Shock is defined as a state of tissue and cell hypoxia resulting either from an imbalance between oxygen delivery and consumption or from the inadequate use of oxygen (1). This condition is associated with multiple-organ dysfunction, high mortality rates, and approximately 1 million annual visits to emergency rooms (ERs) in the United States (2). There are different types of shock, namely distributive, hypovolemic, obstructive, and cardiogenic; and the most frequent etiologies are infections and trauma with a mortality rate about 30% (3) and 50% (4), respectively. Shock is traditionally identified by a mean blood pressure (MBP) < 65 mmHg, a systolic blood pressure (SBP) <90 mmHg or a >40 mmHg decrease on a prior SBP (1). However, some clinical parameters like capillary refill time, shock index and distal temperature, among others, also have been used to identify this type of patient at the ER (5–7).
It has been demonstrated that a lactate increase is associated to worse clinical outcomes and mortality (8, 9). Recently, some patients with severe infections or trauma without hypotension have been characterized with systemic hypoperfusion and mortality rates like those of a classic shock (10, 11). Blood lactate above 2 mmol/L is proposed as and early and reliable tissue hypoperfusion marker; therefore, blood lactate levels measurement may be useful in critical patients at risk of developing shock of any etiology (12, 13). Furthermore, it has been proposed that lactate clearance during resuscitation is a prognostic marker that indicates the patient's response to the treatment (14–17). This clearance has been defined as a decrease of at least 10% of the initial value (18); an absolute value <4 mmol/L (19); or obtaining <2 mmol/L within the first 6 (14), 12 (20), or 24 h (16) of resuscitation.
In many ERs, lactate may not be available or its results may take time, which might delay patient resuscitation strategies. Therefore, it would be very useful to find an agreement between clinical perfusion variables directly available during physical examination, initial lactate levels and their clearance. The aim of this study was to determine, in patients hospitalized by the ER with hypoperfusion: (1) the correlation and the association between clinical perfusion parameters and initial lactate values upon admission to the ER; (2) the correlation and the association between the change of these clinical parameters and lactate clearance after the first 6 and 24 h of resuscitation; and (3) the association among changes in clinical parameters, lactate values, and hospital mortality.
Study design and setting
Prospective cohort study conducted at Hospital Universitario San Vicente Fundación (HUSVF, Medellin, Colombia) from March 2014 to October 2016. HUSVF is a fourth level university hospital with 672 beds and 85,000 annual ER consultations. The Ethics Committee of Universidad de Antioquia and HUSVF approved the study, and COLCIENCIAS—Science Agency of Colombia—funded it. Written informed consent was obtained from every patient or his/her representative and the study was conducted according to the ethical principles for medical research involving human subjects (WMA Declaration of Helsinki).
Patients ≥18 years admitted to the ER with one of the following diagnosis: (1) an acute bacterial infection confirmed by clinical or laboratory evidence, in accordance with the CDC criteria (21); (2) polytrauma, defined by two or more affected body areas; or (3) suspicion of shock of any other etiology or being at risk of shock: this was defined by the presence of at least one hypotension episode in the first 6 h after admission (MBP < 65 mmHg or SBP < 90 mmHg, or a >40 mmHg decrease of SBP in comparison with previous values) and/or hypoperfusion evidenced by delayed capillary refill time, altered mental status or peripheral coldness. Furthermore, patients should were available to assess vital signs and for physical findings upon being admitted to the hospital.
Patients who were referred from another institution where they stayed for more than 24 h; discharge or reference to another institution during the first 24 h of admission; diseases that hinder the physical evaluation of clinical parameters, such as limb amputation, extensive burns or severe skin diseases, Raynaud's phenomenon or peripheral arterial disease; cirrhosis; mesenteric thrombosis; patient's refusal to participate; screening after 6 h of being admitted to the ER; a previous participation in the study and a do not resuscitate order.
The following patient's clinical signs were measured using standardized methods, upon being admitted to the ER and 6 and 24 h after starting of treatment: capillary refill time, heart rate, SBP, diastolic blood pressure, pulse pressure, MBP, shock index, respiratory rate, and temperature. Simultaneously with the clinical evaluation, venous blood samples were taken to measure lactate during the same periods.
Descriptive or potential confusion/modifiers variables
Demographic and epidemiological data, diagnosis upon admission (infection, polytrauma, or shock of another etiology); treatment, including antibiotics and their appropriateness, steroids, intravenous fluids, and vasopressors; as well as procedures or surgeries. In addition, the following scores were calculated: (i) Charlson Index (22), (ii) APACHE-II (23); (iii) SOFA (24); iv) RTS for trauma (25).
