Association between Pre-Existing Long-Term β-Blocker Therapy and the Outcomes of Sepsis-Associated Coagulopathy: A Retrospective Study
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Study Patients
2.3. Measurement of the Outcomes
2.4. Data Collection
2.5. Statistical Analysis
3. Results
3.1. Patient Characteristics
3.2. Pre-Existing Long-Term β-Blocker Therapy and Clinical Outcomes
3.3. Changes in Markers of Coagulation Function
3.4. Pre-Existing Long-Term β-Blocker Therapy and 28-Day Mortality
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Singer, M.; Deutschman, C.S.; Seymour, C.W.; Shankar-Hari, M.; Annane, D.; Bauer, M.; Bellomo, R.; Bernard, G.R.; Chiche, J.D.; Coopersmith, C.M.; et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016, 315, 801–810. [Google Scholar] [CrossRef] [PubMed]
- Seymour, C.W.; Kennedy, J.N.; Wang, S.; Chang, C.H.; Elliott, C.F.; Xu, Z.; Berry, S.; Clermont, G.; Cooper, G.; Gomez, H.; et al. Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis. JAMA 2019, 321, 2003–2017. [Google Scholar] [CrossRef] [PubMed]
- Lyons, P.G.; Micek, S.T.; Hampton, N.; Kollef, M.H. Sepsis-Associated Coagulopathy Severity Predicts Hospital Mortality. Crit. Care Med. 2018, 46, 736–742. [Google Scholar] [CrossRef] [PubMed]
- Giustozzi, M.; Ehrlinder, H.; Bongiovanni, D.; Borovac, J.A.; Guerreiro, R.A.; Gasecka, A.; Papakonstantinou, P.E.; Parker, W.A.E. Coagulopathy and sepsis: Pathophysiology, clinical manifestations and treatment. Blood Rev. 2021, 50, 100864. [Google Scholar] [CrossRef] [PubMed]
- Ren, C.; Li, Y.X.; Xia, D.M.; Zhao, P.Y.; Zhu, S.Y.; Zheng, L.Y.; Liang, L.P.; Yao, R.Q.; Du, X.H. Sepsis-Associated Coagulopathy Predicts Hospital Mortality in Critically Ill Patients With Postoperative Sepsis. Front. Med. 2022, 9, 783234. [Google Scholar] [CrossRef]
- Iba, T.; Levy, J.H.; Warkentin, T.E.; Thachil, J.; van der Poll, T.; Levi, M.; The Scientific and Standardization Committee on DIC; The Scientific and Standardization Committee on Perioperative and Critical Care of the International Society on Thrombosis and Haemostasis. Diagnosis and management of sepsis-induced coagulopathy and disseminated intravascular coagulation. J. Thromb. Haemost. 2019, 17, 1989–1994. [Google Scholar] [CrossRef]
- Vincent, J.L.; Francois, B.; Zabolotskikh, I.; Daga, M.K.; Lascarrou, J.B.; Kirov, M.Y.; Pettila, V.; Wittebole, X.; Meziani, F.; Mercier, E.; et al. Effect of a Recombinant Human Soluble Thrombomodulin on Mortality in Patients with Sepsis-Associated Coagulopathy: The SCARLET Randomized Clinical Trial. JAMA 2019, 321, 1993–2002. [Google Scholar] [CrossRef]
- Thachil, J. Managing sepsis-associated coagulopathy remains an enigma. J. Thromb. Haemost. 2019, 17, 1586–1589. [Google Scholar] [CrossRef]
