1 Introduction

Septic shock is a life-threatening condition characterized by an uncontrolled immune response to infection, leading to severe circulatory, cellular, and metabolic abnormalities [1]. It is associated with a greater risk of mortality, prolonged hospital stays, high duration of mechanical ventilation (MV), need to use vasopressors, renal replacement therapy (RRT), increased costs for patients, and increased use of healthcare resources [2,3,4].

Fluid balance disruption is a key feature of septic shock, caused by increased capillary permeability and fluid leakage into tissues [5, 6]. Additionally, elevated blood lactate levels are commonly observed in septic shock patients [7, 8]. Previous studies showed that initial lactate level and lactate clearance as markers for response to resuscitation have demonstrated a clear association with clinical outcomes including mortality. Therefore, managing fluid balance and lactate clearance are vital aspects of septic shock management, as they profoundly impact prognostic outcomes [9, 10]. Maintaining fluid balance, equilibrium between fluid intake and output in the body, is critical because inadequate or excessive fluid administration can have detrimental effects on patient outcomes [11, 12]. Inadequate fluid resuscitation can lead to inadequate tissue perfusion and organ dysfunction, while excessive fluid administration can result in fluid overload, worsening organ dysfunction, and increased mortality rates [11,12,13]. Proper monitoring and management of fluid balance are crucial for ensuring adequate perfusion and improving the prognosis of septic shock patients.

While hyperlactatemia is important for identifying tissue hypoxia and initiating resuscitation [14, 15], other factors like sustained hyperadrenergia and impaired hepatic clearance can also raise lactate levels. [16,17,18]. Additionally, lactate measurements may not be universally available, and lactate recovery is slow, making it a suboptimal target for fluid resuscitation [19, 20]. Therefore, relying solely on hyperlactatemia for resuscitation may be inappropriate. Evidence suggests that indicators such as peripheral perfusion index (PPI) [21, 22], capillary refill time (CRT) [23, 24], and mottling score are reliable for reflecting perfusion [25]. The ANDROMEDA-SHOCK trial and its post hoc analysis indicated that a CRT-guided strategy may limit organ failure and reduce mortality compared to a lactate-targeted approach [23]. CRT, due to its simplicity, bedside applicability, rapid recovery after fluid resuscitation, and suitability for resource-limited settings, could be used as a target for fluid resuscitation in septic shock [26]. Similarly, the mottling score, as a non-invasive marker, is easy to assess and could guide treatments targeting organ perfusion and microcirculation [27]. A study by Dumas et al. [28] supported the high prognostic value of mottling score for 14-day mortality in septic patients.

This study aimed to compare the predictive ability of macrocirculation and microcirculation markers on the outcomes of patients with septic shock. While MAP and lactate serum levels are commonly used markers in resuscitation, broadening the assessment to include microcirculation markers may better reflect tissue perfusion and improve resuscitation. In addition to these markers, the prognostic values of fluid balance, lactate, and lactate clearance on outcomes were separately evaluated. The study also combined the microcirculation and macrocirculation markers at three different time intervals to evaluate their cumulative effect on predicting the consequences of septic shock.

2 Methods

2.1 Study Design and Setting

In this prospective, single-center observational study, adult patients with septic shock admitted to the intensive care unit (ICU) at Shohada Hospital in Tabriz, Iran, between December 2020 and September 2021, were included. This study was conducted to compare the predictive ability of the macrocirculation and microcirculation markers on outcomes of patients with septic shock. The protocol study was reviewed and approved by Research Ethics Committees of Islamic Azad University-Tabriz Branch (IR.IAU.TABRIZ.REC.1400.044), in accordance with the Declaration of Helsinki of the World Medical Association [29]. Written informed consent was obtained from the patients or from their legally accepted representatives. This observational study was conducted and reported in accordance with the recommendations of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [30].