Our primary outcome was in-hospital mortality. In case that the patient had a prolonged hospital stay, we defined the outcome as the vital status at the 28th day of hospitalization.
Measurement of data
Blood pressure was measured using standard methods with an electronic Riester ri-champion N-tensiometer (Riester, Jungingen, Germany). Heart and respiratory rates were evaluated through patient's pulse and thorax observation, respectively, for 1 min. With the data obtained, pulse pressure was calculated, as well as shock index. Capillary refill time was measured applying pressure with a finger on the patient's second finger pad of the right hand for 5 s, enough to turn pale the examiner's nail bed. Afterward, the time it took to recover its normal color was verified using a chronometer (Casio, Model: HS-3V-1R; Casio Computer Co, Ltd, Tokyo, Japan). The temperature was measured using a digital Microlife NC150 thermometer (Microlife AG, Widnau, Switzerland). Serum lactate was determined using a lactic acid assay ARCHITECT c Systems and AEROSET System (Reference: 9D89–20; Abbott Laboratories, Chicago, Ill) test. The detection limit of this system is 0.05 mg/dL and inaccurateness is ±6.3% of the coefficient of variation. The results were converted from mg/dL to mmol/L based on the following equation in accordance with the manufacturer's instructions: mmol/L = mg/dL × k (where k: 0.111).
Research assistant nurses were trained in standardized procedures; a 2-month pilot study was conducted. Every 3 months there was retraining and the tests were performed on patients to keep levels of kappa index and Pearson's correlation coefficient above 0.8. Every week, a different clinical researcher monitored and supervised the recruitment process and verified eligibility criteria and the quality of the collected data. Likewise, the data coordinating center conducted a daily fieldwork verification of missing values, errors and, inconsistencies; and wrote biweekly data quality reports. The variables measured and the data the research personnel obtained did not influence interventions or therapeutic measures implemented on patients.
We considered one of our previous studies (unpublished results), in which a 5:1 ratio was found for patients with a capillary refill time <3:≥3 s, and 25% hospital mortality rate for patients with a capillary refill time ≥3 s. Accordingly, with a beta and alpha error of 0.2 and 0.05, respectively, 420 patients were estimated in the <3 s group and 84 patients in the ≥3 s to detect a two-fold relative risk of mortality. When this sample size was achieved, a preliminary analysis of data was done and we found less mortality than expected. In order to surpass this situation, we continued the recruitment for obtaining enough statistical power and the ethics committee approved that recruitment was continued.
A Spearman's correlation coefficient was fitted to estimate the correlation between clinical variables and lactate serum levels upon admission, as well as between the change of these variables from 0 to 6 h or from 0 to 24 h and serum lactate changes in the same periods (0–6 and 0–24 h). This correlation was performed for the overall population and for subgroups according to admission diagnosis.
An analysis of the Area under the receiver operating characteristic curve (AUC-ROC) was conducted to estimate the predictive association between clinical perfusion variables at admission and lactate >2 mmol/L, as well as between the changes of these clinical variables in the first 6 h and different measurements of serum lactate clearance: any decrease, a clearance of at least 10%, or 50% of the initial values. This analysis allows determining the capacity of the perfusion variables to discriminate the outcome of hyperlactatemia or its clearance.
Several univariate and multivariate logistic regression models were fitted to estimate the association of hospital mortality with the different perfusion variables at admission, their respective changes in the first hours, initial lactate values, and lactate clearance. Finally, a multivariate logistic regression model was performed to adjust initial capillary refill time, shock index, lactate, and the change of these three variables after 6 h. For the last three dynamic variables, a dummy code was created as follows: for a change in shock index and capillary refill time, 1 = the second measurement equal or higher than the first one and 0 = the second measurement less than the first one; and for lactate change, 1 = the second value of lactate equal or higher than 90% of the first one and 0 = the second value of lactate less than 90% of the first one. The latter means a clearance of at least 10% of the initial lactate values, which was the best cutoff point detected by the AUC-ROC analysis.
There were no losses of follow-up. The missing data for APACHE-II and SOFA data were approximately 5% and were considered normal. In the other variables, the missing data were less than 3%.