- Tagami, T. Antithrombin concentrate use in sepsis-associated disseminated intravascular coagulation: Re-evaluation of a ‘pendulum effect’ drug using a nationwide database. J. Thromb. Haemost. 2018, 16, 458–461. [Google Scholar] [CrossRef]
- van der Poll, T. Recombinant Human Soluble Thrombomodulin in Patients With Sepsis-Associated Coagulopathy: Another Negative Sepsis Trial? JAMA 2019, 321, 1978–1980. [Google Scholar] [CrossRef]
- Tan, K.; Harazim, M.; Tang, B.; McLean, A.; Nalos, M. The association between premorbid beta blocker exposure and mortality in sepsis-a systematic review. Crit. Care 2019, 23, 298. [Google Scholar] [CrossRef]
- Hartmann, C.; Radermacher, P.; Wepler, M.; Nussbaum, B. Non-Hemodynamic Effects of Catecholamines. Shock 2017, 48, 390–400. [Google Scholar] [CrossRef]
- Andreis, D.T.; Singer, M. Catecholamines for inflammatory shock: A Jekyll-and-Hyde conundrum. Intensive Care Med. 2016, 42, 1387–1397. [Google Scholar] [CrossRef]
- Singer, M. Catecholamine treatment for shock—Equally good or bad? Lancet 2007, 370, 636–637. [Google Scholar] [CrossRef]
- Suzuki, T.; Suzuki, Y.; Okuda, J.; Kurazumi, T.; Suhara, T.; Ueda, T.; Nagata, H.; Morisaki, H. Sepsis-induced cardiac dysfunction and beta-adrenergic blockade therapy for sepsis. J. Intensive Care 2017, 5, 22. [Google Scholar] [CrossRef]
- Morelli, A.; Ertmer, C.; Westphal, M.; Rehberg, S.; Kampmeier, T.; Ligges, S.; Orecchioni, A.; D’Egidio, A.; D’Ippoliti, F.; Raffone, C.; et al. Effect of heart rate control with esmolol on hemodynamic and clinical outcomes in patients with septic shock: A randomized clinical trial. JAMA 2013, 310, 1683–1691. [Google Scholar] [CrossRef]
- Macchia, A.; Romero, M.; Comignani, P.D.; Mariani, J.; D’Ettorre, A.; Prini, N.; Santopinto, M.; Tognoni, G. Previous prescription of beta-blockers is associated with reduced mortality among patients hospitalized in intensive care units for sepsis. Crit. Care Med. 2012, 40, 2768–2772. [Google Scholar] [CrossRef]
- Contenti, J.; Occelli, C.; Corraze, H.; Lemoel, F.; Levraut, J. Long-Term beta-Blocker Therapy Decreases Blood Lactate Concentration in Severely Septic Patients. Crit. Care Med. 2015, 43, 2616–2622. [Google Scholar] [CrossRef]
- Li, J.; Sun, W.; Guo, Y.; Ren, Y.; Li, Y.; Yang, Z. Prognosis of beta-adrenergic blockade therapy on septic shock and sepsis: A systematic review and meta-analysis of randomized controlled studies. Cytokine 2020, 126, 154916. [Google Scholar] [CrossRef]
- Hasegawa, D.; Sato, R.; Prasitlumkum, N.; Nishida, K.; Takahashi, K.; Yatabe, T.; Nishida, O. Effect of Ultrashort-Acting beta-Blockers on Mortality in Patients With Sepsis With Persistent Tachycardia Despite Initial Resuscitation: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Chest 2021, 159, 2289–2300. [Google Scholar] [CrossRef]
- Goradia, S.; Sardaneh, A.A.; Narayan, S.W.; Penm, J.; Patanwala, A.E. Vasopressor dose equivalence: A scoping review and suggested formula. J. Crit. Care 2021, 61, 233–240. [Google Scholar] [CrossRef] [PubMed]
