Severe hyperlactatemia in unselected surgical patients. Retrospective analysis of prognostic outcome factors.

Severe hyperlactatemia in unselected surgical patients. Retrospective analysis of prognostic outcome factors. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Severe hyperlactatemia in unselected surgical patients. Retrospective analysis of prognostic outcome factors. Julia Spiegelberg, Ann-Kathrin Lederer, Sibylla Claus, Mira Runkel, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1526639/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract BACKGROUND Etiology of hyperlactatemia in ICU patients is heterogeneous - septic, cardiogenic or hemorrhagic shock seem to be predominant reasons. Multiple studies show hyperlactatemia as an independent predictor for ICU mortality. Only limited data exists about the etiology of hyperlactatemia and lactate clearance and their influence on mortality. The goal of this single-center retrospective study, was to evaluate the effect of severe hyperlactatemia and reduced lactate clearance rate on the outcome of unselected ICU surgical patients. METHODS Overall, 239 surgical patients with severe hyperlactatemia (>10 mmol/L) who were treated in the surgical ICU at the University Medical Center Freiburg between June 2011 and August 2017, were included in this study. The cause of the hyperlactatemia as well as the postoperative course and the patient morbidity and mortality were retrospectively analyzed. Lactate clearance was calculated by comparing lactate level 12h after first measurement of >10mmol/L. RESULTS The overall mortality rate in our cohort was 82.4%. Severe hyperlactatemia was associated with death in the ICU (p<0.001). The main etiologic factor was sepsis (51.9%), followed by mesenteric ischemia (15.1%), hemorrhagic shock (13.8%) and liver failure (9.6%). Higher lactate levels at ICU admission were associated with increased mortality (p< 0.001). Lactate clearance after 12h was found to predict ICU mortality (ANOVA p<0.001) with an overall clearance of under 50% within 12h. The median percentage of clearance was 60.3% within 12h for the survivor and 29.1% for the non-survivor group (p < 0.001). CONCLUSION Lactate levels appropriately reflect disease severity and are associated with short-term mortality in critically ill patients. The main etiologic factor for surgical patients is sepsis. When elevated lactate levels persist more than 12h, survival chances are low and the benefit of continued maximum therapy should be evaluated. lactate lactic acidosis sepsis shock outcome surgical therapy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Hyperlactatemia is defined as lactate level > 2 mmol/L and is commonly seen in critically ill patients [ 1 ]. Hyperlactatemia results from the accumulation of lactate and protons in human fluids and tissues and is often associated with poor clinical outcomes. When aerobic glycolysis is impaired, cells increase their glucose utilization by anaerobic glycolysis. This process is less efficient in generating triphosphates and additionally produces pyruvate. This undergoes redox-coupled interconversion catalyzed by the enzyme lactate dehydrogenase, ultimately resulting in lactate [ 2 ]. Hyperlactatemia occurs when lactate production outruns lactate consumption. Additionally, protons equivalent to the number of excess lactate ions are synthetized regardless of the prevailing acid-base status. Approximately 70% of lactate clearance occurs in the liver. Coexisting acidemia contributes to decreased lactate clearance by the liver. Therefore the severity of acidemia seems to be a better predictor of cellular dysfunction and clinical outcomes than hyperlactatemia [ 3 ]. In general, hyperlactatemia is caused by tissue hypoxemia due to an imbalance between oxygen supply and demand. This tissue hypoxemia is attributed by impairment of oxygen supply or different forms of shock such as hypovolemic, hemorrhagic, cardiogenic or obstructive shock. Nevertheless, hyperlactatemia can also occur under aerobic conditions. During a state of shock, lactate production is dependent on the stimulation of β 2− muscle receptors, thus largely independent of tissue hypoxia [ 4 ]. Lactate levels and their trend may be reliable markers of illness severity and mortality [ 5 , 6 ]. Only limited data exists about the etiology of lactatemia in sepsis. Wong et al. included lactate in a multibiomarker-based outcome risk model for patients with septic shock [ 7 ]. Opdam et al. reported the lungs to be a major source of lactate for patients in septic shock, which is comparable to animal models [ 8 ]. Lactate and pyruvate concentrations are measured higher in muscle than in arteries during septic shock [ 9 ]. The metabolism of lactate in critically ill patients is described as being associated with cellular inflammatory response [ 10 ]. Hyperlactatemia is considered as a clinical marker of critical illness severity. The association between elevated lactate levels and poor outcome of ICU patients is reported in multiple studies [ 11 ]. Effective lactate clearance seems to be associated with improved outcome [ 12 ]. Recently, Haas et al. retrospectively analyzed patients with plasma lactate levels > 10 mmol/L [ 13 ], and found an overall mortality of 78.2% in these patients, whereas mortality rate of all patients in ICU were only 9.8%. The main etiology for severe hyperlactatemia was septic shock (34.0%), cardiogenic shock (19.3%) and cardiopulmonary resuscitation (13.8%) [ 13 ]. Nevertheless, the etiology of hyperlactatemia and lactate clearance rates showed heterogeneity emphasizing the necessity of further research. We therefore analyzed severe hyperlactatemia in unselected surgical patients from the surgical intensive care unit of the University Medical Center Freiburg and evaluated prognostic outcome factors. We hypothesized that severe hyperlactatemia (> 10 mmol/L) and a reduced lactate clearance are associated with a poor outcome of surgical patients. Methods This cohort study retrospectively evaluated the outcome of 239 consecutive surgical patients with serum lactate levels > 10 mmol/L, who were treated at the Medical Center of the University Freiburg between June 2011 and August 2017. The study was approved by the medical Ethics Committee of the University of Freiburg (EK-FR 372/17). Patients were eligible for inclusion if serum lactate concentration > 10mmol/L was documented in a venous or arterial blood sample on at least one occasion. Only patients being treated in surgical ICU were considered. All patients underwent surgery or received another therapeutic intervention such as endoscopic procedures (gastroscopic clipping, endoscopic retrograde cholangiography), therapeutic interventional angiography or comparable endovascular interventions. No pre-analytical sample size calculation was performed. Electronic data acquisition of blood gas analysis results in our medical department exists since June 2011. Therefore, due to feasibility reasons, a fixed period between June 2011 and August 2017 was chosen during which all above-mentioned surgical patients with severe hyperlactatemia were included to data analysis. Lactate concentrations were measured during ICU stay in every patient and recorded by an automated data management system. Blood samples were collected in heparinized blood gas syringes and measured with a blood gas analyzer (ABL800 FLEX © Radiometer; Radiometer, Copenhagen, Denmark). All laboratory maintenance was reviewed regularly and tested according to national German laws and manufacturer’s specification. Clinical data and patient demographics were extracted from our patient data management system (KIS Freiburg PROMetheus). ICU admission date, date of death (in or outside hospital), cause of hyperlactatemia, sex, age, organic failure / replacement therapies, operations or interventions, hospital admission lactate level as well as peak lactate level and 12h lactate level were defined as target variables. Patients were grouped into different categories related to the etiology of hyperlactatemia [ 13 ]: (1) sepsis (including septic shock), (2) cardiogenic shock, (3) postoperative cardiosurgical patients, (4) cardiopulmonary resuscitation, (5) hemorrhagic shock, (6) liver failure, (7) mesenteric ischemia, (8) seizure, (9) other reasons not captured by the previous categories. Due to retrospective design time trends, selection bias and confounder due to incomplete data cannot be avoided. SPSS 27 for Windows™ was used for statistical analysis (SPSS, Chicago, IL, USA). Categorical variables are presented as frequency and percentage of level. Quantitative variables are shown as the mean ± standard deviation (SD) of distribution. Lactate clearance was calculated by comparing blood lactate concentration 12h after first measurement of lactate > 10mmol/L. Categorical variables were put in absolute and relative frequencies; differences were evaluated by Chi-Square or Fisher’s exact test as appropriate. Quantitative values were expressed as medians with range and differences were measured using the Mann–Whitney-U test. Multivariate analysis was performed through forward logistic regression model, with relative risk and a 95% confidence interval. The Kaplan–Meier method was used to evaluate survival, with a log-rank test for the comparison of subgroups. We used the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve to prognosticate the predictive power of different factors predicting ICU mortality. Youden Index was used to find the