2.2 Participants

All consecutive adult patients with septic shock admitted at ICU subjected were considered as eligible for this study. Septic shock was diagnosed at ICU admission according to the Sepsis-3 Consensus Conference [14]. It was defined as suspected or confirmed infection by a serum lactate > 2 mmol/liter and requirements of norepinephrine (NE) to maintain a MAP ≥ 65 mmHg after an intravenous fluid load of at least 20 ml/kg over 60 min [14]. Patients in whom CRT could not be evaluated (Raynaud syndrome, severe hypothermia), pregnant patients, patients with active bleeding, patients with liver cirrhosis, patients with severe acute respiratory distress syndrome (ARDS), patients who required a peremptory surgical procedure during the first 6 h after potential inclusion, or had a Do-Not-Resuscitate (DNR) order, were excluded from the study.

2.3 Management of Patients

All participants with septic shock were treated according to the standard protocol recommended by the Surviving Sepsis Campaign (SSC) guidelines for the first 3 h includes obtaining blood culture before antibiotics, obtaining lactate level, administering broad-spectrum antibiotics, administering 30 mL/kg of crystalloid fluid in 2 h for hypotension (defined as mean arterial pressure (MAP) < 65) or lactate (> 4), and standardized assessment of the circulation including serum lactate levels before and after this initial FR [17]. After an initial fluid bolus, a fluid challenge technique was implemented as long as hemodynamic improvement was witnessed. Norepinephrine up to a maximum dose of 1.5 μg/Kg/min was started as the first choice of vasopressor to maintain mean arterial pressure (MAP) > 65 mmHg. If a second vasopressor drug was needed, vasopressin at a dose of 0.03 IU/min was added to the regimen.

2.4 Data Collection

Patient data collected at baseline (0 h) included demographic data (age and gender), comorbidities such as congestive heart failure (CHF), cerebral vascular accident (CVA), diabetes mellitus (DM]), end-stage renal disease (ESRD), hypertension (HTN), and ischemic heart disease (IHD), as well as severity of illness assessed by the acute physiology and chronic health evaluation (APACHE IV) [31], and sequential organ failure assessment (SOFA) scores [32]. Macrocirculation and organ perfusion were assessed at time zero (0 h) and at 6 and 24 h (6 h and 24 h) after ICU admission. Macrocirculation was evaluated using heart rate (HR), mean arterial pressure (MAP), and central venous pressure (CVP), while microcirculatory dysfunction and organ perfusion were assessed through capillary refill time (CRT), peripheral perfusion index (PPI), and mottling score. Fluid balance, serum lactate levels, and lactate clearance levels were also assessed at 6 h and 24 h as independent factors for all participants. The study spanned 24 h, with markers recorded at 0 h, 6 h, and 24 h for all patients. After this, attending intensivists continued treating patients according to standard protocol care, and patients were followed until ICU discharge.

2.5 Micro/Macro Circulation Markers

Heart rate was monitored by electrocardiography and mean arterial pressure was measured through non-invasive blood pressure technique. HR, MAP, and CVP were recorded at baseline (0 h), 6 h, and 24 h. Normal range was defined for MAP greater than 65 (mmHg), CVP between 8 and 12 (mmHg), and HR for adults from 60 to 100 beats per minute (bpm).

CVP monitoring is prescribed every 3 h by the medical staff. After checking the absence of spontaneous breathing of the patient on the screen of the ventilator, CVP was carefully measured by the physician or by a trained nurse. Measurements in patients in whom a cardiac arrhythmia occurred were not performed or excluded. The zero reference was carefully checked and calibrated as required. The pressure line was connected to the monitoring system. The research staff (physician or research nurse) froze the screen allowing the measurement of pressure at end expiratory time at the base of the “c” wave.

Capillary refill time (CRT) was measured by applying firm pressure to the distal phalanx of the index finger for 10 s. The pressure applied was just enough to remove the blood at the tip of the physician’s nail, illustrated by the appearance of a thin white distal crescent (blanching) under the nail. The time for the return of the normal skin color will be registered with a chronometer, and > 3 s is defined as abnormal. During the prospective observational study, CRT was measured three times (0 h, 6 h, and 24 h), and the mean value ± standard division was recorded.

PPI was derived from the photoelectric plethysmographic signal of pulse oximetry which reflects changes in peripheral perfusion that can be measured continuously and noninvasively. A PPI value < 1.4% indicates the presence of poor peripheral perfusion in critically ill patients.