- Stolk, R.F.; Kox, M.; Pickkers, P. Noradrenaline drives immunosuppression in sepsis: Clinical consequences. Intensive Care Med. 2020, 46, 1246–1248. [Google Scholar] [CrossRef] [PubMed]
- de Montmollin, E.; Aboab, J.; Mansart, A.; Annane, D. Bench-to-bedside review: Beta-adrenergic modulation in sepsis. Crit. Care 2009, 13, 230. [Google Scholar] [CrossRef] [PubMed]
- Kimmoun, A.; Louis, H.; Al Kattani, N.; Delemazure, J.; Dessales, N.; Wei, C.; Marie, P.Y.; Issa, K.; Levy, B. beta1-Adrenergic Inhibition Improves Cardiac and Vascular Function in Experimental Septic Shock. Crit. Care Med. 2015, 43, e332–e340. [Google Scholar] [CrossRef] [PubMed]
- Kuo, M.J.; Chou, R.H.; Lu, Y.W.; Guo, J.Y.; Tsai, Y.L.; Wu, C.H.; Huang, P.H.; Lin, S.J. Premorbid beta1-selective (but not non-selective) beta-blocker exposure reduces intensive care unit mortality among septic patients. J. Intensive Care 2021, 9, 40. [Google Scholar] [CrossRef]
- Tan, K.; Harazim, M.; Simpson, A.; Tan, Y.C.; Gunawan, G.; Robledo, K.P.; Whitehead, C.; Tang, B.; McLean, A.; Nalos, M. Association Between Premorbid Beta-Blocker Exposure and Sepsis Outcomes-The Beta-Blockers in European and Australian/American Septic Patients (BEAST) Study. Crit. Care Med. 2021, 49, 1493–1503. [Google Scholar] [CrossRef]
- Musher, D.M.; Abers, M.S.; Corrales-Medina, V.F. Acute Infection and Myocardial Infarction. N. Engl. J. Med. 2019, 380, 171–176. [Google Scholar] [CrossRef]
- Ho, S.; Phua, H.P.; Lim, W.Y.; Mahalingam, N.; Tan, G.H.C.; Puah, S.H.; Lew, J.W.S. Sepsis, cardiovascular events and short-term mortality risk in critically ill patients. Ann. Acad. Med. Singap. 2022, 51, 272–282. [Google Scholar] [CrossRef]
- Matsubara, T.; Yamakawa, K.; Umemura, Y.; Gando, S.; Ogura, H.; Shiraishi, A.; Kushimoto, S.; Abe, T.; Tarui, T.; Hagiwara, A.; et al. Significance of plasma fibrinogen level and antithrombin activity in sepsis: A multicenter cohort study using a cubic spline model. Thromb. Res. 2019, 181, 17–23. [Google Scholar] [CrossRef]
- Hjemdahl, P.; Larsson, P.T.; Wallen, N.H. Effects of stress and beta-blockade on platelet function. Circulation 1991, 84, VI44–VI61. [Google Scholar]
- Keularts, I.M.; van Gorp, R.M.; Feijge, M.A.; Vuist, W.M.; Heemskerk, J.W. alpha(2A)-adrenergic receptor stimulation potentiates calcium release in platelets by modulating cAMP levels. J. Biol. Chem. 2000, 275, 1763–1772. [Google Scholar] [CrossRef]
- Markel, A.; Brook, J.G.; Levy, Y.; Aviram, M.; Youdim, M.B. Increased platelet adhesion and aggregation in hypertensive patients: Effect of atenolol. Br. J. Clin. Pharmacol. 1983, 16, 663–668. [Google Scholar] [CrossRef]
- Adler, B.; Gimbrone, M.A., Jr.; Schafer, A.I.; Handin, R.I. Prostacyclin and beta-adrenergic catecholamines inhibit arachidonate release and PGI2 synthesis by vascular endothelium. Blood 1981, 58, 514–517. [Google Scholar] [CrossRef]