optimal cut-off value, which leads to the highest sensitivity and specificity. A p-value < 0.05 was considered statistically significant. Results Between June 2011 and August 2017, a total of 14.973 patients were treated in the surgical intensive care unit at the University Medical Center Freiburg. Of these, 242 patients with lactate level > 10mmol/L during ICU stay were eligible for study inclusion. Three patients had to be excluded due to implausibility of the recorded lactate measurements. Therefore, data from 239 patients were available for retrospective evaluation. Of 239 included patients, 18 (7.5%) were admitted after elective surgery or intervention and 221 (92.5%) were emergency ICU admissions due to variable causes. We summarized demographic data as well as maximum lactate level, mean hospitalization days, ICU days, ventilation percentage, renal replacement therapy and etiology of hyperlactatemia in Table 1. In this cohort mortality was 82.4% (n = 197). There was a significant difference in age between ‘survivors’ and ‘non-survivors’ (64 years vs. 68 years, respectively p < 0.001). There was no statistical difference in gender distribution across the two groups. Non-survivors were more likely to be ventilated (p = 0.004), however the need for renal replacement therapy showed no significant difference between the two groups. (p = 0.340) In the survivor group the mean length of ICU stay was 14.4 ± 13.4 days compared to 9.2 ± 13.7 days for the non-survivor group. Peak lactate level was significantly higher in the non-survivor group (17.8 ± 5.8mmol/L) compared to the survivor group (13.9 ± 4.4mmol/L, p = 0.001). Table 1: Demographic data, complications and lactate etiology Parameter Total Survivors Non-Survivors p a n = 239 n = 42 (17.6%) n = 197 (82.4%) Mean age (years) ± SD 67.6 ± 12.3 64.1 ± 13.5 68.3 ± 12.0 < 0.001 * Gender Male Female 144 (60.3%) 95 (39.7%) 23 (9.6%) 19 (7.9%) 121 (50.6%) 76 (31.8%) 0.264 Mean duration of ICU stay (days) 10.1 ± 13.8 14.4 ± 13.4 9.2 ± 13.7 0.025 * Hospitalization days (days) 20.6 ± 23.7 37.2 ± 25.8 17.0 ± 21.7 0.000 * * Ventilation (n (percentage)) 208 (87.0%) 30 (12.6%) 178 (74.5%) 0.004 Renal replacement (n(percentage) 72 (30.1%) 11 (4.6%) 61 (25.5%) 0.340 * Maximum lactate (mmol/L) 17.0 ± 5.8 13.9 ± 4.4 17.8 ± 5.8 0.001 Lactate etiology * Sepsis 124 (51.9%) 14 (11.3%) 110 (88.7%) Mesenteric ischemia Hemorrhagic shock 36 (15.1%) 33 (13.8%) 5 (13.9%) 8 (24.2%) 31 (86.1%) 25 (75.8%) Liver failure 23 (9.6%) 7 (30.4%) 16 (69.6%) Cardiopulmonary resuscitation Cardiogenic shock 12 (5.0%) 6 (2.5%) 2 (16.7%) 2 (33.3%) 10 (83.3%) 4 (66.7%) Seizure 2 (0.8%) 1 (50%) 1 (50%) Other reasons 3 (1.3%) 3 (100%) 0 (0%) a Mann-Whitney-U-Test for lactate etiology/ Fisher‘s exact Test for other parameters Etiology and course of hyperlactatemia The distribution of patients across different groups of etiology of hyperlactatemia is shown in Fig. 1 . In 24 cases, the etiology was considered to be multifactorial and the leading cause was determined according to patients’ medical history and current consecutive symptom order. Mortality rate in this cohort was 82.4% (n = 197). In numerous cases a precise determination of the cause of death was not possible. However, given the frequency of sepsis and septic shock (51.9%), septic multiorgan failure is likely to be the leading cause. Other causes of death included circulatory failure, ARDS and therapy limitation due to, for example, irreversible complete bowel ischemia. ICU mortality in the subgroups was 89% due to sepsis, 86% due to mesenteric ischemia, 76% due to hemorrhagic shock, 70% due to liver failure, 83% due to cardiopulmonary resuscitation, 67% due to cardiogenic shock, 50% due to seizure and 0% due to other reasons. For 72 patients requiring renal replacement therapy, ICU mortality was 85%. Mortality for patients with persisting hyperlactatemia for > 12 hours was 87.7% (n = 192, (p < 0.001). Median lactate concentration ranged from 11.2 ± 0.8 mmol/L to 17.6 ± 6.0 mmol/L. The distribution of maximum lactate levels is shown in Fig. 2. Figure 2: Distribution of measured peak lactate concentration (mmol/L) by subgroups Mean lactate concentration was 13.9 +/- 4.4 mmol/L in the survivor group and 17.8 +/- 5.8 mmol/L in the non-survivor group. In patients with lactate concentration 10mmol/L with 7.9 +/- 1.3 days. We calculated 12.38 mmol/L as peak lactate cut-off with the highest sensitivity for prediction of mortality (Youden Index). When performing Kaplan-Maier analysis, we found blood lactate concentration at ICU admission to significantly influence overall survival (Fig. 3 ). Patients whose admission lactate concentration was already above 10 mmol/L show a significantly reduced chance of survival in the 90-day overall survival compared to patients with lactate levels < 10mmol/L, according to log rank analysis (p < 0.001). Patients with mesenteric ischemia has significantly lower overall survival compared to other subgroups (p = 0.003). Patients with sepsis and septic shock seem to have a better outcome when compared to all other subgroups (Fig. 4). Figure 4: Kaplan- Maier 90 days overall survival in patients with severe hyperlactatemia depending on different etiologic factors (log rank analysis). Lactate clearance Data of lactate clearance within 12h was available for 90 patients (40 survivors, 50 non-survivors). The median percentage of clearance (percentage of reduction after 12h compared to the first measured value of lactate above 10 mmol/L) was 60.3% within 12h for the survivor group and 29.1% for the non-survivor group (p < 0.001). There was no statistical difference of 12h lactate clearance between etiologic subgroups (p = 0.243). Calculation of ROC analysis revealed a cut-off value for 12h lactate clearance of 29.4% for the prediction of ICU mortality. Lactate clearance was significantly slower when aspartate aminotransferase (p = 0.013) as well as alanine aminotransferase were increased (p = 0.017). The mean 12 h lactate clearance in each subgroup was 37.7% ± 40.9 for sepsis, 72.6% ± 0 for cardiogenic shock 55.0 ± 50.1% for cardiopulmonary resuscitation, 43.0 ± 39.7% for hemorrhagic shock, 30.5 ± 56.6% for liver failure, 48.4 ± 24.4%, for mesenteric ischemia, 91.9 ± 4.8% for seizure, and 89.9 ± 3.5% for ‘others‘. We summarized the association between 12h lactate clearance and mortality in Fig. 5. Mortality rate for patients with negative lactate clearance (implying an increase of serum lactate level 12h after first measurement of severe hyperlactatemia) was 100%. Figure 5: Association between 12h lactate clearance and mortality. The black lines show 12h lactate clearance of 0% and the cutoff having highest specificity to predict ICU mortality regarding sensitivity and specificity (12 h lactate clearance of 29.4%). Discussion This retrospective study indicates that severe hyperlactatemia is associated with poor clinical outcome in unselected surgical patients. Our results highlight that severe hyperlactatemia is still associated with an extremely high ICU mortality. Limitations to this study are the retrospective nature as well as selection bias. Furthermore, the lack of absolute diagnostic criteria for subgroup selection can lead to over- and/or underrepresentation of subgroups. Multiple factors can lead to severe hyperlactatemia, thus making it difficult to identify a sole cause of increased lactate levels. Nevertheless, we were able to show interesting results for more than 250 patients agreeing with previously reported observations: It is well-known that hyperlactatemia is associated with an increased risk of death [ 14 – 16 ]. Almost 30 years ago, Bakker et al. reported about 48 patients suffering from septic shock, with survivors showing significantly lower levels of lactate initially and in the final phase of septic shock, compared to the control group [ 14 ]. Another retrospective study of Varpula et al. with patients in septic shock revealed similar results emphasizing the impact of lactate on mortality [ 16 ]. A few years later, Khosravani et al. confirmed the results by reporting data of more than 10 000 ICU patients. Hyperlactatemia was commonly seen in critically ill patients and predicted the risk of death [ 15 ]. Studies of critically ill medical [ 17 ] and cardiac surgical [ 18 , 19 ] showed an association between elevated lactate level, prolonged lactate clearance and mortality. Juneja et al. demonstrated that the outcome of patients with hyperlactatemia on admission is inferior, regardless of the occurrence of hypotension. Hyperlactatemia on admission can thus help us identify patients at higher risk of death so that immediate resuscitative measures can be taken to improve the overall survival. We observed sepsis as the predominant reason for severe hyperlactatemia in our cohort. This is consistent with the findings of Haas et al.