Mottling score was defined as patchy skin discoloration, is a common sign of cutaneous hypoperfusion Blood flow reduction may be due to local vasoconstriction and endothelial dysfunction [25, 33]. The mottling score provided a semi-quantitative evaluation of mottling based on skin area extension on knee: Score 0 no mottling, score 1 small mottling area (coin size) localized to the center of the knee, score 2 mottling area that does not exceed the superior edge of the knee cap, score 3 mottling area that does not exceed the middle thigh, score 4 mottling area that does not exceed the fold of the groin, and score 5 severe mottling that extends beyond the groin.

Fluid balance was calculated as follows: total fluid input minus total fluid output within the first 72 h of ICU stay. As fluid accumulation during 72 h is an independent marker for mortality in septic patients we measured fluid balance at 72 h after initiation of initial resuscitation. Lactate and lactate clearance levels outcomes: Serum was sampled at baseline and after 6 h and 24 h of resuscitation from arterial. A normal serum lactate value is defined as less than 2 mmol/l. Lactate will be assessed with the techniques, including arterial serum levels point-of-care or artery blood gas analysis at the central laboratory. Moreover, we calculated lactate clearance using the serum lactate level at 6 h and 24 h after admission using the following formula: lactate clearance = (lactate baseline − lactate at 6 h or 24 h)/lactate baseline [34].

2.6 Outcomes

Various outcomes were recorded for all participants, including ICU length of stay (LOS), the need for renal replacement therapy (RRT), the need for and number of vasopressors, the duration of mechanical ventilator (MV) use, and the mortality rate. Additionally, we established a binary outcome based on the median of quantitative variables and, for qualitative variables, based on a yes or no classification. This binary outcome encompassed ICU LOS (≥ 13 days vs. < 13 days), MV duration (≥ 10 days vs. < 10 days), the need for renal replacement therapy (yes vs. no), the number of vasopressors administered (1 vs. > 1), and ICU mortality (yes vs. no).

2.7 Statistical Analysis

All quantitative variables were tested for normal distribution with Kolmogorov–Smirnov test. Patient characteristics are reported as mean ± standard deviation (SD), median (IQR) for non-normal distributions, and percentages as appropriate. Changes of macrocirculation and microcirculation markers in participants according to time trends (baseline, 6 h and 24 h) were assessed based on two-way analysis of variance with repeated measures (RMANOVA), adjusted and non-adjusted models. Adjusted RMANOVA model was done according to the baseline characteristics, including age, gender, comorbidities, and APACHE IV and SOFA scores. The results of the mottling score were reported as median (IQR), and P value was calculated based on the Friedman test. The effect of patients’ characteristics, macrocirculation and microcirculation markers on outcomes (ICU length of stay, need for renal replacement therapy (RRT), need and number of vasopressors, duration of MV, and mortality rate) were determined by univariate and multivariate logistic regression, and the results were expressed as odds ratio (OR) with 95% confidence interval (CI). Receiver operating characteristic curve (ROC) was generated, and area under the curve (AUC) figures were calculated alongside sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR−), for each macrocirculation and microcirculation markers at baseline, 6 h, and 24 h. In addition, we combined the microcirculation and macrocirculation markers separately in three different time intervals to create new markers to predict outcomes using binary logistic regression to get the probability and then run a ROC curve using the probability as the test markers, and AUCs were compared using the DeLong test. According to the general guidelines for the discriminative power of a test based on ROC, AUC between (0.9–1.0), (0.8–0.9), (0.7–0.8), and (0.6–0.7) was considered as excellent, good, fair, and poor, respectively. Statistical analysis was carried out using SPSS software (ver.21) (SPSS Inc. IL, Chicago, USA) and MedCalc (https://www.medcalc.org/calc/diagnostic_test.php). In all analyses, P values less than 0.05 were considered significant.

