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Early Lactate Values After Out-of-Hospital Cardiac Arrest: Associations With One-Year Outcome

Laurikkala, Johanna; Skrifvars, Markus B.; Bäcklund, Minna; Tiainen, Marjaana; Bendel, Stepani; Karhu, Jaana§; Varpula, Tero; Vaahersalo, Jukka; Pettilä, Ville; Wilkman, Erika; the FINNRESUSCI study group

Author Information
doi: 10.1097/SHK.0000000000001145



Out-of-hospital cardiac arrest (OHCA) occurs in approximately 37 per 100,000 inhabitants per year in Europe (1). Elevated serum lactate is associated with tissue hypoperfusion and organ dysfunction, and in shock states may have prognostic utility (2). High serum lactate levels are predictive of poor outcome in critical illness, such as sepsis and severe trauma (3–6). Several studies have investigated the evolution of lactate values after cardiac arrest, and shown that lower lactate levels and better lactate clearance are associated with decreased short-term mortality and more favorable short-term outcome (7–9). In a recent study, initial lactate levels were suggested as independent predictors of neurologic recovery in OHCA patients (10). Data from another study indicated that early lactate reduction over the first 6 h during ICU stay is associated with better survival and good neurologic outcome at 30 days (11). However, few studies have focused on the possible association between lactate and long-term outcome.

Accordingly, we aimed to determine the associations between lactate values during intensive care after OHCA and 1-year outcome. We hypothesized that high early lactate values after out-of-hospital cardiac arrest are associated with poor long-term outcome.


The FINNRESUSCI study (12) was a multicenter prospective observational study on OHCA patients admitted to 21 ICUs in Finland, from March 1, 2010 to February 28, 2011. The inclusion criteria for the FINNRESUSCI study have been described previously (12). The study protocol was approved by the Ethics Committee of Helsinki University Hospital and each participating hospital.

Patients and general data collection

Demographic data (the International Classification of Diseases [ICD-10] diagnosis, ICU scores, physiologic measures, and outcomes), data on vasopressor and inotrope use, and arterial blood gas samples (including arterial lactate measurements) drawn during intensive care treatment were collected prospectively to the Finnish Intensive Care Consortium database (maintained by Tieto Ltd. Helsinki, Finland) (13).

From the main study database, we included 458 patients from 19 participating ICUs with information on lactate values on admission and during the ICU stay (Fig. 1). The blood-gas samples in each participating ICU were drawn in a standardized way (2 mL sample) from arterial catheters (preferably in the radial artery) and analyzed using point-of-care blood gas analyzers. The timing of blood sampling was at the discretion of ICU staff.

Fig. 1
Fig. 1:
Flowchart of study patients with 1-year outcome after out-of-hospital cardiac arrest.

Vasopressor use and lactate levels

We analyzed vasopressor use during the first 48 h and determined the maximum doses of norepinephrine (NE) and dobutamine use. We identified the first and last lactate measurements, in addition to the highest and lowest values during the ICU stay. We calculated the lactate-time integral (lactate value × time of measurement from first measurement) for evaluation of total lactate burden during the ICU stay and also analyzed the lactate burden for the first 24, 48, and 72 h in the ICU. By dividing the lactate-time integral with the analyzed time frame, we calculated the time-weighted mean lactate values for the first 24, 48, 72 h and for the total duration of lactate follow-up (usually ICU stay or until removal of the arterial catheter). We also calculated lactate clearance, i.e., the difference between admission lactate and the lactate value obtained closest to 12 h, the value closest to 24 h, the value closest to 48 h, and last available lactate between 48 and 72 h as blood gas samples were not drawn according to a preplanned scheme, but at the discretion of the treating team. Lactate clearance was calculated as lactate 0 lactate xhours / lactate 0. We assessed the ability of arterial lactate values at admission and time-weighted lactate during different time frames (0–24, 0–48, 0–72 h and the entire ICU stay) to predict outcome.

Outcome data

A specialist in neurology (MT), blinded to management in the ICU, determined 1-year neurologic outcome based on a telephone interview with the patient, next of kin, or a caregiver. Functional outcome was evaluated with the cerebral performance category (CPC) that was either good (CPC 1–2) or poor (CPC 3–5). CPC1–2 group is defined as good cerebral performance or moderate cerebral disability, but can act independently on daily lives. CPC 3–5 group is defined as severe disability, coma, and (brain) death.