[ 13 ]. Gotmarker et al. have even demonstrated that patients with isolated hyperlactatemia in the setting of sepsis had significantly reduced 90-day overall survival compared to patients with isolated sepsis induced hypotension [ 20 ]. Various guidelines, including those by „surviving sepsis campaign‘ [ 21 ] now assign lactate measurement as a screening strategy for identifying patients with suspected severe sepsis with higher risk of mortality. Interestingly, our data suggest that patients whose hyperlactatemia results from sepsis show significantly better overall survival than patients with hyperlactatemia due to mesenteric ischemia (Fig. 4). Thus, it can be concluded that despite the apparent anaerobic processes occurring in both groups, the underlying etiology and reversibility of hyperlactatemia seem to be of relevance when evaluating overall survival. Mesenteric ischemia without hyperlactemia is also associated with poor prognosis, which is also confirmed by other studies [ 22 ]. Furthermore, our results emphasize the importance of lactate clearance for the prognosis of overall survival. Patients with a lactate clearance of less than 30% within the first 12h were shown to have a reduced overall survival with an ICU mortality of 80%. The reversibility of hyperlactatemia is therefore an important risk factor. Multiple trials [ 11 – 13 , 23 ] showed a good predictive power for 12h lactate clearance in determining ICU mortality in critical ill patients. Lactate clearance is currently not part of the general recommendations for septic shock management. Our data go in line with the findings of Arnold et al. [ 24 ] and show that assessment of lactate clearance is important as a predictor of mortality, independent of central venous oxygen saturation. We suggest that serial lactate measurement may provide important information during intensive care treatment and resuscitation. Mak et al. [ 18 ] suggest that the duration of hyperlactatemia is a more important risk factor than the peak lactate concentration for cardiac surgical patients. The authors propose that persistent elevations in lactate are due to a state of ongoing hypoperfusion, leading to a significant increase in mortality risk. This is consistent with our findings regarding the correlation of reduced lactate clearance and increased mortality. Thus, an irreversible cause of hyperlactatemia and reduced hepatic and renal clearances due to multiorgan failure seem to be crucial in risk calculation. However, there are many studies for post-cardiac surgery patients regarding hyperlactatemia and lactate clearance but there is a need for prospective further studies evaluating general surgical patients. Our findings confirm the association between the timing of severe hyperlactatemia and ICU mortality. Patients, who already showed severe hyperlactatemia at ICU admission, had a significantly increased risk of mortality comparing to patients with lactate levels < 10mmol/L. This goes along with data of a European prospective study in patients with liver cirrhosis showing the significant impact of admission lactate levels on 28-day mortality [ 25 ]. Juneja et al demonstrated that hyperlactatemia is commonly evident on admission to a general medical ICU and is associated with increased need for organ support and increased ICU mortality [ 17 ]. The outcome of patients with hyperlactatemia on admission is worse, independent of the presence of hypotension. Hyperlactatemia on admission can guide in identifying patients at higher risk of mortality [ 17 ]. Regarding our results, it can be assumed that patients with severe hyperlactatemia on admission have basically not received causal therapy so far, and thus have a worse outcome than patients who develop hyperlactatemia in the ICU receiving differentiated therapy, e.g., in the context of postoperative hemorrhage or seizure. This could explain the lower overall survival and is an important finding with regard to further prognosis-adapted therapy. Lactate is strong predictor of organ failure and short-term overall survival in critically ill surgical patients. Due to the simplicity and availability in the clinical ICU setting, lactate measurements should be used as a useful and rapid tool to assess severity of disease. Conclusion Hyperlactatemia remains a life-threatening emergency status with a high mortality rate. The underlying etiology of hyperlactatemia is relevant to overall survival. Our findings match with previous studies indicating that lactate clearance predicts mortality. Nevertheless, the results clearly indicate the need for further prospective research to develop therapeutic approaches for a better management of hyperlactatemia dependent on its etiology and consequently improve outcome of affected patients. Abbreviations AUC - Area Under the Curve ROC - Receiver Operating Characteristic SD - standard deviation ANOVA - Analysis of Variance ARDS – Acute Respiratory Distress Syndrome ICU – Intensive Care Unit Declarations Institutional review board statement : The study was approved by the Medical Ethics Committee of the University of Freiburg (EK-FR 372/17). Competing Interest : All the authors have no conflict of interest related to the manuscript. Funding : No funding or grants were received for this study Availability of Data and Materials : The original anonymous dataset is available on request from the corresponding author at [email protected] Authors’ contribution: All authors (JS, AKL, SC, MR, SU, SFF, LK) contributed to the study conception and design. JS, AKL and SC performed acquisition of data. All authors (JS, AKL, SC, MR, SU, SFF, LK) performed analysis and interpretation of data. JS and AKL wrote the first draft of the manuscript. All authors (JS, AKL, SC, MR, SU, SFF, LK) commented on previous versions of the manuscript. All authors (JS, AKL, SC, MR, SU, SFF, LK) read, revised and approved the final manuscript. Consent for Publication : Not Applicable. Acknowledgement : Not Applicable. References Rishu AH, Khan R, Al-Dorzi HM, Tamim HM, Al-Qahtani S, Al-Ghamdi G, Arabi YM. Even mild hyperlactatemia is associated with increased mortality in critically ill patients. Crit Care 2013, 17, R197, doi: 10.1186/cc12891 . Kraut JA, Madias NE. Lactic acidosis. N Engl J Med. 2015;372:1078–9. doi: 10.1056/NEJMc1500327 . Lee SW, Hong YS, Park DW, Choi SH, Moon SW, Park JS, Kim JY, Baek KJ. Lactic acidosis not hyperlactatemia as a predictor of in hospital mortality in septic emergency patients. Emerg Med J. 2008;25:659–65. doi: 10.1136/emj.2007.055558 . Levy B, Desebbe O, Montemont C, Gibot S. Increased aerobic glycolysis through beta2 stimulation is a common mechanism involved in lactate formation during shock states. Shock 2008, 30 , 417–421, doi: 10.1097/SHK.0b013e318167378f . Cerovic O, Golubovic V, Spec-Marn A, Kremzar B, Vidmar G. Relationship between injury severity and lactate levels in severely injured patients. Intensive Care Med. 2003;29:1300–5. doi: 10.1007/s00134-003-1753-8 . Nichol A, Bailey M, Egi M, Pettila V, French C, Stachowski E, Reade MC, Cooper DJ, Bellomo R. Dynamic lactate indices as predictors of outcome in critically ill patients. Crit Care. 2011;15:R242. doi: 10.1186/cc10497 . Wong HR, Lindsell CJ, Pettila V, Meyer NJ, Thair SA, Karlsson S, Russell JA, Fjell CD, Boyd JH, Ruokonen E, et al. A multibiomarker-based outcome risk stratification model for adult septic shock*. Crit Care Med. 2014;42:781–9. doi: 10.1097/CCM.0000000000000106 . Opdam H, Bellomo R. Oxygen consumption and lactate release by the lung after cardiopulmonary bypass and during septic shock. Crit Care Resusc. 2000;2:181–7. Levy B, Gibot S, Franck P, Cravoisy A, Bollaert PE. Relation between muscle Na + K + ATPase activity and raised lactate concentrations in septic shock: a prospective study. Lancet. 2005;365:871–5. doi: 10.1016/S0140-6736(05)71045-X . Kellum JA, Song M, Li J. Lactic and hydrochloric acids induce different patterns of inflammatory response in LPS-stimulated RAW 264.7 cells. Am J Physiol Regul Integr Comp Physiol. 2004;286:R686–92. doi: 10.1152/ajpregu.00564.2003 . Gharipour A, Razavi R, Gharipour M, Modarres R, Nezafati P, Mirkheshti N. The incidence and outcome of severe hyperlactatemia in critically ill patients. Intern Emerg Med. 2021;16:115–23. doi: 10.1007/s11739-020-02337-9 . Gu WJ, Zhang Z, Bakker J. Early lactate clearance-guided therapy in patients with sepsis: a meta-analysis with trial sequential analysis of randomized controlled trials. Intensive Care Med. 2015;41:1862–3. doi: 10.1007/s00134-015-3955-2 . Haas SA, Lange T, Saugel B, Petzoldt M, Fuhrmann V, Metschke M, Kluge S. Severe hyperlactatemia, lactate clearance and mortality in unselected critically ill patients. Intensive Care Med. 2016;42:202–10. doi: 10.1007/s00134-015-4127-0 . Bakker J, Coffernils M, Leon M, Gris P, Vincent JL. Blood lactate levels are superior to oxygen-derived variables in predicting outcome in human septic shock. Chest. 1991;99:956–62. doi: 10.1378/chest.99.4.956 . Khosravani H, Shahpori R, Stelfox HT, Kirkpatrick AW, Laupland KB. Occurrence and adverse effect on outcome of hyperlactatemia in the critically ill. Crit Care. 2009;13:R90. doi: 10.1186/cc7918 . Varpula M, Tallgren M, Saukkonen K, Voipio-Pulkki LM, Pettila V. Hemodynamic variables related to outcome in septic shock. Intensive Care Med. 2005;31:1066–71. doi: 10.1007/s00134-005-2688-z . Juneja D, Singh O, Dang R. Admission hyperlactatemia: causes, incidence, and impact on outcome of patients admitted in a general medical intensive care unit. J Crit Care. 2011;26:316–20. doi: 10.1016/j.jcrc.2010.11.009 . Mak NT, Iqbal S, de Varennes B, Khwaja K. Outcomes of post-cardiac surgery patients with persistent hyperlactatemia in the intensive care unit: a matched cohort study. J Cardiothorac Surg. 2016;11:33. doi: 10.1186/s13019-016-0411-5 . Naik R, George G, Karuppiah S, Philip MA. Hyperlactatemia in patients undergoing adult cardiac surgery under cardiopulmonary bypass: Causative factors and its effect on surgical outcome. Ann Card Anaesth. 2016;19:668–75. doi: 10.4103/0971-9784.191579 . Gotmaker R, Peake SL, Forbes A, Bellomo R, Investigators* A Mortality is Greater in Septic Patients With Hyperlactatemia Than With Refractory Hypotension. Shock 2017, 48 , 294–300, doi: 10.1097/SHK.0000000000000861 . Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, Machado FR, McIntyre L, Ostermann M, Prescott HC, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021. Crit Care Med. 2021;49:e1063–143. doi: 10.1097/CCM.0000000000005337 . Leone M, Bechis C, Baumstarck K, Ouattara A, Collange O, Augustin P, Annane D, Arbelot C, Asehnoune K, Baldesi O, et al. Outcome of acute mesenteric ischemia in the intensive care unit: a retrospective, multicenter study of 780 cases. Intensive Care Med. 2015;41:667–76. doi: 10.1007/s00134-015-3690-8 . Falk JL, Rackow EC, Leavy J, Astiz ME, Weil MH. Delayed lactate clearance in patients surviving circulatory shock. Acute Care. 1985;11:212–5. Arnold RC, Shapiro NI, Jones AE, Schorr C, Pope J, Casner E, Parrillo JE, Dellinger RP, Trzeciak S. Emergency Medicine Shock Research Network, I. Multicenter study of early lactate clearance as a determinant of survival in patients with presumed sepsis. Shock. 2009;32:35–9. doi: 10.1097/shk.0b013e3181971d47 . Drolz A, Horvatits T, Rutter K, Landahl F, Roedl K, Meersseman P, Wilmer A, Kluwe J, Lohse AW, Kluge S, et al. Lactate Improves Prediction of Short-Term Mortality in Critically Ill Patients With Cirrhosis: A Multinational Study. Hepatology. 2019;69:258–69. doi: 10.1002/hep.30151 . Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 30 Jun, 2022 Reviewers agreed at journal 18 May, 2022 Reviewers invited by journal 18 May, 2022 Editor invited by journal 12 Apr, 2022 Editor assigned by journal 07 Apr, 2022 First submitted to journal 05 Apr, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1526639","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":106958188,"identity":"45b812cb-1f90-4cb9-835f-adbf30f53b67","order_by":0,"name":"Julia Spiegelberg","email":"","orcid":"","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Spiegelberg","suffix":""},{"id":106958189,"identity":"9402e91d-efb8-484b-bdf4-a0e4827f296b","order_by":1,"name":"Ann-Kathrin Lederer","email":"","orcid":"","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Ann-Kathrin","middleName":"","lastName":"Lederer","suffix":""},{"id":106958190,"identity":"39d635cb-4598-4b03-87c7-660a2d32634b","order_by":2,"name":"Sibylla Claus","email":"","orcid":"","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Sibylla","middleName":"","lastName":"Claus","suffix":""},{"id":106958191,"identity":"553cc419-1a67-4708-9bf4-97c3c6be7a26","order_by":3,"name":"Mira Runkel","email":"","orcid":"","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Mira","middleName":"","lastName":"Runkel","suffix":""},{"id":106958192,"identity":"eaca0ff7-9443-4a10-98ca-141789f2cde5","order_by":4,"name":"Stefan Utzolino","email":"","orcid":"","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Utzolino","suffix":""},{"id":106958193,"identity":"9aeb32a3-fb84-4ed1-987a-2d4cf640d312","order_by":5,"name":"Stefan Fichtner-Feigl","email":"","orcid":"","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Fichtner-Feigl","suffix":""},{"id":106958194,"identity":"8398ab44-9bbd-4c30-b0c2-6b9feb341ba2","order_by":6,"name":"Lampros Kousoulas","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-9706-7345","institution":"University Medical Center Freiburg: Universitatsklinikum Freiburg","correspondingAuthor":true,"prefix":"","firstName":"Lampros","middleName":"","lastName":"Kousoulas","suffix":""}],"badges":[],"createdAt":"2022-04-05 16:40:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1526639/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1526639/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":21717028,"identity":"6d8843c1-71fc-4254-bffb-154bd72bf8a3","added_by":"auto","created_at":"2022-05-20 15:59:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49855,"visible":true,"origin":"","legend":"\u003cp\u003eEtiology of hyperlactatemia\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1526639/v1/ed465f8060a0d81353f874cc.png"},{"id":21717027,"identity":"efae952b-cadc-4658-8813-a7908314a6e7","added_by":"auto","created_at":"2022-05-20 15:59:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36955,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of measured peak lactate concentration (mmol/L) by subgroups\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1526639/v1/14210c6dd1580a48172e5cc7.png"},{"id":21716866,"identity":"7952a9d8-0825-42a9-8446-e49bcbb2a608","added_by":"auto","created_at":"2022-05-20 15:54:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22848,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Maier 90 days overall survival depending on blood lactate concentration at ICU admission.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-1526639/v1/a9b688b854f088f5cfc70203.png"},{"id":21716862,"identity":"926c9e5e-3316-424b-a5ef-ac517375baac","added_by":"auto","created_at":"2022-05-20 15:54:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19604,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan- Maier 90 days overall survival in patients with severe hyperlactatemia depending on different etiologic factors (log rank analysis).\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-1526639/v1/2ed22cc8bfe36ecbe962827a.png"},{"id":21716865,"identity":"3fbbcbc4-94d7-4383-9998-520d4a36a16e","added_by":"auto","created_at":"2022-05-20 15:54:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":20850,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between 12h lactate clearance and mortality. The\u003cem\u003e black lines\u003c/em\u003e show 12h lactate clearance of 0% and the cutoff having highest specificity to predict ICU mortality regarding sensitivity and specificity (12\u0026nbsp;h lactate clearance of 29.4%).\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-1526639/v1/021c3692273cfec9d7d53e66.png"},{"id":21717062,"identity":"24ebb0f1-b38b-42db-9f14-ee724c00d4c1","added_by":"auto","created_at":"2022-05-20 15:59:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":477734,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1526639/v1/ec8058f3-b2e4-4cee-ae57-cd597a21ca1f.pdf"}],"financialInterests":"","formattedTitle":"Severe hyperlactatemia in unselected surgical patients. Retrospective analysis of prognostic outcome factors.","fulltext":[{"header":"Background","content":"\u003cp\u003eHyperlactatemia is defined as lactate level\u0026thinsp;\u0026gt;\u0026thinsp;2 mmol/L and is commonly seen in critically ill patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Hyperlactatemia results from the accumulation of lactate and protons in human fluids and tissues and is often associated with poor clinical outcomes. When aerobic glycolysis is impaired, cells increase their glucose utilization by anaerobic glycolysis. This process is less efficient in generating triphosphates and additionally produces pyruvate. This undergoes redox-coupled interconversion catalyzed by the enzyme lactate dehydrogenase, ultimately resulting in lactate [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Hyperlactatemia occurs when lactate production outruns lactate consumption. Additionally, protons equivalent to the number of excess lactate ions are synthetized regardless of the prevailing acid-base status. Approximately 70% of lactate clearance occurs in the liver. Coexisting acidemia contributes to decreased lactate clearance by the liver. Therefore the severity of acidemia seems to be a better predictor of cellular dysfunction and clinical outcomes than hyperlactatemia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn general, hyperlactatemia is caused by tissue hypoxemia due to an imbalance between oxygen supply and demand. This tissue hypoxemia is attributed by impairment of oxygen supply or different forms of shock such as hypovolemic, hemorrhagic, cardiogenic or obstructive shock. Nevertheless, hyperlactatemia can also occur under aerobic conditions. During a state of shock, lactate production is dependent on the stimulation of β\u003csub\u003e2\u0026minus;\u003c/sub\u003e muscle receptors, thus largely independent of tissue hypoxia [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Lactate levels and their trend may be reliable markers of illness severity and mortality [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Only limited data exists about the etiology of lactatemia in sepsis. Wong et al. included lactate in a multibiomarker-based outcome risk model for patients with septic shock [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Opdam et al. reported the lungs to be a major source of lactate for patients in septic shock, which is comparable to animal models [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Lactate and pyruvate concentrations are measured higher in muscle than in arteries during septic shock [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The metabolism of lactate in critically ill patients is described as being associated with cellular inflammatory response [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHyperlactatemia is considered as a clinical marker of critical illness severity. The association between elevated lactate levels and poor outcome of ICU patients is reported in multiple studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Effective lactate clearance seems to be associated with improved outcome [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Recently, Haas et al. retrospectively analyzed patients with plasma lactate levels\u0026thinsp;\u0026gt;\u0026thinsp;10 mmol/L [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and found an overall mortality of 78.2% in these patients, whereas mortality rate of all patients in ICU were only 9.8%. The main etiology for severe hyperlactatemia was septic shock (34.0%), cardiogenic shock (19.3%) and cardiopulmonary resuscitation (13.8%) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Nevertheless, the etiology of hyperlactatemia and lactate clearance rates showed heterogeneity emphasizing the necessity of further research. We therefore analyzed severe hyperlactatemia in unselected surgical patients from the surgical intensive care unit of the University Medical Center Freiburg and evaluated prognostic outcome factors. We hypothesized that severe hyperlactatemia (\u0026gt;\u0026thinsp;10 mmol/L) and a reduced lactate clearance are associated with a poor outcome of surgical patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis cohort study retrospectively evaluated the outcome of 239 consecutive surgical patients with serum lactate levels\u0026thinsp;\u0026gt;\u0026thinsp;10 mmol/L, who were treated at the Medical Center of the University Freiburg between June 2011 and August 2017. The study was approved by the medical Ethics Committee of the University of Freiburg (EK-FR 372/17).