3 Results

3.1 Baseline Characteristics and Clinical Outcomes of Participants

Baseline characteristics and clinical outcomes of the patients are shown in Table 1. One hundred patients with septic shock, including 55 men and 45 women, were enrolled in this study. The median (IQR) age, APACHE IV and SOFA scores of the patients were 66 (59–70), 27 (24–30) and 14 (12–15), respectively. All participants used vasopressors and underwent MV. The most common comorbidities in the patients were HTN (26.5%) and DM (25%). In terms of outcomes, the mean ± SD of ICU LOS and MV duration of the patients were 13.5 ± 2.3 and 10.8 ± 2.5 days, respectively. Seventy percent of the patients need only one vasopressor and 27% of the patients’ needs RRT. The incidence of mortality was 34%. In terms of multivariate analysis, the male gender was associated with an increased use of more than one vasopressor (OR: 2.858, 95% CI: 1.075–7.599, P = 0.035) (Supplementary File, Table S1).

Table 1 Baseline characteristics and clinical outcomes of patients with septic shock
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3.2 Time Trend Changes of Markers

The time trend of macrocirculation, microcirculation and independent markers are presented in Table 2. According to the results, the trend changes of all markers based on the time effect were significant (P < 0.05). Parameters including hemodynamic (HR, MAP, and CVP), PPI, fluid balance and clearance lactate significantly increased after 6 h and 24 h of resuscitation. However, serum lactate concentration and CRT significantly decreased after 6 h and 24 h of resuscitation (P < 0.001).

Table 2 Evaluation markers in patients with septic shock according to time trends
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3.3 Logistic Regression Analysis

Univariate and multivariate logistic regression analysis to determine the effect of microcirculation markers and independent factors (fluid balance, lactate and clearance lactate) on outcomes are presented in Tables 3 and 4. In multivariate analysis, the OR of mortality significantly increased with CRT at 6 h (OR: 17.482, 95% CI: 1.278–23.185, P = 0.032), and serum lactate level at baseline (OR: 3.392, 95% CI: 1.145–10.052, P = 0.032). However, PPI at baseline (OR: 0.027, 95% CI: 0.003–0.233, P = 0.001) and at 6 h (OR: 0.008, 95% CI: 0.001–0.186, P = 0.003) were decreased the risk of mortality. Mottling score was associated with an increased risk of RRT (OR: 3.709, 95% CI: 1.182–11.634, P = 0.025). CRT at baseline and at 24 h were associated with an increased risk of using more than one vasopressor (OR: 6.506, 95% CI: 2.226–9.117, P = 0.010) and (OR: 1.075, 95% CI: 0.007–2.844, P = 0.036), respectively. PPI at 6 h (OR: 0.005, 95% CI: 0.001–0.187, P = 0.004) was decreased the risk of prolonged MV duration (> 10 days). The results of univariate and multivariate logistic regression analysis to determine the effect of macrocirculation markers on outcomes are presented in Supplementary file, Table S2.

Table 3 Univariate and multivariate logistic regression analysis to determine the effect of microcirculation markers on outcomes
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Table 4 Univariate and multivariate logistic regression analysis to determine the effect of fluid balance, serum lactate level and clearance lactate on outcomes
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3.4 Predicting Outcomes by Markers

The AUCs for the macrocirculation and microcirculation markers for predicting mortality ranged from 0.517 to 0.770 and 0.695 to 0.993, respectively. Best performing predictive value for mortality in the macrocirculation markers was related to the CVP at baseline with (AUC: 0.770, 95% CI: 0.676–0.849, P < 0.001), and the best cut-off value (> 13) had a value sensitivity 61.76%, specificity 90.91%, (LR+) 6.79, (LR−) 0.42, PPV 77.8%, NPV 82.2%, and 65% of accuracy. All microcirculation markers had significantly excellent predictive value for mortality (AUC between 0.837 and 0.993), except CRT at baseline with (AUC: 0.695, 95% CI: 0.594–0.783, P < 0.001). Best performing predictive value for mortality in the microcirculation markers was related to the PPI at 24 h with (AUC: 0.993, 95% CI: 0.983–1.000, P < 0.001), and the best cut-off value (< 1.55) had a value sensitivity 94.1%, specificity 93.9%, (LR+) 15.53, (LR−) 0.06, PPV 88.89%, NPV 96.88%, and 65% of accuracy. The microcirculation markers had a better predictive accuracy value for mortality in patients with septic shock than macrocirculation markers. Nevertheless, most markers in both of macrocirculation and microcirculation had poor predictive value for the other outcomes with an AUC between 0.408 and 0.705. In macrocirculation markers, MAP (at baseline) for ICU length of stay, and HR (at 24 h), MAP (at 6 h) for MV duration had AUC values significantly greater than 0.6. Results for macrocirculation and microcirculation markers with significant AUC values for other outcomes (RRT, vasopressors, ICU length of stay, and MV duration) are shown in Tables 5 and 6.