A total of 3,110 patients were evaluated, 1,320 met the inclusion criteria: 66.7% (n = 880) confirmed infection, 19% (n = 251) polytrauma, and 14.3% (n = 189) shock or hypoperfusion of another etiology (Fig. 1).
The mean age was 51 years (IQR = 34–67) and 62.7% (n = 827) were men. Polytrauma patients differed from the rest of the cohort with a median age of 33 (IQR = 26–47), 90% men (n = 226) and a lower frequency of comorbidities. Among the overall cohort, the median Charlson Index, SOFA and APACHE-II scores were 0 (IQR = 0–2), 2 (IQR = 1–5), and 10 (IQR = 6–16), respectively. Shock, defined as the need for vasopressor use, was present in 131 patients (13.7%). The median length of stay was 9 days (IQR = 4–16), and the hospital mortality rate was 11.6% (n = 153). In the first 24 h, the trauma subgroup patients received more fluids (4,060 cc, IQR = 3,000–6,500) in comparison with infected patients (2,500 mL, IQR = 1,500–3,740) or with other diagnostics (3,000 mL, IQR = 2,000–4,500). Only 13.7% of the patients (n = 181) required vasopressor, and 28.7% (n = 52) of them used two of these medications. This requirement of one or two vasopressors was more frequent in the trauma subgroup: 25.1% (n = 63) and 41.3% (n = 26), respectively. Among infected patients, 601 (68.3%) received appropriate antibiotics. Only 21.5% (n = 284) of the participants were admitted to ICU and this proportion was higher in trauma patients (45.4%, n = 114). The median ICU length of stay was 5 days (IQR = 2–12), without differences according subgroups (Table 1).
The most frequent comorbidities among nonsurvivors were chronic obstructive pulmonary disease (COPD) in 20.3% (n = 31), chronic kidney disease in 11.8% (n = 18), and heart failure in 11.1% (n = 17). Those who died also had at admission higher values in shock index (0.9, IQR = 0.7–1.2 vs. 0.8, IQR = 0.7–1), capillary refill time (2.3, IQR = 2–3.1 s vs. 2, IQR = 1.7–2.4 s), and lactate (3.6, IQR = 2.2–6.8 mmol/L vs. 2.5, IQR = 1.7–3.6 mmol/L). Trauma patients had the longest capillary refill time (2.9 s, IQR = 2–3.7 among deceased patients vs. 2.1, IQR = 1.8–2.9 among the living), and the highest lactate values (4.6 mmol/L, IQR = 2.9–6.9 among deceased patients vs. 3.7, IQR = 2.5–5.3 among the living) (Table 2).
After 6 and 24 h, hemodynamic variables improved in all the patients, including those that eventually died in the hospital. Capillary refill time and lactate values continued being the highest after 6 and 24 h among deceased patients (Supplementary appendix 1 and 2, https://links.lww.com/SHK/A680). It was not found any significant correlation between the clinical variables measured upon being admitted to the ER and the initial lactate values, neither between the deltas of the variables and the delta of lactate (appendix 3, https://links.lww.com/SHK/A680). No relevant data were found in any perfusion variable regarding their discriminative capacity for lactate values >2 mmol/L (appendix 4, https://links.lww.com/SHK/A680), nor any variable change was able to predict lactate clearance (appendixes 5–7, https://links.lww.com/SHK/A680).
Figure 2 shows changes in lactate, capillary refill time, and shock index from 0 to 6 h and from 0 to 24 h. There were significant differences in the trauma subgroup at 6 h, in which deceased patients compared with survivors cleared less lactate (delta = −0.4, IQR = −2–0.8 vs. 0.8, IQR = −0.2–2.1, P = 0.001) and did not improve their capillary refill time (delta = −0.09, IQR = −0.2–0.3 vs. 0.2, IQR = −0.1–0.5, P = 0.001). In the univariate analysis, shock index was associated to mortality and this association was strongest among trauma patients (OR = 5.2; 95% CI = 1.9–14.5), whereas capillary refill time and lactate had a constant association with mortality both in the general population and within subgroups (Table 3). However, in the multivariate analysis, absolute lactate value at admission was the only independent factor associated to mortality in all the cohort's subgroups (Fig. 3). Capillary refill time (OR = 1.7; 95% CI = 1.2–2.4) and a clearance of at least 10% of the initial lactate value (OR = 8.6; 95% CI = 2.4–30.8) provided additional information regarding the prognostics of infected and polytrauma patients, respectively (Table 4). In an additional sensitivity analysis in the subgroup of infected patients without appropriate antibiotics (n = 279, 32%), neither capillary refill time (OR = 1.4; 95% CI = 0.6–3.6) nor lactate value (OR = 0.9; 95% CI = 0.6–1.5) were associated with mortality.