\u003c/p\u003e \u003cp\u003ePatients were eligible for inclusion if serum lactate concentration\u0026thinsp;\u0026gt;\u0026thinsp;10mmol/L was documented in a venous or arterial blood sample on at least one occasion. Only patients being treated in surgical ICU were considered. All patients underwent surgery or received another therapeutic intervention such as endoscopic procedures (gastroscopic clipping, endoscopic retrograde cholangiography), therapeutic interventional angiography or comparable endovascular interventions.\u003c/p\u003e \u003cp\u003eNo pre-analytical sample size calculation was performed. Electronic data acquisition of blood gas analysis results in our medical department exists since June 2011. Therefore, due to feasibility reasons, a fixed period between June 2011 and August 2017 was chosen during which all above-mentioned surgical patients with severe hyperlactatemia were included to data analysis.\u003c/p\u003e \u003cp\u003eLactate concentrations were measured during ICU stay in every patient and recorded by an automated data management system. Blood samples were collected in heparinized blood gas syringes and measured with a blood gas analyzer (ABL800 FLEX \u0026copy; Radiometer; Radiometer, Copenhagen, Denmark). All laboratory maintenance was reviewed regularly and tested according to national German laws and manufacturer\u0026rsquo;s specification.\u003c/p\u003e \u003cp\u003eClinical data and patient demographics were extracted from our patient data management system (KIS Freiburg PROMetheus). ICU admission date, date of death (in or outside hospital), cause of hyperlactatemia, sex, age, organic failure / replacement therapies, operations or interventions, hospital admission lactate level as well as peak lactate level and 12h lactate level were defined as target variables. Patients were grouped into different categories related to the etiology of hyperlactatemia [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]: (1) sepsis (including septic shock), (2) cardiogenic shock, (3) postoperative cardiosurgical patients, (4) cardiopulmonary resuscitation, (5) hemorrhagic shock, (6) liver failure, (7) mesenteric ischemia, (8) seizure, (9) other reasons not captured by the previous categories.\u003c/p\u003e \u003cp\u003eDue to retrospective design time trends, selection bias and confounder due to incomplete data cannot be avoided.\u003c/p\u003e \u003cp\u003eSPSS 27 for Windows\u0026trade; was used for statistical analysis (SPSS, Chicago, IL, USA). Categorical variables are presented as frequency and percentage of level. Quantitative variables are shown as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) of distribution. Lactate clearance was calculated by comparing blood lactate concentration 12h after first measurement of lactate\u0026thinsp;\u0026gt;\u0026thinsp;10mmol/L. Categorical variables were put in absolute and relative frequencies; differences were evaluated by Chi-Square or Fisher\u0026rsquo;s exact test as appropriate. Quantitative values were expressed as medians with range and differences were measured using the Mann\u0026ndash;Whitney-U test. Multivariate analysis was performed through forward logistic regression model, with relative risk and a 95% confidence interval. The Kaplan\u0026ndash;Meier method was used to evaluate survival, with a log-rank test for the comparison of subgroups. We used the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve to prognosticate the predictive power of different factors predicting ICU mortality. Youden Index was used to find the optimal cut-off value, which leads to the highest sensitivity and specificity. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBetween June 2011 and August 2017, a total of 14.973 patients were treated in the surgical intensive care unit at the University Medical Center Freiburg. Of these, 242 patients with lactate level\u0026thinsp;\u0026gt;\u0026thinsp;10mmol/L during ICU stay were eligible for study inclusion. Three patients had to be excluded due to implausibility of the recorded lactate measurements. Therefore, data from 239 patients were available for retrospective evaluation. Of 239 included patients, 18 (7.5%) were admitted after elective surgery or intervention and 221 (92.5%) were emergency ICU admissions due to variable causes. We summarized demographic data as well as maximum lactate level, mean hospitalization days, ICU days, ventilation percentage, renal replacement therapy and etiology of hyperlactatemia in Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eIn this cohort mortality was 82.4% (n\u0026thinsp;=\u0026thinsp;197). There was a significant difference in age between \u0026lsquo;survivors\u0026rsquo; and \u0026lsquo;non-survivors\u0026rsquo; (64 years vs. 68 years, respectively p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There was no statistical difference in gender distribution across the two groups. Non-survivors were more likely to be ventilated (p\u0026thinsp;=\u0026thinsp;0.004), however the need for renal replacement therapy showed no significant difference between the two groups. (p\u0026thinsp;=\u0026thinsp;0.340)\u003c/p\u003e \u003cp\u003eIn the survivor group the mean length of ICU stay was 14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4 days compared to 9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7 days for the non-survivor group.\u003c/p\u003e \u003cp\u003ePeak lactate level was significantly higher in the non-survivor group (17.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8mmol/L) compared to the survivor group (13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4mmol/L, p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eTable\u0026nbsp;1: Demographic data, complications and lactate etiology\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eParameter\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eSurvivors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eNon-Survivors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;42 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;197 (82.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean age (years)\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.6 \u0026plusmn; 12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (60.3%)\u003c/p\u003e \u003cp\u003e95 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (9.6%)\u003c/p\u003e \u003cp\u003e19 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e121 (50.6%)\u003c/p\u003e \u003cp\u003e76 (31.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean duration of ICU stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHospitalization days (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.6\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.2\u0026thinsp;\u0026plusmn;\u0026thinsp;25.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVentilation (n (percentage))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208 (87.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178 (74.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRenal replacement (n(percentage)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (30.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 (25.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMaximum lactate (mmol/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLactate etiology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110 (88.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMesenteric ischemia\u003c/p\u003e \u003cp\u003eHemorrhagic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (15.1%)\u003c/p\u003e \u003cp\u003e33 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (13.9%)\u003c/p\u003e \u003cp\u003e8 (24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (86.1%)\u003c/p\u003e \u003cp\u003e25 (75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (69.