Table 5 Performance of macrocirculation markers in predicting outcomes
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Table 6 Performance of microcirculation markers in predicting outcomes
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Table 7 shows the predictive performance of fluid balance, lactate and clearance lactate for septic shock outcomes. The AUCs for these markers for predicting mortality ranged from 0.714 to 0.984, respectively. Best performing predictive value for mortality in these markers was related to the lactate at 24 h with (AUC: 0.984, 95% CI: 0.966–1.000, P < 0.001), and the best cut-off value (> 3.35) had a value sensitivity 91.2%, specificity 96.9%, (LR+) 30.09, (LR−) 0.09, PPV 93.94%, NPV 93.94%, and 95% of accuracy. However, lower predictive value for mortality in these markers was related to the fluid balance at 24 h with (AUC: 0.714, 95% CI: 0.615–0.800, P < 0.001), and the best cut-off value (≤ 3600) had a value sensitivity 88.24%, specificity 66.67%, (LR+) 2.65, (LR−) 0.18, PPV 57.7%, NPV 91.7%, and 72% of accuracy (The ROC curves related to this factors for predictive mortality are presented in the Supplementary file, Figure S1).

Table 7 Performance of fluid balance, serum lactate level and clearance lactate on outcomes in predicting outcomes
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3.5 Cumulative Effect of Markers

To have a cumulative effect of markers, we conducted a logistic regression and then used the probability for creating new variables from combined the microcirculation and macrocirculation markers separately at three different time intervals to predict the consequences of septic shock. The cumulative effect of markers on outcomes is presented in Table 8. In combined macrocirculation markers at baseline to predict mortality, the AUC was 0.837 (95% CI: 0.749–0.903, P < 0.001) and the used cutoff value had a value of sensitivity 61.7%, specificity 89.4%, PPV 75%, NPV 81.9%, (LR+) 5.82, (LR−) 0.43 and 0.511 of Yuden index. In combined macrocirculation markers at 6 h and 24 h to predict mortality, the AUC was 0.726 (95% CI: 0.628–0.810, P < 0.001) and 0.652 (95% CI: 0.551–0.745, P = 0.004). Best performing predictive value for mortality in the combined microcirculation markers was related to the combined marker at baseline with (AUC: 0.962, 95% CI: 0.904–0.990, P < 0.001), and the used cutoff value had a value of sensitivity 91.18%, specificity 90.91%, PPV 83.8%, NPV 95.2%, (LR+) 10.03, (LR−) 0.097 and 0.820 of Yuden index. In combined microcirculation markers at 6 h to predict mortality, the AUCs were 0.947 (95%CI: 0.883–0.982, P < 0.001) and 0.871 (95%CI: 0.789–0.930, P < 0.001), with 97.06% and 100% of sensitivity and 90.91% and 74.245 of specificity, respectively.

Table 8 Binary logistic regression model based on combination of macrocirculation/microcirculation markers to predicting outcomes
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3.6 Compares of AUCs

Comparison of AUCs was performed between individual macro and microcirculation markers and combined markers to predict mortality using the DeLong test (Fig. 1). The combined macrocirculation markers at baseline were found to be comparable as predictors of mortality with all single macrocirculation markers at baseline, including HR (0.837 vs. 0.517, P < 0.0001), MAP (0.837 vs. 0.742, P = 0.0193) and CVP (0.837 vs. 0.770, P = 0.0449) (Fig. 1A). The cumulative effect of macrocirculation marker at 6 h was also comparable as a predictor of mortality with HR (AUC: 0.726 vs. 0.615, P = 0.0433) (Fig. 1B). However, there was no significant difference between the AUCs of the combined marker and the macrocirculation markers at 24 h for predicting mortality (P > 0.05) (Fig. 1C).

