Lactate level as a predictor of outcomes in patients with acute upper gastrointestinal bleeding: A systematic review and meta‑analysis
- Authors:
- Published online on: January 24, 2024 https://doi.org/10.3892/etm.2024.12401
- Article Number: 113
-
Copyright: © Zeng et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Upper gastrointestinal bleeding (UGIB) is a frequent medical emergency (1) that may arise from peptic ulcers, oesophageal varices, Mallory-Weiss tears and malignancies and is associated with high mortality and morbidity rates (2). Therefore, early detection and prompt management are essential to improve patient outcomes. However, predicting outcomes in patients with acute UGIB is still challenging. Traditional prognostic markers such as age, comorbidities and bleeding intensity are not necessarily accurate indicators of how a patient will fare (3). Therefore, identifying accurate indicators of prognosis in patients with acute UGIB is crucial.
Prognostic value of lactate levels as predictor of outcomes in acute UGIB has drawn more attention in recent years (4-6). Lactate is a by-product of an anaerobic metabolism and builds up in hypoxic tissues (7). Measuring lactate levels is an easy, affordable and accessible test (8). Recent studies show that increased lactate levels are associated with a number of unfavourable outcomes, such as mortality, extended hospital stays and requirement for ICU admission (4,6,9). Increased lactate levels in critically ill patients have been linked to poor outcomes in cases of sepsis, trauma and cardiac arrest (9).
However, it is still debatable whether lactate levels play a role in predicting outcomes in UGIB. While some studies have found no significant correlation, others have established a relationship between elevated lactate levels and poorer outcomes in UGIB patients (4-6). The main goal of the current systematic literature review was to assess the evidence, summarize available findings on the association of lactate levels with outcomes in acute UGIB and evaluate whether the lactate levels can act as predictor for adverse outcomes in patients with UGIB.
Materials and methods
Inclusion criteria. Study design
Observational studies, including cohort (prospective/retrospective), case-control and cross-sectional studies, were considered for inclusion. Full-text studies that met the eligibility criteria were included, while case reports/series and unpublished grey literature were excluded from the analysis. The study was registered at PROSPERO; no. CRD42023406493.
Study participants
Studies performed in patients with acute UGIB who underwent lactate tests were included.
Index test and reference standard
Studies comparing the prognostic role of lactate levels with the real-time occurrence of adverse outcomes through the follow-up of patients either through records or in-person were included.
Outcomes
Mortality, need for packed red blood cell (pRBC) transfusion, rebleeding and ICU admissions.
Search strategy
Search was conducted in multiple databases, including PubMed Central (https://www.ncbi.nlm.nih.gov/pmc/), SCOPUS (https://www.scopus.com/search/form.uri?display=basic#basic), EMBASE (https://www.embase.com/login), MEDLINE (https://pubmed.ncbi.nlm.nih.gov), Google Scholar (https://scholar.google.com) and ScienceDirect (https://www.sciencedirect.com) using medical subject headings (MeSH) and free-text terms with the appropriate Boolean operators (‘AND,’ ‘OR,’ and ‘NOT’) to combine predefined search terms. The search period ranged between January 1964 and February 2023, without any language restrictions (Appendix S1).
Study selection
The initial stage of the study selection process was conducted independently by two researchers, who examined the titles, keywords and abstracts of the identified studies. For the second phase of screening, full texts of the selected studies were retrieved by both investigators. Studies that met eligibility criteria were ultimately included for further analysis. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist 2020 was used to report the present study (10).
Data extraction
For data extraction, two researchers participated in the manual data extraction procedure using a predefined semi-structured data collection form. A third researcher was involved in resolving any conflict arising out of data extraction process.
Risk of bias assessment
Quality of the included studies was assessed by two investigators using the Newcastle Ottawa Scale for observational studies (11). The scale encompasses selection, comparability and outcome domains. Based on the responses, each study was categorized as having good/poor quality.