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCardiopulmonary resuscitation\u003c/p\u003e \u003cp\u003eCardiogenic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (5.0%)\u003c/p\u003e \u003cp\u003e6 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (16.7%)\u003c/p\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (83.3%)\u003c/p\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeizure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther reasons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMann-Whitney-U-Test\u003c/p\u003e \u003cp\u003efor lactate etiology/ Fisher\u0026lsquo;s exact Test for other parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEtiology and course of hyperlactatemia\u003c/h2\u003e \u003cp\u003eThe distribution of patients across different groups of etiology of hyperlactatemia is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In 24 cases, the etiology was considered to be multifactorial and the leading cause was determined according to patients\u0026rsquo; medical history and current consecutive symptom order.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMortality rate in this cohort was 82.4% (n\u0026thinsp;=\u0026thinsp;197). In numerous cases a precise determination of the cause of death was not possible. However, given the frequency of sepsis and septic shock (51.9%), septic multiorgan failure is likely to be the leading cause. Other causes of death included circulatory failure, ARDS and therapy limitation due to, for example, irreversible complete bowel ischemia. ICU mortality in the subgroups was 89% due to sepsis, 86% due to mesenteric ischemia, 76% due to hemorrhagic shock, 70% due to liver failure, 83% due to cardiopulmonary resuscitation, 67% due to cardiogenic shock, 50% due to seizure and 0% due to other reasons. For 72 patients requiring renal replacement therapy, ICU mortality was 85%. Mortality for patients with persisting hyperlactatemia for \u0026gt;\u0026thinsp;12 hours was 87.7% (n\u0026thinsp;=\u0026thinsp;192, (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eMedian lactate concentration ranged from 11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 mmol/L to 17.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0 mmol/L. The distribution of maximum lactate levels is shown in Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003e Figure 2: Distribution of measured peak lactate concentration (mmol/L) by subgroups\u003c/p\u003e \u003cp\u003eMean lactate concentration was 13.9 +/- 4.4 mmol/L in the survivor group and 17.8 +/- 5.8 mmol/L in the non-survivor group. In patients with lactate concentration\u0026thinsp;\u0026lt;\u0026thinsp;10 mmol/L at the time of ICU admission survival was 21.5 +/- 2.0 days compared to patients with lactate concentration of \u0026gt;\u0026thinsp;10mmol/L with 7.9 +/- 1.3 days. We calculated 12.38 mmol/L as peak lactate cut-off with the highest sensitivity for prediction of mortality (Youden Index).\u003c/p\u003e \u003cp\u003eWhen performing Kaplan-Maier analysis, we found blood lactate concentration at ICU admission to significantly influence overall survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Patients whose admission lactate concentration was already above 10 mmol/L show a significantly reduced chance of survival in the 90-day overall survival compared to patients with lactate levels\u0026thinsp;\u0026lt;\u0026thinsp;10mmol/L, according to log rank analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePatients with mesenteric ischemia has significantly lower overall survival compared to other subgroups (p\u0026thinsp;=\u0026thinsp;0.003). Patients with sepsis and septic shock seem to have a better outcome when compared to all other subgroups (Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e Figure 4: Kaplan- Maier 90 days overall survival in patients with severe hyperlactatemia depending on different etiologic factors (log rank analysis).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLactate clearance\u003c/h2\u003e \u003cp\u003eData of lactate clearance within 12h was available for 90 patients (40 survivors, 50 non-survivors). The median percentage of clearance (percentage of reduction after 12h compared to the first measured value of lactate above 10 mmol/L) was 60.3% within 12h for the survivor group and 29.1% for the non-survivor group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There was no statistical difference of 12h lactate clearance between etiologic subgroups (p\u0026thinsp;=\u0026thinsp;0.243). Calculation of ROC analysis revealed a cut-off value for 12h lactate clearance of 29.4% for the prediction of ICU mortality.\u003c/p\u003e \u003cp\u003eLactate clearance was significantly slower when aspartate aminotransferase (p\u0026thinsp;=\u0026thinsp;0.013) as well as alanine aminotransferase were increased (p\u0026thinsp;=\u0026thinsp;0.017). The mean 12 h lactate clearance in each subgroup was 37.7% \u0026plusmn; 40.9 for sepsis, 72.6% \u0026plusmn; 0 for cardiogenic shock 55.0\u0026thinsp;\u0026plusmn;\u0026thinsp;50.1% for cardiopulmonary resuscitation, 43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;39.7% for hemorrhagic shock, 30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;56.6% for liver failure, 48.4\u0026thinsp;\u0026plusmn;\u0026thinsp;24.4%, for mesenteric ischemia, 91.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8% for seizure, and 89.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5% for \u0026lsquo;others\u0026lsquo;.\u003c/p\u003e \u003cp\u003eWe summarized the association between 12h lactate clearance and mortality in Fig.\u0026nbsp;5. Mortality rate for patients with negative lactate clearance (implying an increase of serum lactate level 12h after first measurement of severe hyperlactatemia) was 100%.\u003c/p\u003e \u003cp\u003e Figure 5: Association between 12h lactate clearance and mortality. The \u003cem\u003eblack lines\u003c/em\u003e show 12h lactate clearance of 0% and the cutoff having highest specificity to predict ICU mortality regarding sensitivity and specificity (12 h lactate clearance of 29.4%).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective study indicates that severe hyperlactatemia is associated with poor clinical outcome in unselected surgical patients. Our results highlight that severe hyperlactatemia is still associated with an extremely high ICU mortality.\u003c/p\u003e \u003cp\u003eLimitations to this study are the retrospective nature as well as selection bias. Furthermore, the lack of absolute diagnostic criteria for subgroup selection can lead to over- and/or underrepresentation of subgroups. Multiple factors can lead to severe hyperlactatemia, thus making it difficult to identify a sole cause of increased lactate levels. Nevertheless, we were able to show interesting results for more than 250 patients agreeing with previously reported observations: It is well-known that hyperlactatemia is associated with an increased risk of death [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Almost 30 years ago, Bakker et al. reported about 48 patients suffering from septic shock, with survivors showing significantly lower levels of lactate initially and in the final phase of septic shock, compared to the control group [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Another retrospective study of Varpula et al. with patients in septic shock revealed similar results emphasizing the impact of lactate on mortality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A few years later, Khosravani et al. confirmed the results by reporting data of more than 10 000 ICU patients. Hyperlactatemia was commonly seen in critically ill patients and predicted the risk of death [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies of critically ill medical [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and cardiac surgical [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] showed an association between elevated lactate level, prolonged lactate clearance and mortality. Juneja et al. demonstrated that the outcome of patients with hyperlactatemia on admission is inferior, regardless of the occurrence of hypotension. Hyperlactatemia on admission can thus help us identify patients at higher risk of death so that immediate resuscitative measures can be taken to improve the overall survival.\u003c/p\u003e \u003cp\u003eWe observed sepsis as the predominant reason for severe hyperlactatemia in our cohort. This is consistent with the findings of Haas et al.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Gotmarker et al. have even demonstrated that patients with isolated hyperlactatemia in the setting of sepsis had significantly reduced 90-day overall survival compared to patients with isolated sepsis induced hypotension [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Various guidelines, including those by \u0026bdquo;surviving sepsis campaign\u0026lsquo; [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] now assign lactate measurement as a screening strategy for identifying patients with suspected severe sepsis with higher risk of mortality.\u003c/p\u003e \u003cp\u003eInterestingly, our data suggest that patients whose hyperlactatemia results from sepsis show significantly better overall survival than patients with hyperlactatemia due to mesenteric ischemia (Fig.