Fig. 1
figure 1

Comparison of ROC curves of single markers with combine marker to predict mortality A–C macrocirculation markers vs. combined marker (at baseline, 6 h and 24 h, respectively), D–F macrocirculation markers vs. combined marker (at baseline, 6 h and 24 h, respectively), and G and H between fluid balance, lactate and clearance lactate at 6 and 24 h, respectively

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The combined microcirculation markers at baseline were found to be comparable as predictors of mortality with both single microcirculation markers, including CRT (0.962 vs. 0.695, P < 0.001) and PPI (0.962 vs.0.837, P = 0.008) (Fig. 1D). There was no significant difference between the AUCs of the combined marker and the microcirculation markers at 6 h for predicting mortality (P > 0.05) (Fig. 1E). However, the AUC of the combined microcirculation marker was significantly lower at 24 h than that of the CRT (0.871 vs. 0.990, P < 0.0001) and PPI (0.871 vs. 0.993, P < 0.0001) markers for predicting mortality (Fig. 1F).

Among the fluid balance, lactate and clearance lactate at 6 h, the AUC of lactate was comparable as predictor of mortality compared to fluid balance (0.897 vs. 0.738, P = 0.0028) and clearance lactate (0.897 vs. 0.799, P = 0.0119) (Fig. 1G). However, when comparing these factors at 24 h, the AUC of fluid balance was significantly lower than lactate (0.714 vs. 0.984, P < 0.0001) and clearance lactate (0.714 vs. 0.961, P < 0.0001) markers for predicting mortality (Fig. 1H). The rest of the results, including ROC curves and pairwise comparisons between markers for other outcomes, are presented in the Supplementary file, Figure S2 to S31.

4 Discussion

This prospective observational study aimed to compare the predictive abilities of of macrocirculatory markers (HR, MAP and CVP), microcirculatory markers (CRT, PPI and molting score) and fluid balance, lactate and clearance lactate on the outcomes (mortality, RRT, vasopressors, ICU LOS and MV duration) of patients with septic shock during initial resuscitation. Additionally, to assess the cumulative effect of the markers, we combined the microcirculation and macrocirculation markers separately at three different time intervals to predict the consequences of septic shock. Our findings revealed that the accuracy of the microcirculation markers in predicting outcomes was comparable and higher than that of the macrocirculation markers. The three most important predictors of mortality identified in our study were PPI with an AUC of 0.993, CRT with an AUC of 0.990, and lactate with an AUC of 0.984 at 24 h.

Among the microcirculation markers we evaluated, PPI emerged as the most valuable prognostic indicator for mortality in adult patients with septic shock. PPI serves as a reflection of inadequate perfusion in critically ill patients [21] and, in comparison to blood lactate testing, offers real-time and non-invasive monitoring [35]. The plotted ROC curves of PPI and CRT at baseline for predicting mortality demonstrated the AUCs of 0.837 and 0.695, respectively. These findings indicate that PPI can predict mortality earlier with improved sensitivity and specificity. During the early stages of hypoperfusion, peripheral blood vessels constrict to maintain sufficient blood flow to the heart [36, 37]. At this point, macro vital signs such as HR and blood pressure (BP) appear normal. As a result of vasoconstriction reducing blood flow in a specific area, PPI, an indicator of regional perfusion, decreases. This highlights the superiority of PPI over other micro parameters, such as lactate, in alerting physicians to hypoperfusion. However, the use of PPI is limited by its susceptibility to external factors such as low temperature, vascular diseases, and patient positioning [38, 39].

The study found that both CRT and lactate concentration were equally accurate in predicting mortality, with excellent predictive value. These findings are consistent with a randomized controlled trial by Castro et al. [40], which showed that CRT-targeted fluid resuscitation was comparable to lactate-targeted fluid resuscitation in terms of fluid administration and balances. Another study by Kataria et al. [41], found that elevated CRT at 3 h and 6 h can be a valuable additional aid for prognostication of septic shock patients, while lactate levels at 6 h had a better predictive value in predicting 28-day mortality than other parameters. A pilot study [42] indicated a potential link between CRT and microcirculatory dysfunction, a key factor in septic shock mortality, by showing that abnormal CRT values during early septic shock resuscitation are associated with impaired skin blood flow and abnormal skin microvascular reactivity. These findings suggest that both CRT and lactate have high accuracy in providing prognostic information in septic shock as a predictor of mortality. However, CRT measurement could be a better predictor than blood lactate concentration due to its simplicity, non-invasive alternative, and suitability for resource-limited settings. Further research is needed to confirm and generalize these results.