Statistical analysis
The pooled effect was calculated as standardized mean difference (SMD)/odds ratio (OR) with 95% confidence interval (CI) depending on the type of outcome. Using the inverse variance technique, a random effects model was applied (12). Predictive accuracy was evaluated by calculating the combined values of sensitivity, specificity, likelihood ratios for positive and negative outcomes as well as the overall diagnostic OR for lactate levels. Area under the Receiver Operator Characteristic (AUROC ) was used to produce Summary Receiver Operator Characteristic curves (SROC) (13).
Heterogeneity was measured by I2 statistics and the χ2 of heterogeneity. The effect of a single study on the pooled estimates was determined by sensitivity analysis. Publication bias assessment and meta-regression could not be performed as none of the outcomes had at ≥10 studies. STATA version 14.2 (StataCorp LLC) was used for the analysis.
Results
Search results
A total of 1,489 citations were identified across the databases. Following duplicates removal, 91 full-text articles were retrieved and underwent secondary screening. Finally, a total of 11 studies that satisfied the eligibility criteria were included (Fig. 1) (4-6,14-21).
Characteristics of the included studies
The majority of the studies were conducted in the United States of America (four studies) and Korea (three studies). Most studies were retrospective (six out of 11 studies). Sample size in the included studies varied between 104 and 1,644. The mean age of the participants varied from 55.4-72.9 years. The cut-off for the lactate levels to predict adverse outcomes ranged from 1.85 to 4.3 mmol/l. Of the studies, >50% (six out of 11 studies) had a higher risk of bias (Table I).
Mortality
A total of nine studies reported the utility of lactate levels for prediction of mortality in patients with acute UGIB. Of them, six studies reported the outcomes in terms of OR, with the pooled OR of 1.39 (95% CI: 1.29-1.51; I2=85%), indicating that in patients with acute UGIB higher lactate level are significantly associated with increased mortality compared with normal lactate levels (P<0.001; Fig. 2).
The predictive accuracy of lactate for mortality in patients with acute UGIB is shown in Fig. 3. The diagnostic OR was 7 (95% CI: 5-12), the sensitivity and specificity were 72% (95% CI: 57-83%) and 75% (95% CI: 61-85%), respectively and the positive and negative likelihood ratios were 2.8 (95% CI: 2-4.1) and 0.38, respectively (95% CI: 0.27-0.54). The AUROC was 0.79 (95% CI: 0.72-0.85) (Fig. 4).
Differences in the mean values of lactate in survivors and non-survivors were reported in five studies. The pooled SMD was 1.83 (95% CI: 0.56-3.09; I2=96.2%), indicating that the non-survivors had significantly higher values of lactate when compared with survivors (P<0.001; Fig. 5).
ICU admission
A total of three studies reported the value of lactate levels for prediction of ICU admission in patients with acute UGIB with the pooled OR of 1.29 (95% CI: 1.17-1.42; I2=85.9%), indicating that higher lactate levels associated with increased odds of acute UGIB patients being admitted to ICU compared with normal lactate levels (P<0.001; Fig. 6). Small number of studies, reporting this outcome did not allow to assess the predictive accuracy and mean values.
Rebleeding
A total of four studies reported the utility of lactate levels for prediction of rebleeding in patients with acute UGIB. Of them, three studies reported the outcomes in terms of OR. The pooled OR was 1.14 (95% CI: 1.06-1.23; I2=42.4%) indicating that higher lactate levels are associated with significantly higher (P<0.001) odds of rebleeding compared with normal lactate levels (Fig. 7). The difference in mean values of lactate between acute UGIB patients with and without rebleeding were reported in two studies. Pooled SMD was -0.29 (95% CI: -0.94 to 0.37; I2=71.1%; p=0.39; Fig. 8).