Statistical analyses

Data are presented as percentages or medians with interquartile ranges (IQR). We used a chi-square test or Fisher exact test, when appropriate for categorical data and the Mann–Whitney U test for continuous data. We performed a univariable analysis to determine prognostic factors for 1-year outcome. Finally, variables with a P value < 0.1 were entered to a backward logistic regression analysis to evaluate the possible independent associations between lactate parameters and 1-year outcome. Receiver operating characteristics (ROC) curves with area under the curve (AUC) with 95% confidence intervals (CI) were constructed. The accuracy of ROC analyses is measured by the area under the ROC curve: an area of 1 represents a perfect test and an area of 0.5 a worthless test. All statistical analyses were performed using IBM, SPSS statistics 21.0 and 22.0 (IBM, Armonk, NY) or NCSS 8 (East Kaysville, Utah) software.


We analyzed 548 OHCA patients, of whom 458 patients from 19 participating ICUs had lactate value recordings. Of these 458 patients, 185 (40%) patients had good and 273 (60%) patients had poor 1-year outcomes. Altogether, 91 patients died in the ICU and 193 died in hospital. Of all patients, 204 patients were alive at 12 months. Of these, 185 of 204 (90.7%) were assessed as having a good outcome. We analyzed 10,299 lactate values, a median of 16 (7-35) values per patient. The first lactate measurement was performed at a median of 31 (19–65) min from admission and the last measurement at 6,619 (3,814–14,033) min from admission. The median timing of the samples was 2,566 (970–5,902) min or 42.7 (16.2–98.4) h. Differences in patient characteristics, factors at resuscitation and during ICU stay between patients with good and poor outcomes are presented in ESM Table 1 (see


The admission lactate, the lowest measured lactate, the highest measured lactate, the last measured lactate, and the time-weighted lactate values for all studied time periods were all significantly higher in patients with poor 1-year outcome in univariate analysis as shown in Table 1. Figure 2 shows mean lactate values for 0–24, 24–48, 48–72, and 72–96 h stratified to outcome. Lactate values for 12 h were available in 248 patients, for 24 h were available in 350 patients, and for 48–72 h in 250 patients. A greater difference in lactate values between admission lactate and values measured closest to 12, 24, and 48 h, but not 72 h, were significantly associated with poor outcome (Table 2). Furthermore, we analyzed the associations of the lactate variables with outcome in 1-year survivors only (185 good outcome and 19 bad outcome) (ESM Table 2, see

Table 1
Table 1:
Lactate values and AUCs from ROC analyses in patients with OHCA and their associations with 1-year outcome
Fig. 2
Fig. 2:
Mean lactate for the first 96 h in the ICU stratified according to 1-year outcome (good = CPC 1–2, poor = CPC 3–5).
Table 2
Table 2:
Lactate difference and lactate clearance for 12, 24, 48, and 72 h according to 1-year outcome

The AUC for admission lactate to predict poor outcome in ROC analysis was 0.638 (CI 95% 0.588–0.689), for time-weighted mean lactate for the entire ICU stay 0.654 (CI 95% 0.604–0.703) and for the last measured lactate value in ICU 0.719 (CI 95% 0.673–0.765) (ESM Figure 1, see

Vasopressor use during the first 48 h

Vasopressor data were available in 412 patients treated in 16 participating ICUs. Of these 412 patients, 324 (78.6%) received vasopressors or inotropes during the first 48 h (Table 3). Of 412 patients, 300 (72.8%) were treated with NE. The maximum dose of NE was significantly higher in patients with poor 1-year outcome than those with a good outcome 0.135 μg/kg/min (IQR 0.071–0.256) vs 0.096 μg/kg/min (0.055–0.188), P = 0.004. Of the 412 patients, 121 (29.4%) received dobutamine during the first 48 h. Patients with poor outcome received a higher maximum dose of dobutamine, 3.51 μg/kg/min (IQR 2.08–5.56) than those with good outcome (3.03 μg/kg/min (IQR 1.96–4.17), P = 0.055. No statistical difference in dopamine (P = 0.41) and epinephrine (P = 0.80) use between the groups existed (Table 3). Epinephrine was mainly used as i.v. boluses during resuscitation.

Table 3
Table 3:
Vasopressor and inotrope treatment during the first 48 h in intensive care units after out-of-hospital cardiac arrest and 1-year outcome

Multivariate risks of poor 1-year outcome

We entered the following variables into the multivariate logistic regression analyses, based on the univariable analyses: previous diagnosis of coronary artery disease, witnessed cardiac arrest, time to ROSC, use of epinephrine during CPR, SAPS II score, therapeutic hypothermia, PCI during ICU stay, shockable primary rhythm, chronic heart failure, chronic kidney disease, all with P < 0.1. We inserted the following lactate variable into six separate models: admission lactate (first lactate value measured in the ICU), time-weighted mean lactate value for the first 24 h, time-weighted mean lactate value for the first 48 h, time-weighted mean lactate value for the first 72 h, time-weighted mean lactate for the entire ICU stay. Time-weighted mean lactate for the entire ICU stay and the last measured lactate value were independent predictors of poor 1-year outcome (Table 4). Sensitivity analyses were performed in patients with vasopressor data (n = 412). In these analyses time-weighted mean lactate for the entire ICU stay and the last measured lactate value were also independent predictors of poor 1-year outcome (Table 4).