\u0026nbsp;4). Thus, it can be concluded that despite the apparent anaerobic processes occurring in both groups, the underlying etiology and reversibility of hyperlactatemia seem to be of relevance when evaluating overall survival. Mesenteric ischemia without hyperlactemia is also associated with poor prognosis, which is also confirmed by other studies [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, our results emphasize the importance of lactate clearance for the prognosis of overall survival. Patients with a lactate clearance of less than 30% within the first 12h were shown to have a reduced overall survival with an ICU mortality of 80%. The reversibility of hyperlactatemia is therefore an important risk factor. Multiple trials [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] showed a good predictive power for 12h lactate clearance in determining ICU mortality in critical ill patients. Lactate clearance is currently not part of the general recommendations for septic shock management. Our data go in line with the findings of Arnold et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and show that assessment of lactate clearance is important as a predictor of mortality, independent of central venous oxygen saturation. We suggest that serial lactate measurement may provide important information during intensive care treatment and resuscitation.\u003c/p\u003e \u003cp\u003eMak et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] suggest that the duration of hyperlactatemia is a more important risk factor than the peak lactate concentration for cardiac surgical patients. The authors propose that persistent elevations in lactate are due to a state of ongoing hypoperfusion, leading to a significant increase in mortality risk. This is consistent with our findings regarding the correlation of reduced lactate clearance and increased mortality. Thus, an irreversible cause of hyperlactatemia and reduced hepatic and renal clearances due to multiorgan failure seem to be crucial in risk calculation. However, there are many studies for post-cardiac surgery patients regarding hyperlactatemia and lactate clearance but there is a need for prospective further studies evaluating general surgical patients.\u003c/p\u003e \u003cp\u003eOur findings confirm the association between the timing of severe hyperlactatemia and ICU mortality. Patients, who already showed severe hyperlactatemia at ICU admission, had a significantly increased risk of mortality comparing to patients with lactate levels\u0026thinsp;\u0026lt;\u0026thinsp;10mmol/L. This goes along with data of a European prospective study in patients with liver cirrhosis showing the significant impact of admission lactate levels on 28-day mortality [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Juneja et al demonstrated that hyperlactatemia is commonly evident on admission to a general medical ICU and is associated with increased need for organ support and increased ICU mortality [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The outcome of patients with hyperlactatemia on admission is worse, independent of the presence of hypotension. Hyperlactatemia on admission can guide in identifying patients at higher risk of mortality [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding our results, it can be assumed that patients with severe hyperlactatemia on admission have basically not received causal therapy so far, and thus have a worse outcome than patients who develop hyperlactatemia in the ICU receiving differentiated therapy, e.g., in the context of postoperative hemorrhage or seizure. This could explain the lower overall survival and is an important finding with regard to further prognosis-adapted therapy.\u003c/p\u003e \u003cp\u003eLactate is strong predictor of organ failure and short-term overall survival in critically ill surgical patients. Due to the simplicity and availability in the clinical ICU setting, lactate measurements should be used as a useful and rapid tool to assess severity of disease.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eHyperlactatemia remains a life-threatening emergency status with a high mortality rate. The underlying etiology of hyperlactatemia is relevant to overall survival. Our findings match with previous studies indicating that lactate clearance predicts mortality. Nevertheless, the results clearly indicate the need for further prospective research to develop therapeutic approaches for a better management of hyperlactatemia dependent on its etiology and consequently improve outcome of affected patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC - Area Under the Curve\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROC - Receiver Operating Characteristic\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSD - standard deviation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eANOVA - Analysis of Variance\u003c/p\u003e\n\u003cp\u003eARDS \u0026ndash; Acute Respiratory Distress Syndrome\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eICU \u0026ndash; Intensive Care Unit\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eInstitutional review board statement\u003c/strong\u003e: The study was approved by the Medical Ethics Committee of the University of Freiburg\u0026nbsp;(EK-FR\u0026nbsp;372/17).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e: All the authors have no conflict of interest related to the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: No funding or grants were received for this study\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e: The original anonymous dataset is available on request from the corresponding author at [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution:\u003c/strong\u003e All authors (JS, AKL, SC, MR, SU, SFF, LK) contributed to the study conception and design. JS, AKL and SC performed acquisition of data. All authors (JS, AKL, SC, MR, SU, SFF, LK) performed analysis and interpretation of data. JS and AKL wrote the first draft of the manuscript. All authors (JS, AKL, SC, MR, SU, SFF, LK) commented on previous versions of the manuscript. All authors (JS, AKL, SC, MR, SU, SFF, LK) read, revised and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e: Not Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e: Not Applicable.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRishu AH, Khan R, Al-Dorzi HM, Tamim HM, Al-Qahtani S, Al-Ghamdi G, Arabi YM. Even mild hyperlactatemia is associated with increased mortality in critically ill patients. Crit Care 2013, 17, R197, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc12891\u003c/span\u003e\u003cspan address=\"10.1186/cc12891\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKraut JA, Madias NE. Lactic acidosis. N Engl J Med. 2015;372:1078\u0026ndash;9. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMc1500327\u003c/span\u003e\u003cspan address=\"10.1056/NEJMc1500327\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SW, Hong YS, Park DW, Choi SH, Moon SW, Park JS, Kim JY, Baek KJ. Lactic acidosis not hyperlactatemia as a predictor of in hospital mortality in septic emergency patients. Emerg Med J. 2008;25:659\u0026ndash;65. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/emj.2007.055558\u003c/span\u003e\u003cspan address=\"10.1136/emj.2007.055558\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevy B, Desebbe O, Montemont C, Gibot S. Increased aerobic glycolysis through beta2 stimulation is a common mechanism involved in lactate formation during shock states. Shock 2008, \u003cem\u003e30\u003c/em\u003e, 417\u0026ndash;421, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/SHK.0b013e318167378f\u003c/span\u003e\u003cspan address=\"10.1097/SHK.0b013e318167378f\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCerovic O, Golubovic V, Spec-Marn A, Kremzar B, Vidmar G. Relationship between injury severity and lactate levels in severely injured patients. Intensive Care Med. 2003;29:1300\u0026ndash;5. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-003-1753-8\u003c/span\u003e\u003cspan address=\"10.1007/s00134-003-1753-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNichol A, Bailey M, Egi M, Pettila V, French C, Stachowski E, Reade MC, Cooper DJ, Bellomo R. Dynamic lactate indices as predictors of outcome in critically ill patients. Crit Care. 2011;15:R242. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc10497\u003c/span\u003e\u003cspan address=\"10.1186/cc10497\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong HR, Lindsell CJ, Pettila V, Meyer NJ, Thair SA, Karlsson S, Russell JA, Fjell CD, Boyd JH, Ruokonen E, et al. A multibiomarker-based outcome risk stratification model for adult septic shock*. Crit Care Med. 2014;42:781\u0026ndash;9. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0000000000000106\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0000000000000106\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpdam H, Bellomo R. Oxygen consumption and lactate release by the lung after cardiopulmonary bypass and during septic shock. Crit Care Resusc. 2000;2:181\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevy B, Gibot S, Franck P, Cravoisy A, Bollaert PE. Relation between muscle Na + K + ATPase activity and raised lactate concentrations in septic shock: a prospective study. Lancet. 2005;365:871\u0026ndash;5. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(05)71045-X\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(05)71045-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKellum JA, Song M, Li J. Lactic and hydrochloric acids induce different patterns of inflammatory response in LPS-stimulated RAW 264.7 cells. Am J Physiol Regul Integr Comp Physiol. 2004;286:R686\u0026ndash;92. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/ajpregu.00564.2003\u003c/span\u003e\u003cspan address=\"10.1152/ajpregu.00564.2003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGharipour A, Razavi R, Gharipour M, Modarres R, Nezafati P, Mirkheshti N. The incidence and outcome of severe hyperlactatemia in critically ill patients. Intern Emerg Med. 2021;16:115\u0026ndash;23. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11739-020-02337-9\u003c/span\u003e\u003cspan address=\"10.1007/s11739-020-02337-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu WJ, Zhang Z, Bakker J. Early lactate clearance-guided therapy in patients with sepsis: a meta-analysis with trial sequential analysis of randomized controlled trials. Intensive Care Med. 2015;41:1862\u0026ndash;3. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-015-3955-2\u003c/span\u003e\u003cspan address=\"10.1007/s00134-015-3955-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaas SA, Lange T, Saugel B, Petzoldt M, Fuhrmann V, Metschke M, Kluge S. Severe hyperlactatemia, lactate clearance and mortality in unselected critically ill patients. Intensive Care Med. 2016;42:202\u0026ndash;10. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-015-4127-0\u003c/span\u003e\u003cspan address=\"10.1007/s00134-015-4127-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBakker J, Coffernils M, Leon M, Gris P, Vincent JL. Blood lactate levels are superior to oxygen-derived variables in predicting outcome in human septic shock. Chest. 1991;99:956\u0026ndash;62. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1378/chest.99.4.956\u003c/span\u003e\u003cspan address=\"10.1378/chest.99.4.956\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhosravani H, Shahpori R, Stelfox HT, Kirkpatrick AW, Laupland KB. Occurrence and adverse effect on outcome of hyperlactatemia in the critically ill. Crit Care. 2009;13:R90. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc7918\u003c/span\u003e\u003cspan address=\"10.1186/cc7918\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarpula M, Tallgren M, Saukkonen K, Voipio-Pulkki LM, Pettila V. Hemodynamic variables related to outcome in septic shock. Intensive Care Med. 2005;31:1066\u0026ndash;71. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-005-2688-z\u003c/span\u003e\u003cspan address=\"10.1007/s00134-005-2688-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuneja D, Singh O, Dang R. Admission hyperlactatemia: causes, incidence, and impact on outcome of patients admitted in a general medical intensive care unit. J Crit Care. 2011;26:316\u0026ndash;20. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcrc.2010.11.009\u003c/span\u003e\u003cspan address=\"10.1016/j.jcrc.2010.11.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMak NT, Iqbal S, de Varennes B, Khwaja K. Outcomes of post-cardiac surgery patients with persistent hyperlactatemia in the intensive care unit: a matched cohort study. J Cardiothorac Surg. 2016;11:33. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13019-016-0411-5\u003c/span\u003e\u003cspan address=\"10.1186/s13019-016-0411-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaik R, George G, Karuppiah S, Philip MA. Hyperlactatemia in patients undergoing adult cardiac surgery under cardiopulmonary bypass: Causative factors and its effect on surgical outcome. Ann Card Anaesth. 2016;19:668\u0026ndash;75. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/0971-9784.191579\u003c/span\u003e\u003cspan address=\"10.4103/0971-9784.191579\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGotmaker R, Peake SL, Forbes A, Bellomo R, Investigators* A Mortality is Greater in Septic Patients With Hyperlactatemia Than With Refractory Hypotension. \u003cem\u003eShock\u003c/em\u003e 2017, \u003cem\u003e48\u003c/em\u003e, 294\u0026ndash;300, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/SHK.0000000000000861\u003c/span\u003e\u003cspan address=\"10.1097/SHK.0000000000000861\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, Machado FR, McIntyre L, Ostermann M, Prescott HC, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021. Crit Care Med. 2021;49:e1063\u0026ndash;143. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0000000000005337\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0000000000005337\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeone M, Bechis C, Baumstarck K, Ouattara A, Collange O, Augustin P, Annane D, Arbelot C, Asehnoune K, Baldesi O, et al. Outcome of acute mesenteric ischemia in the intensive care unit: a retrospective, multicenter study of 780 cases. Intensive Care Med. 2015;41:667\u0026ndash;76. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-015-3690-8\u003c/span\u003e\u003cspan address=\"10.1007/s00134-015-3690-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFalk JL, Rackow EC, Leavy J, Astiz ME, Weil MH. Delayed lactate clearance in patients surviving circulatory shock. Acute Care. 1985;11:212\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArnold RC, Shapiro NI, Jones AE, Schorr C, Pope J, Casner E, Parrillo JE, Dellinger RP, Trzeciak S. Emergency Medicine Shock Research Network, I. Multicenter study of early lactate clearance as a determinant of survival in patients with presumed sepsis. Shock. 2009;32:35\u0026ndash;9. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/shk.0b013e3181971d47\u003c/span\u003e\u003cspan address=\"10.1097/shk.0b013e3181971d47\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrolz A, Horvatits T, Rutter K, Landahl F, Roedl K, Meersseman P, Wilmer A, Kluwe J, Lohse AW, Kluge S, et al. Lactate Improves Prediction of Short-Term Mortality in Critically Ill Patients With Cirrhosis: A Multinational Study. Hepatology. 2019;69:258\u0026ndash;69. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hep.30151\u003c/span\u003e\u003cspan address=\"10.1002/hep.30151\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bsur","sideBox":"Learn more about [BMC Surgery](http://bmcsurg.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bsur/default.aspx","title":"BMC Surgery","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"lactate, lactic acidosis, sepsis, shock, outcome, surgical therapy ","lastPublishedDoi":"10.21203/rs.3.rs-1526639/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1526639/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBACKGROUND\u003c/p\u003e\u003cp\u003eEtiology of hyperlactatemia in ICU patients is heterogeneous - septic, cardiogenic or hemorrhagic shock seem to be predominant reasons. Multiple studies show hyperlactatemia as an independent predictor for ICU mortality. Only limited data exists about the etiology of hyperlactatemia and lactate clearance and their influence on mortality. The goal of this single-center retrospective study, was to evaluate the effect of severe hyperlactatemia and reduced lactate clearance rate on the outcome of unselected ICU surgical patients. \u003c/p\u003e\u003cp\u003eMETHODS\u003c/p\u003e\u003cp\u003eOverall, 239 surgical patients with severe hyperlactatemia (\u0026gt;10 mmol/L) who were treated in the surgical ICU at the University Medical Center Freiburg between June 2011 and August 2017, were included in this study. The cause of the hyperlactatemia as well as the postoperative course and the patient morbidity and mortality were retrospectively analyzed. Lactate clearance was calculated by comparing lactate level 12h after first measurement of \u0026gt;10mmol/L.\u003c/p\u003e\u003cp\u003eRESULTS\u003c/p\u003e\u003cp\u003eThe overall mortality rate in our cohort was 82.4%. Severe hyperlactatemia was associated with death in the ICU (p\u0026lt;0.001). The main etiologic factor was sepsis (51.9%), followed by mesenteric ischemia (15.1%), hemorrhagic shock (13.8%) and liver failure (9.6%). Higher lactate levels at ICU admission were associated with increased mortality (p\u0026lt; 0.001). Lactate clearance after 12h was found to predict ICU mortality (ANOVA p\u0026lt;0.001) with an overall clearance of under 50% within 12h. The median percentage of clearance was 60.3% within 12h for the survivor and 29.1% for the non-survivor group (p \u0026lt; 0.001). \u003c/p\u003e\u003cp\u003eCONCLUSION\u003c/p\u003e\u003cp\u003eLactate levels appropriately reflect disease severity and are associated with short-term mortality in critically ill patients. The main etiologic factor for surgical patients is sepsis. When elevated lactate levels persist more than 12h, survival chances are low and the benefit of continued maximum therapy should be evaluated.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Severe hyperlactatemia in unselected surgical patients. Retrospective analysis of prognostic outcome factors.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-05-20 15:54:12","doi":"10.21203/rs.3.rs-1526639/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-06-30T23:50:15+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2022-05-18T15:46:44+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-05-18T11:46:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"BMC Surgery","date":"2022-04-12T10:41:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-04-07T06:23:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Surgery","date":"2022-04-05T12:39:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bsur","sideBox":"Learn more about [BMC Surgery](http://bmcsurg.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bsur/default.aspx","title":"BMC Surgery","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eabbb13e-6219-458f-b6af-d82a6e0f2ccb","owner":[],"postedDate":"May 20th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-07-18T13:14:05+00:00","versionOfRecord":[],"versionCreatedAt":"2022-05-20 15:54:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1526639","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1526639","identity":"rs-1526639","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}