103-5357B). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was conducted in a 20-bed medical ICU of Chiayi Chang Gung Memorial Hospital from 27 November 2015 to 30 April 2019. Adult patients (age ≥18 years) who were transferred to the ICU from the emergency department and admitted within 72 h for new-onset severe sepsis were enrolled. Severe sepsis was defined as sepsis with sepsis-induced tissue hypoperfusion or organ dysfunction according to the 2012 Surviving Sepsis Campaign criteria (30). Patients with pregnancy, active pulmonary tuberculosis, or contact isolation were excluded from the study. Healthy volunteers who did not have any disorders were recruited among the students of the National Chiao Tung University as healthy controls. Informed consent was obtained from the healthy volunteers and patients. Legal guardians provided informed consent to participate if the patient had cognitive impairment. After signing the informed consent form, the patients and healthy volunteers received a non-invasive NIRS device for use in estimations at rest. The estimated data were recorded after 3 min to stabilise the NIRS signals (31). The NIRS data were collected for 3 consecutive days or until the patient was transferred to an ordinary ward, discharged against medical advice, or died. We recorded the demographic and clinical data of all patients, including age, sex, aetiology of severe sepsis, acute physiology and chronic health evaluation II score on admission, systemic haemodynamic parameters, laboratory results, and ICU outcome. Patients with missing or incomplete NIRS data were excluded from the final analysis.

Sample size calculation

The sample size estimate for the study was based on a comparison of repeated measures between patients and controls. Since this study was a pilot study and there was no previous applicable research to calculate the effect size, we considered a power of 0.95 at the 0.05 alpha level and an estimated effect size of 0.15 to calculate the sample size. Using G*Power, a sample size of 70 per group was required. However, that was inflated by 20% for any potentially missing data, thus yielding a priori sample size of 84 per group.

Statistical analyses

Continuous data were summarised as mean, standard deviation (SD), and 95% confidence interval (CI) or median and interquartile range (IQR), as appropriate. Categorical data were expressed using counts and percentages. A two-sample t-test was used to compare the differences between cases and controls for continuous variables once normality was demonstrated; otherwise, the nonparametric Mann-Whitney U test was performed. The chi-square or Fisher’s exact test was performed for categorical variables. Pearson correlation coefficients were used to investigate pairwise relationships between continuous variables. As the relative tissue concentrations of Hb and H₂O and tissue oxygenation were repeatedly measured at designated intervals over time, generalised estimating equations (GEEs), which consider the correlation within individuals, were employed to evaluate the differences in NIRS parameters between groups. Statistical analyses were performed using SPSS version 22 (IBM Corp., Armonk, NY, USA). All tests were two-tailed with a significance level of 0.05.

Results

Demographic characteristics and clinical data of patients with severe sepsis

A total of 203 consecutive patients were assessed for eligibility (Figure 2). Six patients were excluded because of active pulmonary tuberculosis or requiring contact isolation, and 113 patients declined to participate in the study. The remaining 84 patients received the NIRS device for estimating regional tissue oxygenation and H₂O content. In seven patients, the wireless signals of the device were intermittently received by the back-end host system, and the data were incompletely recorded. Therefore, the integrated data of the remaining 77 patients were analysed. Of these 77 patients, 30 were women and 47 were men (Table 1). The median [IQR] age of the patients was 75 [65–83] years. In addition, 45 patients (58%) had septic shock and received vasoactive agent therapy. In the three consecutive days, the total mean (SD) of the patient’s net intake and output before the different NIRS measurements was 514.86 (960.87) mL per day, and the total mean (SD) of the amount of fluid administered to patients before the different NIRS measurements was 1,376.16 (823.84) mL per day. Furthermore, 51 patients (66%) had pulmonary infection, and 61 patients (79%) were ICU survivors. The median (IQR) length of ICU stay was 7.00 (4.00–11.50) days. There were a total of 30 healthy controls recruited for the study (Figure 2). Among the healthy controls, 20 (67%) were men with a median [IQR] age of 24 [23–25] years, which was significantly lower than the age of patients with sepsis (P<0.001) (Table 1).

Figure 2 Flowchart of patient inclusion and exclusion in the study. TB, tuberculosis; NIRS, near-infrared spectroscopy; ICU, intensive care unit.