In this cohort of patients hospitalized by the ER with infection, polytrauma or clinical signs of hypoperfusion, we could not demonstrate a correlation between the traditional findings of physical examination and lactate values. Moreover, we did not find a correlation between the change of these variables and the delta of lactate; nor was it possible to predict lactate values higher than 2 mmol/L based on any physical sign. On the adjusted analysis, only the initial lactate values had a significant effect on mortality on all patient groups, with an increase of 20% to 30% in the odds of mortality for every mmol of lactate difference.
Although there are studies regarding the predictive capacity of clinical examination findings for hypoperfusion, there is variability in the studied parameters, the outcomes, the standard of measurement for the variables, and the type of statistical analysis. Specifically, the correlation of capillary refill time and lactate was only evaluated recently by Morimura et al. (26), who used a device to quantify capillary refill time using a modified pulse oximetry technique. With this technique, capillary refill time was correlated with lactate (Spearman's coefficient = 0.68) and with an AUC-ROC = 1, they found a 6.81-s cutoff point to predict a lactate higher than 2 mmol/L. This study may have a selection bias, because there are not clear inclusion criteria for the population of 23 patients at the ICU. In addition, they used a device not standardized for clinical use everywhere.
Lima et al. (27) found a higher frequency of elevated lactate levels (67% vs. 33%, P < 0.05) and a higher SOFA score (9 ± 3 vs. 7 ± 2, P < 0.05) in critical patients with peripheral perfusion abnormalities, such as >4.5 s capillary refill time or cold extremities, after resuscitation. However, these differences were not confirmed with a multivariate analysis. Hernandez et al. (5) found that patients that could normalize capillary refill time and reduce peripheral coldness had more resuscitation success, defined as normalization of lactate values. These results agree with our study, which demonstrated the capacity of capillary refill time to detect infected patients with a higher risk of death, as well as the presence of polytrauma patients in whom the persistence of prolonged capillary refill time suggested an increased mortality risk. Vital signs have been classically used to classify patients’ severity upon being admitted to the ER. Barfod et al. (28) retrospectively reviewed 6,279 patients admitted to the ER to determine which vital signs were related to mortality. They described a significant dose–response association of oxygen saturation (Sat O2), respiratory rate, SBP, and the Glasgow Coma Scale with hospital mortality.
Consistent with previous studies, deceased patients in our cohort had higher hemodynamic deterioration, a more prolonged capillary refill time and higher lactate values. These differences were more marked in the subgroups of polytrauma and shock from other etiologies, which may be explained by the higher severity of these two subpopulations. Thus, the lack of correlation between clinical variables and lactate in our study does not mean that the clinical findings are useless to detect or stratify patients at risk of death. As a matter of fact, after 6 and 24 h there were no significant hemodynamic differences according to vital status, and even nonsurvivors were able to normalize BP values with the implemented treatment. However, capillary refill time and lactate continued being higher among deceased patients after 6 h and after 24 h (appendixes 1 and 2, https://links.lww.com/SHK/A680). These findings reflect, possibly, unknown underlying physiopathological mechanisms that determine the patient's outcome (29); and, hopefully, the next therapy targets going beyond pre-established hemodynamic measurement goals.
The usefulness of lactate as prognostic factor is confirmed in our study in a vast population facing risk of shock. Most prior studies have been conducted on sepsis. Mikkelsen et al. (8) found that lactate values from 2 to 3.9 mmol/L and >4 mmol/L, compared with lower values, had a 2.05 and a 4.87 odds ratio, respectively, for mortality. The population of septic patients described herein is also vast and includes patients with or without organ dysfunction and with or without shock. It is remarkable, and also consistent with previous studies, the ability of the earliest lactate measurement to discriminate patients’ severity, independent of all other traditionally used clinical parameters (10). Regarding trauma patients, Mizushima et al. (11) found that patients with lactate >5 mmol/L had an odds ratio of 4.11 (95% CI = 1.57–10.74) for death. In our cohort, we corroborate the influence of lactate on the prognosis of patients admitted in this condition.