Table 4
Table 4:
Multivariate backward regression analyses regarding associations between blood lactate and poor 1-year outcome


In this post hoc multicenter observational study, we found that the admission lactate value, the lowest and the highest measured lactate values, the last measured lactate, and time-weighted mean lactate values were all associated with 1-year outcome in the univariate analysis. In multivariate regression analyses, higher time-weighted mean lactate for the entire ICU stay and the last measured lactate were independent predictors of poor 1-year outcome. Contrary to our hypothesis, higher lactate values at admission, higher time-weighted mean lactate for the first 24, 48, and 72 h were not independent predictors of poor long-term outcome.

Several studies have shown associations between hyperlactatemia and worse outcome in different ICU patient groups (14). A recent study showed that high arterial lactate > 4 mmol/L, on presentation to the emergency department, predicted 30-day mortality independently of other measures of illness severity in a heterogeneous patient population (15). In a study of 340 in-hospital cardiac arrest patients, serum lactate level < 9 mmol/L measured within 10 min of cardiopulmonary resuscitation positively correlated with patient survival to hospital discharge (16). Previous studies have also shown that lactate levels are associated with short-term neurologic outcome. In a recent single-center study of 184 OHCA patients surviving to hospital admission, a lactate level < 5 mmol/L was associated with a good neurologic outcome and a cut-off level of > 6.94 mmol/L at admission was associated with poor neurologic outcome within 30 days (17, 18).

Although the results of several studies have shown an association between admission or initial lactate values and outcome, other studies have not confirmed these findings (7, 19, 20). Therefore, recent studies have also assessed the association between lactate clearance, i.e., the decrease in lactate values during a certain time-period, and mortality, as well as neurologic outcome. In two recent prospective studies a greater lactate clearance was a predictor for lower mortality and better neurologic outcome after cardiac arrest (11, 21). However, in a recent observational cohort study of 282 cardiac arrest patients, lactate clearance at 12, 24, and 48 h after admission was not an independent predictor of neurologic outcome at hospital discharge (20).

In line with previous studies we showed that elevated arterial blood lactate levels at every time point were associated with poor neurologic outcome. Unexpectedly, the decrease in lactate values from admission to values closest to 12, 24, and 48 h, i.e., lactate clearances, was greater in patients with poor neurologic outcome. A lower lactate clearance was, however, not independently associated with long-term neurologic outcome in the present study.

In our study, lactate was used for the evaluation of the hemodynamic status of resuscitated patients. Lactatemia during the first hours after cardiac arrest is associated with hypoperfusion after the cessation of blood flow and the inflammatory reaction resulting from the ischemia-reperfusion injury. These early phases of lactatemia may plausibly be treated by hemodynamic optimization if lactate is measured, while persisting or evolving hyperlactatemia in the later phases may be associated with organ failure, which is more difficult to treat, and thus associated with worse outcome. During later phases, several other etiological factors cause elevated lactate including systemic inflammatory reaction, tissue hypoxia, myocardial stunning and microcirculatory and mitochondrial factors as well as unrecognized concomitant infection, sepsis or septic shock, epileptic insults, some forms of mesenterial ischemia and thiamine deficiency may cause hyperlactatemia (3, 4, 7, 22–27).

During resuscitation and the early phase after OHCA, hyperlactatemia can reflect tissue ischemia and the inflammatory reaction resulting from ischemia-reperfusion injury (21). Later during ICU treatment, serial lactate measurements may identify cardiac arrest patients with complications, such as neurologic problems or liver failure (9, 28).

It has been speculated whether the change in serial lactate measurements can guide the treatment strategy of patients. A recent review article suggested that changes in lactate over time are usually relatively slow in critical illnesses and, thus too slow to guide the therapy of patients. Serial lactate concentrations, however, taken every 1 to 2 h, could be used as a compass for checking that therapy of the patient is adequate. If values are not steadily decreasing, changes in therapy may be needed (14). Based on the present study and earlier studies, we suggest that measuring lactate is a valuable part of hemodynamic monitoring of OHCA patients. High lactate levels on admission are worthless for prognostication, but may be used for initiation and monitoring of accurate and timely hemodynamic treatment of these patients (14, 29–31).

The obvious strength of this multicenter study is the inclusion of majority of OHCA patients treated in the Finnish ICUs during 1 year. We analyzed more than 10,000 lactate values, approximately 16 (7–35) values per patient, that were collected directly to the Finnish Intensive Care Consortium database. In addition, we analyzed the association of lactate values and the long-term outcome of patients. Furthermore, in this study an independent neurologist evaluated the 1-year outcome of OHCA patients with a phone interview.