Comparisons of relative tissue concentrations of haemoglobin and water and tissue oxygenation between healthy controls and patients with severe sepsis

In patients with severe sepsis, the first-day measurement of anterior tibial muscle [H₂O] was higher [mean (SD, 95% CI), 10.57 (3.37, 9.81–11.34) vs. 7.40 (1.89, 6.70–8.11); Table 2] and the [HbO₂], [HbT], and StO₂ were lower [0.20 (0.01, 0.20–0.20) vs. 0.22 (0.01, 0.22–0.23), 0.42 (0.02, 0.42–0.43) vs. 0.44 (0.02, 0.44–0.45), and 47.25% (1.97%, 46.80–47.70%) vs. 49.88% (1.26%, 49.41–50.35%), respectively; Table 2] than in healthy controls. In the next two consecutive days, the repeated measurements of [H₂O] were higher, whereas [HbO₂], [HbT], and StO₂ remained lower in patients than in healthy controls (Figure 3). The GEE analysis also showed that these four parameters were significantly different between the two groups (all P≤0.001, Figure 3).

Figure 3 Time courses of relative tissue concentrations of haemoglobin and water and tissue haemoglobin oxygen saturation. (A) [HbO₂], (B) [HbR], (C) [HbT], and (D) [H₂O], and (E) StO₂ measured from days 1 to 3 of the study in patients with severe sepsis and healthy controls are shown. Relative tissue concentrations of substances are expressed in arbitrary units (a.u.). Error bars represent the standard deviation of the mean. *, GEE analysis showed that the parameters of patients with severe sepsis changed significantly over time (day 1 vs. day 3, P=0.041 in [HbO₂] and P=0.036 in StO₂); **, GEE analysis shows a significant difference between patients with severe sepsis and healthy controls (P≤0.001). [HbO₂], relative tissue concentration of oxy-haemoglobin; [HbR], relative tissue concentration of deoxyhaemoglobin; [HbT], relative tissue concentration of total haemoglobin; [H₂O], relative tissue concentration of H₂O; StO₂, tissue haemoglobin oxygen saturation; GEE, generalised estimating equation.

However, in terms of [HbR], the patients had the same value as the healthy controls [mean (SD, 95% CI), 0.22 (0.02, 0.22–0.23) vs. 0.22 (0.02, 0.22–0.23), in first-day measurements; Table 2], and the GEE analysis revealed that there was no difference among the 3-day repeated measurements between the groups (P=0.996, 0.248, and 0.121 on days 1, 2, and 3, respectively; see https://cdn.amegroups.cn/static/public/qims-22-127-1.docx). Furthermore, concerning the changes in the parameters over time, [HbO₂] and StO₂ gradually decreased in patients with severe sepsis (day 1 vs. day 3, P=0.041 and P=0.036, respectively; Figure 3). However, there were no changes in the time trends of tissue H₂O content in either group or tissue oxygenation in healthy controls.

Relationship between tissue oxygenation and water content in severe sepsis

With respect to the relationship between tissue oxygenation and H₂O content, negative correlations were found between [H₂O] and [HbO₂] (r=−0.51, −0.53, and −0.67 on days 1, 2, and 3, respectively, P<0.01 for all; Table 3) and StO₂ (r=−0.42, −0.43, and −0.63 on days 1, 2, and 3, respectively, P<0.01, respectively; Table 3); however, [H₂O] and [HbR] were positively correlated (r=0.28 on day 2 and 0.54 on day 3, P<0.05 and P<0.01, respectively; Table 3). The correlations between [H₂O] and [HbO₂], [HbR], and StO₂ gradually became stronger during the 3-day repeated measurements (Figure 4A-4C). Furthermore, the correlation between [HbT] and StO₂ was negative (r=−0.29 on day 1, P<0.05; r=−0.46 and −0.65 on days 2 and 3, respectively, P<0.01 for both; Table 3 and Figure 4D). Meanwhile, the relationship between [HbO₂] and [HbR] changed over time: positive on day 1 (r=0.30, P<0.01; Table 3) but negative on days 2 and 3 (r=−0.65, P<0.01, and −0.81, P<0.01, respectively; Table 3 and Figure 4E).