Need for pRBC transfusion
A total of three studies reported the prognostic value of lactate levels for prediction of the need for pRBC transfusion, with the pooled OR of 2.84 (95% CI: 2.14-3.77; I2=8.1%). This indicated that in patients with acute UGIB, higher lactate levels are associated with higher odds of requiring pRBC transfusion compared with normal lactate levels (P<0.001; Fig. 9). The predictive accuracy and mean values are not reported due to the small number of studies.
Additional analysis
Sensitivity analysis did not show any difference for any of the above outcomes, indicating that there were no single-study effects.
Discussion
The present study aimed to investigate whether the lactate may act as a predictor for adverse clinical outcomes in patients with UGIB. The results suggested that the lactate level is a moderately accurate early marker for predicting most adverse outcomes such as mortality, rebleeding, ICU admission and a need for pRBC transfusion. Although, no previous similar reviews were conducted, these findings were consistent across almost all the included studies in the present review (4-6,14-21). Presently, commonly used prognostic markers in patients with acute UGIB include shock index (22), hemodynamic parameters (23), Glasgow-Blatchford score (24) and Rockall score (24). However, these markers have limitations, such as low sensitivity and specificity, or a need for complex calculations. By contrast, lactate levels have been found to be more accurate than other markers such as base deficit or pH, as they rise earlier and more consistently in response to hypoperfusion and provide a more reliable marker of tissue hypoxia (25-27). Since blood loss in patients with acute UGIB can lead to a decrease in oxygen-carrying capacity, lactate levels can serve as a reliable early marker of hypoperfusion. As cells switch to anaerobic metabolism in response to hypoperfusion, lactate production is increased and it is released into the bloodstream (27), leading to adverse outcomes such as higher mortality rates, rebleeding and increase in ICU admission. Therefore, using lactate levels for early detection of hypoperfusion can help clinicians timely identify patients at risk of adverse outcomes and take appropriate action to prevent further deterioration (28).
Elevated lactate levels, a reflection of tissue hypoperfusion and oxygen supply-demand imbalance, emerged as a potent predictor in the present study. Notably, the association between higher lactate levels and the need for pRBC transfusion was more pronounced compared with other clinical outcomes. This underscores the significance of early lactate measurement, potentially guiding clinicians towards urgent interventions and potentially preventing further complications. In addition, lactate levels can be used to guide resuscitation efforts in patients with acute UGIB. Early recognition of hypoperfusion can prompt clinicians to initiate resuscitation measures such as intravenous fluids, blood transfusions, or vasopressors. Serial lactate measurements can also be used to monitor response to treatment and guide ongoing resuscitation efforts (29).
The present study had some limitations. Given the variations in methodologies and quality among the included research, its results should interpreted with caution. For some outcomes, there was significant between-study variability. Due to a restriction in the number of papers, meta-regression and publication bias evaluation were not possible. The included studies measured lactate levels at various time points (at admission, or at different time intervals after the admission). This variation in the timing of measurement could have influenced the predictive accuracy of lactate levels. Additionally, some of the included studies reported that lactate clearance, or the change in lactate levels over time, is more important than initial lactate levels in predicting outcomes. This highlights the potential importance of monitoring lactate levels serially rather than relying solely on a single measurement. The studies included in the present review used different lactate cut-off values to define elevated levels, which may have affected the results. Future studies with standardized lactate cut-off values are needed for better comparability and generalizability of results.
Nonetheless, the present study has several important implications for surgeons, clinicians and nursing care professionals. Lactate levels are an important tool for managing acute UGIB patients and should be used routinely in clinical practice. The present study also supported the need for more studies on the predictive accuracy of lactate. It is important to further evaluate and compare multiple biomarkers and decide on the best possible combination of tests for prediction of adverse clinical outcomes in patients with acute UGIB.
Supplementary Material
SEARCH STRATEGY:
Acknowledgements
Not applicable.
Funding
Funding: The present study was supported by the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine (grant no. 19KY17).
Availability of data and materials
Data sharing is not applicable to this article, as no data sets were generated or analyzed during the current study.