However, the current study has some limitations. First, due to the observational retrospective nature of this study, there may have been unknown potential confounders during ICU stay that have influenced the relationship between lactate measurements and outcome. Second, taking blood samples were not scheduled and thus, more blood samples and lactate measurements were possibly drawn from more severely ill patients. However, we calculated time-weighted lactate values, which adjust for differences in frequency. Third, as clinicians were not blinded to lactate values we cannot rule out the possibility that the patients’ lactate values influenced the treating physicians’ treatment decisions especially in the beginning of the ICU stay. Fourth, 90 patients with missing lactate data resulted in slightly reduced statistical power. Fifth, our data focused only on lactate values although alterations in other biomarkers might be related to adverse outcome after cardiac arrest. Thus, further studies are warranted to elucidate the role of a panel of multiple microcirculatory parameters in survival and neurologic recovery after OHCA. Sixth, the inclusion of patients who survived the transportation to the ICU may have resulted in OHCA patients with better prognosis generally. However, all our patients achieved return of spontaneous circulation in the field before hospitalization.


In this post-hoc analysis of a prospective observational multicenter study, we found that while admission lactate, short-term time-weighted mean lactate, or lactate clearance were not predictors of poor 1-year outcomes, the last measured lactate in the ICU and time-weighted mean lactate for the entire ICU stay were moderate to strong predictors of outcome at 1 year.


The authors thank Tieto Healthcare for database management, and they are grateful to all investigators of the FINNRESUSCI Study Group for collecting data for this article.

The FINNRESUSCI Laboratory Study Group: Participating hospitals, investigators (Inv.) and study nurses (SN.) in the FINNRESUSCIstudy.Satakunta Central Hospital, Dr. Vesa Lund (Inv.), Päivi Tuominen,Satu Johansson, Pauliina Perkola, Elina Kumpulainen (SN.); EastSavo Central Hospital, Dr. Markku Suvela (Inv.), Sari Hirvonen, Sirpa Kauppinen (SN.); Central Finland Central Hospital, Dr. Raili Laru-Sompa (Inv.), Mikko Reilama (SN.); South Savo Central Hospital,Dr. Heikki Laine (Inv.), Pekka Kettunen, Iina Smolander (SN.); NorthCarelia Central Hospital, Dr. Matti Reinikainen (Inv.), Tero Surakka(SN.); Seinäjoki Central Hospital, Dr. Kari Saarinen (Inv.), Pauli-ina Lähdeaho, Johanna Soini (SN.); South Carelia Central Hospital,Dr. Seppo Hovilehto (Inv.); Vaasa Central Hospital, Dr. Simo-PekkaKoivisto, Dr. Raku Hautamäki (Inv.); Kanta-Häme Central Hospital,Dr. Ari Alaspää (Inv.), Tarja Heikkilä (SN.); Lappi Central Hospital,Dr. Outi Kiviniemi (Inv.), Esa Lintula (SN.); Keski-Pohjanmaa CentralHospital, Dr. Tadeusz Kaminski (Inv.), Jane Roiko (SN.); Kymen-laakso Central Hospital, Dr. Seija Alila, Dr. Jussi Pentti (Inv.), ReijaKoskinen (SN.); Länsi-Pohja's Central Hospital, Dr. Jorma Heikkinen(Inv.) Helsinki University Hospital, Jorvi Hospital, Dr. Jukka Vaa-hersalo, Dr. Tuomas Oksanen, Dr. Tero Varpula (Inv.), Anne Eronen,Teemu Hult, Taina Nieminen (SN.); Meilahti Hospital Medical ICU,Dr. Tom Bäcklund (Inv.), Leevi Kauhanen (SN.); Meilahti HospitalICU, Dr. Kirsi-Maija Kaukonen, Dr. Ville Pettilä (Inv.), Leena Pettilä,Sari Sutinen (SN.); Tampere University Hospital, Dr. Sanna Hoppu,Dr. Jyrki Tenhunen, Dr. Sari Karlsson (Inv.), Atte Kukkurainen, SimoVarila, Samuli Kortelainen, Minna-Liisa Peltola (SN.); Kuopio Uni-versity Hospital, Dr. Pamela Hiltunen, Dr. Jouni Kurola, Dr. EskoRuokonen (Inv.), Elina Halonen, Saija Rissanen, Sari Rahikainen(SN.); Oulu University Hospital, Dr. Risto Ahola, Dr. Tero Ala-Kokko(Inv.), Sinikka Sälkiö (SN.)


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Cerebral performance category; intensive care; lactate; long-term outcome; out-of-hospital-cardiac arrest

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