Figure 4 A graphical representation of the relationships among the parameters of tissue oxygenation and water content. The correlations between the [H₂O] and the (A) [HbO₂], (B) [HbR], and (C) StO₂; (D) correlation between StO₂ and the [HbT]; and (E) correlation between [HbO₂] and [HbR] from day 1 to day 3 of the study are shown. Relative tissue concentrations of substances are expressed in arbitrary units (a.u.). **P<0.01; *P<0.05. The actual P values have been included in the https://cdn.amegroups.cn/static/public/qims-22-127-1.docx. [H₂O], relative tissue concentration of H₂O; [HbO₂], relative tissue concentration of oxy-haemoglobin; [HbR], relative tissue concentration of deoxyhaemoglobin; StO₂, tissue haemoglobin oxygen saturation; [HbT], relative tissue concentration of total haemoglobin.

Association of regional tissue oxygenation and water content with systemic arterial pressure in severe sepsis

With regard to the associations of systemic haemodynamics with regional tissue oxygenation and H₂O content in patients with severe sepsis, we analysed the correlations between real-time arterial blood pressures and NIRS parameters in patients who also received pulse contour cardiac output (PiCCO) monitoring. A total of 21 patients were monitored using the PiCCO. One of them was monitored starting from day 2, and monitoring was stopped for six patients on day 3 after participating in the study. We found that only [H₂O] was significantly positively correlated with systemic arterial pressure in the first-day measurement, and the correlation coefficients with systolic arterial pressure and mean arterial pressure (MAP) were 0.51 (P<0.05, Table 4 and Figure 5) and 0.45 (P<0.05, Table 4 and Figure 5), respectively. However, no significant correlation was found between tissue oxygenation and systemic arterial pressure.

Figure 5 A graphical representation of the relationships between tissue water content and systemic arterial pressures. The correlations between the [H₂O] and (A) systolic arterial pressure, (B) diastolic arterial pressure, and (C) mean arterial pressure from day 1 to day 3 of the study are shown. Relative tissue concentrations of substances are expressed in arbitrary units (a.u.). *P<0.05. The actual P values are included in the https://cdn.amegroups.cn/static/public/qims-22-127-1.docx. [H₂O], relative tissue concentration of H₂O.

Discussion

Fluid administration in a fluid-responsive patient with sepsis can increase the left heart filling pressure and cardiac output, promote tissue perfusion and oxygenation, preserve organ function, and provide a survival benefit (32-34). However, the infused fluid is exchanged between the plasma and interstitium, and a large amount of fluid leaks from the capillaries and eventually accumulates in the interstitium (35). Increased vascular permeability in sepsis increases plasma volume loss, which becomes more pronounced when vasopressors are used to raise blood pressure (36,37). Therefore, the infusion may transiently affect haemodynamics but eventually cause tissue oedema and worsen tissue perfusion (38). Microcirculation improved by fluid administration was only observed in patients with severe sepsis diagnosed within 24 h (39). Liberal fluid administration can cause organ dysfunction and increase mortality risk (5,40,41). The current study used NIRS to detect tissue H₂O and found that [H₂O] was significantly higher in patients with severe sepsis than in healthy controls. Estimating [H₂O] using NIRS may offer a real-time and non-invasive quantitative assessment of tissue oedema. This parameter is potentially valuable for guiding fluid therapy in patients with severe sepsis. Further studies are needed to ascertain the relationship between fluid administration and [H₂O].