To the best of our knowledge, no study has been reported with characteristics like the one we have specified: prospective information on a population with the entire clinical spectrum faced in an ER, a comprehensive standardization in clinical variable measurement and an exhaustive statistical analysis with various sensitivity analyses. Nevertheless, a reliable evaluation of clinical variables may be problematic because some studies (30–33) have proposed that issues of the environment, such as light, temperature and the medical examiner; may modify the results and their interpretation. In our study, the measurements were done under equal standardized conditions for all the patients. Despite this, one must bear in mind that there is an important variability in the physical examination findings, which could explain, at least partially, the lack of correlation with lactate in our study. Even though these results do not invalidate the use of clinical variables that have been used traditionally for patient approach and handling, it does support the importance of using other diagnostic aids that can detect early and uniformly patients at risk of complications. These properties seem provided by lactate, as has demonstrated in this and other studies. Finally, the cohort suffered lower mortality (10.4%) than what had been estimated (20%), and this could explain the lack of statistical significance in some findings.
Our study shows that, among the collected variables in a population of patients admitted to an ER with risk of shock or hypoperfusion, the lactate value upon admission is an independent prognostic marker for mortality, both in the overall population and in the subgroups with infection, polytrauma, or shock from other etiologies. Although the clinical parameters do not correlate or allow predicting lactate values, capillary refill time and the clearance of at least 10% of the initial lactate value can provide additional prognostic information in infected and trauma patients, respectively.
1. Cecconi M, De Backer D, Antonelli M, Beale R, Bakker J, Hofer C, Jaeschke R, Mebazaa A, Pinsky MR, Teboul JL, et al. Consensus on circulatory shock and hemodynamic monitoring. Task force of the European Society of Intensive Care Medicine. Intensive Care Med
40 12:1795–1815, 2014.
2. Otero R, Nguyen H, Rivers E. Tintinalli J, Stapcynski J, John Ma O, Cline D, Cydulka R, Meckler G. Approach to the patient in shock. Tintinalli's Emergency Medicine: a Comprehensive Study Guide
7th ed.New York, NY: McGraw-Hill Medical; 2010. 165–171.
3. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med
29 7:1303–1310, 2001.
4. Lalezarzadeh F, Wisniewski P, Huynh K, Loza M, Gnanadev D. Evaluation of prehospital and emergency department systolic blood pressure as a predictor of in-hospital mortality. Am Surg
75 10:1009–1014, 2009.
5. Hernandez G, Pedreros C, Veas E, Bruhn A, Romero C, Rovegno M, Neira R, Bravo S, Castro R, Kattan E, et al. Evolution of peripheral vs metabolic perfusion parameters during septic shock resuscitation. A clinical-physiologic study. J Crit Care
27 3:283–288, 2012.
6. Holder AL, Gupta N, Lulaj E, Furgiuele M, Hidalgo I, Jones MP, Jolly T, Gennis P, Birnbaum A. Predictors of early progression to severe sepsis or shock among emergency department patients with nonsevere sepsis. Int J Emerg Med
9 1:10, 2016.
7. Junhasavasdikul D, Theerawit P, Ingsathit A, Kiatboonsri S. Lactate and combined parameters for triaging sepsis patients into intensive care facilities. J Crit Care
8. Mikkelsen ME, Miltiades AN, Gaieski DF, Goyal M, Fuchs BD, Shah CV, Bellamy SL, Christie JD. Serum lactate is associated with mortality in severe sepsis independent of organ failure and shock. Crit Care Med
37 5:1670–1677, 2009.
9. Callaway DW, Shapiro NI, Donnino MW, Baker C, Rosen CL. Serum lactate and base deficit as predictors of mortality in normotensive elderly blunt trauma patients. J Trauma
66 4:1040–1044, 2009.
10. Londoño J, León AL, Rodríguez F, Barrera L, de la Rosa G, Dennis R, Dueñas C, Granados M, Londoño D, Molina F, et al. Serum lactate in the emergency department as a prognostic factor in patients with sepsis without hypotension. Med Clin (Barc)
141 6:246–251, 2013.
11. Mizushima Y, Ueno M, Watanabe H, Ishikawa K, Matsuoka T. Discrepancy between heart rate and makers of hypoperfusion is a predictor of mortality in trauma patients. J Trauma
71 4:789–792, 2011.
12. Manikis P, Jankowski S, Zhang H, Kahn RJ, Vincent JL. Correlation of serial blood lactate levels to organ failure and mortality after trauma. Am J Emerg Med
13 6:619–622, 1995.