Authors' contributions
FZ conceived and designed the study. LD and LL collected the data and performed the literature search. FZ was involved in the writing of the manuscript. All authors read and approved the final manuscript. Data authentication is not applicable.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
References
Wuerth BA and Rockey DC: Changing epidemiology of upper gastrointestinal hemorrhage in the last decade: A nationwide analysis. Dig Dis Sci. 63:1286–1293. 2018.PubMed/NCBI View Article : Google Scholar | |
DiGregorio AM and Alvey H: Gastrointestinal bleeding. In: StatPearls. StatPearls Publishing, Treasure Island, FL, 2023. | |
Kaya E, Karaca MA, Aldemir D and Ozmen MM: Predictors of poor outcome in gastrointestinal bleeding in emergency department. World J Gastroenterol. 22:4219–4225. 2016.PubMed/NCBI View Article : Google Scholar | |
Stokbro LA, de Muckadell OB and Laursen SB: Arterial lactate does not predict outcome better than existing risk scores in upper gastrointestinal bleeding. Scand J Gastroenterol. 53:586–591. 2018.PubMed/NCBI View Article : Google Scholar | |
Wada T, Hagiwara A, Uemura T, Yahagi N and Kimura A: Early lactate clearance for predicting active bleeding in critically ill patients with acute upper gastrointestinal bleeding: A retrospective study. Intern Emerg Med. 11:737–743. 2016.PubMed/NCBI View Article : Google Scholar | |
Kim K, Lee DH, Lee DH, Choi YH and Bae SJ: Early lactate clearance for predicting outcomes in patients with gastrointestinal bleeding. Ir J Med Sci. 192:1923–1929. 2022.PubMed/NCBI View Article : Google Scholar | |
Rabinowitz JD and Enerbäck S: Lactate: The ugly duckling of energy metabolism. Nat Metab. 2:566–571. 2020.PubMed/NCBI View Article : Google Scholar | |
Schmiedeknecht K, Kaufmann A, Bauer S and Solis FV: L-lactate as an indicator for cellular metabolic status: An easy and cost-effective colorimetric L-lactate assay. PLoS One. 17(e0271818)2022.PubMed/NCBI View Article : Google Scholar | |
Andersen LW, Mackenhauer J, Roberts JC, Berg KM, Cocchi MN and Donnino MW: Etiology and therapeutic approach to elevated lactate levels. Mayo Clin Proc. 88:1127–1140. 2013.PubMed/NCBI View Article : Google Scholar | |
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al: The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 372(n71)2021.PubMed/NCBI View Article : Google Scholar | |
Wells G, Shea B, O’Connell D, Robertson J, Peterson J, Losos M and Tugwell P: The Newcastle-ottawa scale (NOS) for assessing the quality of nonrandomized studies in meta- analysis. Ottawa Hospital Research Institute, Ottawa ON, 2011. | |
Borenstein M, Hedges LV, Higgins JPT and Rothstein HR: A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 1:97–111. 2010.PubMed/NCBI View Article : Google Scholar | |
Wang J, Keusters WR, Wen L and Leeflang MMG: IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta-analyses of diagnostic test accuracy. Res Synth Methods. 12:45–54. 2021.PubMed/NCBI View Article : Google Scholar | |
Shrestha MP, Borgstrom M and Trowers EA: Elevated lactate level predicts intensive care unit admissions, endoscopies and transfusions in patients with acute gastrointestinal bleeding. Clin Exp Gastroenterol. 11:185–192. 2018.PubMed/NCBI View Article : Google Scholar | |
Gulen M, Satar S, Tas A, Avci A, Nazik H and Firat BT: Lactate level predicts mortality in patients with upper gastrointestinal bleeding. Gastroenterol Res Pract. 2019(5048078)2019.PubMed/NCBI View Article : Google Scholar | |