StO₂ is a surrogate measure for assessing microcirculation (14,42). The value of StO₂ varies depending on the measurement site (43,44). The normal gastrocnemius muscle StO₂ is 65%±19% (45). Our study found that the normal anterior tibial muscle StO₂ was 49.88%±1.26%. Muscle StO₂ changes during limb perfusion (18). Lower venous oxygen saturation and StO₂ have been identified in sepsis-related hypoperfusion (19,46). StO₂ is dependent on [HbO₂] and [HbR]. [HbO₂], [HbT], and StO₂ were significantly lower in patients with severe sepsis than in healthy controls. However, the [HbR] values were similar. In an early study, Davis and Barstow found that during exercise, changes in total tissue Hb and Mb measured by NIRS can reflect changes in microvascular hematocrit (17). In addition, NIRS-derived total Hb can indicate changes in muscular blood flow during exercise, measured using Doppler ultrasound (47). Therefore, [HbT] in the present study could be associated with tissue blood flow at rest. Besides, changes in HbR reflect microvascular oxygen extraction (48). Therefore, [HbR] may be related to tissue oxygen consumption (VO₂) at rest. However, this does not mean that [HbR] can be a surrogate measure of VO₂. Therefore, our findings suggest that patients with severe sepsis had reduced limb perfusion, resulting in lower [HbT]. Nevertheless, their peripheral skeletal muscle VO₂ might remain unchanged, showing consistent [HbR] values in healthy controls at rest. [HbO₂] and StO₂ decreased with increasing oxygen extraction ratio (O₂ER). To date, whether muscle VO₂ increases in patients with sepsis remains controversial (49,50). VO₂ is physiologically dependent on perfusive oxygen delivery (QO₂) below critical QO₂ (51). QO₂ depends on blood flow, the product of heart rate and cardiac output, and O₂ concentrations in arterial and venous blood (15). Therefore, patients with an obvious decrease in blood flow have a physiological dependence of VO₂ on QO₂. However, whether pathological dependence of VO₂ on QO₂ occurs in septic patients has not yet been elucidated (52). Our findings are consistent with the findings of Menegueti et al., who found that VO₂ was not increased in patients with sepsis (53). Efforts to reduce metabolic demands from skeletal muscles using neuromuscular blockade do not alter VO₂, QO₂, and O₂ER in septic patients (54). The above findings explain why maintaining supranormal QO₂ may not benefit critically ill patients, as tissue oxygen demand may not be increased (55-57). Our study suggests that identifying the individual [HbT] and [HbR] using NIRS is crucial for non-invasively and indirectly understanding patients’ tissue perfusion and VO₂. These data may help determine the peripheral tissue response to altered systemic haemodynamics using inotropic agents and fluid resuscitation in patients with severe sepsis.

As an estimation of tissue perfusion and oxygenation, StO₂ is correlated with QO₂, responds to the ischaemic challenge, and may be associated with survival outcomes in patients with severe sepsis (19-21,58,59). Nevertheless, the clinical significance of StO₂ remains controversial. Baseline StO₂ cannot be used for the early detection of severe sepsis, and the routine implementation of resuscitation protocols incorporating StO₂ >80% as a target does not provide a survival benefit (60,61). An important reason for these controversial findings is that StO₂ is confounded by several factors, including tissue oedema (23). Compared with baseline StO₂, the measurement of the change in StO₂ reperfusion slope during a vascular occlusion test (VOT) may eliminate the personal confounding factor of tissue oedema and is significantly related to microcirculation in patients with septic shock and the outcome of septic patients (46,62). However, VOT is not convenient for continuous real-time monitoring of microcirculation. In the present study, we found that StO₂ was significantly negatively correlated with [H₂O], which resulted from the negative correlation between [H₂O] and [HbO₂]. In addition, the relationship between [HbO₂], [HbR], and StO₂ and [H₂O] became more relevant during the study period, suggesting that the impact of tissue H₂O on tissue oxygenation may become increasingly apparent during ICU admission. Our study determined that regional tissue H₂O interacts with tissue HbO₂ and StO₂. It remains unclear whether the oedematous interstitium physiologically leads to reduced regional tissue perfusion, thereby altering tissue oxygenation. More research is warranted to clarify the detailed mechanism by which tissue H₂O affects tissue perfusion and oxygenation, and whether fluid administration for normalising unstable haemodynamics in septic shock causes tissue oedema, leading to tissue perfusion deterioration.