13. Aluisio AR, Jain A, Baron BJ, Sarraf S, Sinert R, Legome E, Zehtabchi S. The prognostic role of non-critical lactate levels for in-hospital survival time among ED patients with sepsis. Am J Emerg Med
34 2:170–173, 2016.
14. Cardinal Fernández PA, Olano E, Acosta C, Bertullo H, Albornoz H, Bagnulo H. Prognostic value of lactate clearance in the first 6 hours of intensive medicine course. Med Intensiva
33 4:166–170, 2009.
15. Nguyen HB, Kuan WS, Batech M, Shrikhande P, Mahadevan M, Li CH, Ray S, Dengel A. ATLAS (Asia Network to Regulate Sepsis care) Investigators. Outcome effectiveness of the severe sepsis resuscitation bundle with addition of lactate clearance as a bundle item: a multi-national evaluation. Crit Care
15 5:R229, 2011.
16. Abramson D, Scalea TM, Hitchcock R, Trooskin SZ, Henry SM, Greenspan J. Lactate clearance and survival following injury. J Trauma
35 4:584–589, 1993.
17. Zhang Z, Xu X. Lactate clearance is a useful biomarker for the prediction of all-cause mortality in critically ill patients: a systematic review and meta-analysis. Crit Care Med
42 9:2118–2125, 2014.
18. Jones AE, Shapiro NI, Trzeciak S, Arnold RC, Claremont HA, Kline JA. Emergency Medicine Shock Research Network (EMShockNet) Investigators. Lactate clearance vs central venous oxygen saturation as goals of early sepsis therapy: a randomized clinical trial. JAMA
303 8:739–746, 2010.
19. Casserly B, Phillips GS, Schorr C, Dellinger RP, Townsend SR, Osborn TM, Reinhart K, Selvakumar N, Levy MM. Lactate measurements in sepsis-induced tissue hypoperfusion: results from the Surviving Sepsis Campaign database. Crit Care Med
43 3:567–573, 2015.
20. Nguyen HB, Rivers EP, Knoblich BP, Jacobsen G, Muzzin A, Ressler JA, Ressler JA, Tomlanovich MC. Early lactate clearance is associated with improved outcome in severe sepsis and septic shock. Crit Care Med
32 8:1637–1642, 2004.
21. Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control
36 5:309–332, 2008.
22. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis
40 5:373–383, 1987.
23. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med
13 10:818–829, 1985.
24. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, Bruining H, Reinhart CK, Suter PM, Thijs LG. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med
22 7:707–710, 1996.
25. Champion HR, Sacco WJ, Copes WS, Gann DS, Gennarelli TA, Flanagan ME. A revision of the Trauma Score. J Trauma
29 5:623–629, 1989.
26. Morimura N, Takahashi K, Doi T, Ohnuki T, Sakamoto T, Uchida Y, Takahashi H, Fujita T, Ikeda H. A pilot study of quantitative capillary refill time to identify high blood lactate levels in critically ill patients. Emerg Med J
32 6:444–448, 2015.
27. Lima A, Jansen TC, van Bommel J, Ince C, Bakker J. The prognostic value of the subjective assessment of peripheral perfusion in critically ill patients. Crit Care Med
37 3:934–938, 2009.
28. Barfod C, Lauritzen MM, Danker JK, Sölétormos G, Forberg JL, Berlac PA, Lippert F, Lundstrøm LH, Antonsen K, Lange KH. Abnormal vital signs are strong predictors for intensive care unit admission and in-hospital mortality in adults triaged in the emergency department—a prospective cohort study. Scand J Trauma Resusc Emerg Med
29. Jones AE, Puskarich MA. Sepsis-induced tissue hypoperfusion. Crit Care Nurs Clin North Am
23 1:115–125, 2011.
30. Gorelick MH, Shaw KN, Baker MD. Effect of ambient temperature on capillary refill in healthy children. Pediatrics
92 5:699–702, 1993.
31. Schriger DL, Baraff L. Defining normal capillary refill: variation with age, sex, and temperature. Ann Emerg Med
17 9:932–935, 1988.
32. Brown LH, Prasad NH, Whitley TW. Adverse lighting condition effects on the assessment of capillary refill. Am J Emerg Med
12 1:46–47, 1994.
33. Pickard A, Karlen W, Ansermino JM. Capillary refill time: is it still a useful clinical sign? Anesth Analg
113 1:120–123, 2011.