CRT assessment is susceptible to various factors that can significantly influence results, such as ambient temperature, skin temperature, core temperature, age, ambient light conditions, time of pressure, level, and site of pressure application [43]. Some of these conditions can be controlled, and measurements can be standardized to reduce ambient-related and technical variability [44]. Van Genderen et al. [35] investigated the reliability of observers in CRT assessments among different healthcare workers and demonstrated good overall consensus. Another study revealed a strong correlation with objective variables of peripheral perfusion [43]. Ait-Oufella et al. [24] showed that CRTs were highly reproducible in a prospective cohort of patients with septic shock and exhibited excellent interrater concordance. However, to optimize CRT reproducibility, effective measures include education, standardization, and minimizing the impact of environmental factors.

Our observational study shows that fluid balance had a fair predictive value for mortality at 6 h and 24 h (AUC: 0.738 and 0.714, respectively). These results align with previous studies, which demonstrated that higher positive fluid balance in the first two days of resuscitation was linked to increased mortality risk in septic shock patients [12, 45]. Additionally, our study revealed good predictive accuracy for serum lactate and lactate clearance for mortality and number of vasopressors and also a poor significant predictive value for RRT. Similarly, a retrospective study by Ryoo et al. [46] indicated that lactate and lactate clearance levels at 6 h were effective prognostic tools for septic shock patients treated with protocol-driven resuscitation bundle therapy. Mahmoodpoor et al. [47], showed that serial measurements of serum lactate, with emphasis on its concentration at 24 h after admission, were the most predictive of short-term mortality in the ICU. Furthermore, Marty et al. [48] reported that lactate clearance was the best parameter associated with the 28-day mortality rate in septic patients during the first 24 h in the ICU. Another study demonstrated that combining lactate levels and its clearance is a reliable predictor of mortality in sepsis [49]. Using lactate as a potential resuscitation marker is controversial as it is a non-specific sign of hypoperfusion that also shows slow recovery kinetics. In fact, drop in levels of lactate even after appropriate resuscitation may show a biphasic curve. First, a rapid initial drop in parallel to other flow-sensitive parameters. Second, a later slower decrease, probably representing residual stress-related hyperlactatemia and metabolic clearance problems. Therefore, aiming at lactate optimization can lead to over-resuscitation and fluid overload, which has been associated with higher mortality [18, 19].

Our study found that the mottling score was associated with an increased risk of mortality and RRT in septic patients, consistent with previous studies [27, 28]. However, the clinical evaluation of mottling can be influenced by factors such as vasopressor dosage [25]. Combining macrocirculation and microcirculation markers resulted in a greater AUC and higher accuracy, SN, SP, LR+, PPV, and NPV, and lower LR− values compared to using each marker alone. This suggests that the combination of markers is the most reliable predictor of septic shock outcome, with microcirculatory variables at 24 h being the most important. Using the cutoffs identified by ROC analyses in a multivariable analysis, adjusted for appropriate confounders, can help identify prognostic value.

Our study has several limitations. It is a single-center study, and results need to be confirmed in a larger population. Our participants were critically ill patients with various pre-existing comorbidities which acute dysfunction precludes a correct interpretation of results. We excluded patients with advanced liver dysfunction and ARDS but cannot rule out some degree of subclinical dysfunction. CRT assessment might be subjected to inter-observer variability, but we used a standardized technique that decreases the likelihood of bias. Nevertheless, while the size of this preliminary study was not very large, it was sufficient to highlight significant results.

5 Conclusion

In conclusion, microcirculation markers to predict mortality was superior to macrocirculation markers. The three most important predictors of mortality identified in our study were PPI, CRT and serum lactate at 24 h. An important observation of the present study is the combined models for both macrocirculation and microcirculation markers at baseline which had a greater AUCs with higher sensitivity and specificity than the marker alone to predict morbidity and mortality in patients with septic shock.