In sepsis-induced hypoperfusion, additional fluid administration after the initial resuscitation should be guided by frequent reassessments of the patient’s haemodynamic status (3). Most measurements are obtained by monitoring systemic haemodynamics, and systemic arterial pressure is one of the most commonly measured parameters. The present study found that the regional tissue oxygenation parameters, including [HbO₂], [HbR], and StO₂, were not related to the systemic arterial pressure in the early stage of ICU admission. Our findings seem to be consistent with the concept of loss of haemodynamic coherence between the macrocirculation and microcirculation in sepsis (6). Systemic arterial pressure poorly reflects regional tissue perfusion (63). In addition, microcirculation is profoundly disturbed in severe sepsis, and the organ tissue blood supply may not reflect tissue oxygenation (64). Meanwhile, as mentioned above, fluid volume expansion to increase systemic arterial pressure also increases intravascular hydrostatic pressure, which may exacerbate fluid accumulation and result in tissue oedema (65). The oedematous interstitium reduces capillary perfusion, which in turn worsens tissue oxygenation (66). This may explain why systemic arterial pressure was positively correlated with tissue H₂O but was not related to tissue oxygenation in our study. Targeting an MAP level >65 mmHg is a general goal in the initial resuscitation of patients with septic shock (3). Jozwiak et al. recently found that the impact of a unique MAP target on peripheral oxygenation may differ widely among patients with septic shock (9). In this study, patients with severe sepsis were enrolled after ICU admission. Most of them had received initial fluid resuscitation for normalising systemic haemodynamics at the ER. Attempts to increase MAP levels early in ICU admission may not guarantee improved tissue oxygenation but may result in increased tissue H₂O. These findings suggest that care should be taken when administering fluid to normalise systemic blood pressure during early ICU admission, particularly if initial fluid resuscitation has already been performed. Initial fluid resuscitation may improve sepsis-induced hypoperfusion and improve patient survival (4). However, continued fluid administration following initial resuscitation may be harmful and should be guided by careful assessment of intravascular volume status and organ perfusion (67). Tissue H₂O can be measured using NIRS and is potentially helpful in appreciating the effectiveness of fluid therapy on regional tissue perfusion and oxygenation.

This study has some limitations. First, the estimated sample size required 70 people per group, but the healthy control group comprised only 30 people, reducing the statistical power. In addition, healthy controls had a lower mean age than those with severe sepsis. Therefore, differences in NIRS parameters may be attributed to differences in age. However, Rosenberry et al. recently found that age is related to NIRS-derived post-occlusion StO₂ recovery kinetics, but not baseline forearm StO₂ (68). Therefore, severe sepsis remained a significant factor contributing to the difference in NIRS parameters between the two groups. Another limitation is the lack of a multivariate analysis investigating the causal relationship between [H₂O] and tissue oxygenation parameters. Correlation analysis offers only crude assessments of the linear relationships between [H₂O] and tissue oxygenation parameters. The same limitation exists in the findings on the relationship between systemic arterial pressure and [H₂O]. However, the results provide evidence for the interaction of tissue H₂O with tissue Hb and StO₂ used to assess tissue perfusion and oxygenation. Compared with baseline StO₂, dynamic NIRS measurements are more relevant to sepsis-related microvascular dysfunction (19,69). However, we did not investigate the dynamic changes in [HbO₂], [HbR], and [H₂O] during VOT and their relationship to the StO₂ recovery slope. This crucial issue will be investigated and examined in future studies.

Conclusions

A NIRS device transmitting tri-wavelength light can be used to concurrently assess regional tissue oxygenation and H₂O content. The regional tissue H₂O content was significantly increased in patients with severe sepsis. In the early phase of severe sepsis, elevated systemic arterial pressure may be related to increased regional tissue H₂O, but not to tissue oxygenation. Therefore, the measurement of tissue H₂O is crucial and should be considered when estimating microcirculation and tissue oxygenation in patients with severe sepsis. Further studies are needed to elucidate the physiological effect of tissue H₂O on tissue oxygenation and whether it can be accurately measured.

Acknowledgments

Funding: This work was supported by the Chang Gung Medical Foundation of Taiwan (Nos. CORPG6E0111, CORPG6E0112, and CORPG6E0113 to Chin-Kuo Lin).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-22-127/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-127/coif). CKL received grants from the Chang Gung Medical Foundation of Taiwan (Nos. CORPG6E0111, CORPG6E0112, and CORPG6E0113) for the study. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Review Board of Chang Gung Medical Foundation (No. 103-5357B). Informed consent was obtained from the healthy volunteers and patients. Legal guardians provided informed consent to participate if the patient had cognitive impairment.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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