Lee SH, Min YW, Bae J, Lee H, Min BH, Lee JH, Rhee PL and Kim JJ: Lactate parameters predict clinical outcomes in patients with nonvariceal upper gastrointestinal bleeding. J Korean Med Sci. 32:1820–1827. 2017.PubMed/NCBI View Article : Google Scholar | |
Berger M, Divilov V and Teressa G: Lactic acid is an independent predictor of mortality and improves the predictive value of existing risk scores in patients presenting with acute gastrointestinal bleeding. Gastroenterology Res. 12:1–7. 2019.PubMed/NCBI View Article : Google Scholar | |
Ko BS, Kim WY, Ryoo SM, Ahn S, Sohn CH, Seo DW, Lee YS, Lim KS and Jung HY: Predicting the occurrence of hypotension in stable patients with nonvariceal upper gastrointestinal bleeding: Point-of-care lactate testing. Crit Care Med. 43:2409–2415. 2015.PubMed/NCBI View Article : Google Scholar | |
El-Kersh K, Chaddha U, Sinha RS, Saad M, Guardiola J and Cavallazzi R: Predictive role of admission lactate level in critically Ill patients with acute upper gastrointestinal bleeding. J Emerg Med. 49:318–325. 2015.PubMed/NCBI View Article : Google Scholar | |
Shah A, Chisolm-Straker M, Alexander A, Rattu M, Dikdan S and Manini AF: Prognostic use of lactate to predict inpatient mortality in acute gastrointestinal hemorrhage. Am J Emerg Med. 32:752–755. 2014.PubMed/NCBI View Article : Google Scholar | |
Strzałka M, Winiarski M, Dembiński M, Pędziwiatr M, Matyja A and Kukla M: Predictive role of admission venous lactate level in patients with upper gastrointestinal bleeding: A prospective observational study. J Clin Med. 11(335)2022.PubMed/NCBI View Article : Google Scholar | |
Saffouri E, Blackwell C, Laursen SB, Laine L, Dalton HR, Ngu J, Shultz M, Norton R and Stanley AJ: The Shock Index is not accurate at predicting outcomes in patients with upper gastrointestinal bleeding. Aliment Pharmacol Ther. 51:253–260. 2020.PubMed/NCBI View Article : Google Scholar | |
Benedeto-Stojanov D, Bjelaković M, Stojanov D and Aleksovski B: Prediction of in-hospital mortality after acute upper gastrointestinal bleeding: Cross-validation of several risk scoring systems. J Int Med Res. 50(3000605221086442)2022.PubMed/NCBI View Article : Google Scholar | |
Chang A, Ouejiaraphant C, Akarapatima K, Rattanasupa A and Prachayakul V: Prospective comparison of the AIMS65 score, glasgow-blatchford score and rockall score for predicting clinical outcomes in patients with variceal and nonvariceal upper gastrointestinal bleeding. Clin Endosc. 54:211–221. 2021.PubMed/NCBI View Article : Google Scholar | |
Neville AL, Nemtsev D, Manasrah R, Bricker SD and Putnam BA: Mortality risk stratification in elderly trauma patients based on initial arterial lactate and base deficit levels. Am Surg. 77:1337–1341. 2011.PubMed/NCBI | |
Jansen TC, van Bommel J, Mulder PG, Rommes JH, Schieveld SJM and Bakker J: The prognostic value of blood lactate levels relative to that of vital signs in the pre-hospital setting: A pilot study. Crit Care. 12(R160)2008.PubMed/NCBI View Article : Google Scholar | |
Northfield TC, Kirby BJ and Tattersfield AE: Acid-base balance in acute gastrointestinal bleeding. Br Med J. 2:242–244. 1971.PubMed/NCBI View Article : Google Scholar | |
Foucher CD and Tubben RE: Lactic acidosis. In: StatPearls. StatPearls Publishing, Treasure Island (FL), 2023. | |
Krishna U, Joshi SP and Modh M: An evaluation of serial blood lactate measurement as an early predictor of shock and its outcome in patients of trauma or sepsis. Indian J Crit Care Med. 13:66–73. 2009.PubMed/NCBI View Article : Google Scholar |