- Morelli, A.; Donati, A.; Ertmer, C.; Rehberg, S.; Kampmeier, T.; Orecchioni, A.; D’Egidio, A.; Cecchini, V.; Landoni, G.; Pietropaoli, P.; et al. Microvascular effects of heart rate control with esmolol in patients with septic shock: A pilot study. Crit. Care Med. 2013, 41, 2162–2168. [Google Scholar] [CrossRef]
Variables | Total n = 228 | Beta-Blocker n = 48 | No Beta-Blocker n = 180 | p Value |
---|---|---|---|---|
Age, years, mean ± SD | 66.1 ± 15.7 | 72.8 ± 12.3 | 64.3 ± 16.1 | 0.001 |
Male sex, n (%) | 139 (61.0%) | 25 (52.1%) | 114 (63.3%) | 0.156 |
Comorbidities | ||||
Hypertension, n (%) | 92 (40.4%) | 39 (81.3%) | 53 (29.4%) | <0.001 |
Diabetes, n (%) | 48 (21.1%) | 16 (33.3%) | 32 (17.8%) | 0.019 |
Chronic lung disease, n (%) | 26 (11.4%) | 4 (8.3%) | 22 (12.2%) | 0.451 |
Coronary heart disease, n (%) | 49 (21.5%) | 20 (41.7%) | 29 (16.1%) | <0.001 |
Cerebrovascular disease, n (%) | 44 (19.3%) | 13 (27.1%) | 31 (17.2%) | 0.124 |
Others, n (%) | 64 (28.1%) | 13 (27.1%) | 51 (28.3%) | 0.864 |
Source of infection | ||||
Pulmonary infection, n (%) | 106 (46.5%) | 17 (35.4%) | 89 (49.4%) | 0.083 |
Intraabdominal infection, n (%) | 74 (32.5%) | 19 (39.6%) | 55 (30.6%) | 0.235 |
Urinary infections, n (%) | 44 (19.3%) | 13 (27.1%) | 31 (17.2%) | 0.124 |
Soft tissue infection, n (%) | 14 (6.1%) | 3 (6.3%) | 11 (6.1%) | 0.972 |
Bacteraemia, n (%) | 20 (8.3%) | 4 (8.3%) | 16 (8.8%) | 0.904 |
Other sources, n (%) | 6 (2.6%) | 2 (4.2%) | 4 (2.2%) | 0.455 |
Vital lab data | ||||
WBC (109/L), median (IQR) | 11.5 (6.9–17.1) | 11.6 (8.7–16.3) | 11.4 (6.5–17.7) | 0.826 |
Neutrophils (%), median (IQR) | 91.0 (83.6–94.0) | 91.2 (84.4–94.0) | 91.0 (82.6–94.0) | 0.961 |
Lymphocytes (%), median (IQR) | 4.3 (2.6–8.8) | 4.4 (2.2–8.0) | 4.2 (2.7–9.8) | 0.462 |
Monocytes (%), median (IQR) | 3.7 (2.4–6.1) | 4.2 (3.0–6.3) | 3.6 (2.2–6.0) | 0.209 |
Platelet (109/L), median (IQR) | 73.0 (42.0–103.0) | 74.5 (54.0–107.8) | 73.0 (41.0–99.3) | 0.354 |
INR, median (IQR) | 1.61 (1.47–1.99) | 1.60 (1.46–1.94) | 1.62 (1.48–2.00) | 0.543 |
HGB (g/L), median (IQR) | 98.0 (81.3–114.0) | 96.0 (86.5–113.0) | 98.5 (79.0–114.3) | 0.96 |
ALB (g/L), median (IQR) | 27.5 (23.9–30.6) | 28.3 (26.5–30.5) | 27.0 (23.6–30.6) | 0.156 |
Glucose (mmol/L), median (IQR) | 6.6 (5.3–8.9) | 6.7 (5.8–9.0) | 6.5 (5.1–8.9) | 0.186 |
Bilirubin (μmol/L), median (IQR) | 33.1 (17.3–65.2) | 28.2 (13.2–64.0) | 33.9 (18.1–65.2) | 0.391 |
Creatinine (μmol/L), median (IQR) | 167.1 (96.1–256.4) | 177.8 (113.4–252.0) | 163.4 (85.3–256.4) | 0.314 |
SOFA score, mean ± SD | 11.2 ± 4.6 | 9.9 ± 4.4 | 11.5 ± 4.6 | 0.034 |
Variables | Total n = 228 | Beta-Blocker n = 48 | No Beta-Blocker n = 180 | p Value |
---|---|---|---|---|
Septic shock, n (%) | 173 (75.9%) | 31 (64.6%) | 142 (78.9%) | 0.040 |
Mechanical ventilation, n (%) | 121 (53.1%) | 19 (39.6%) | 102 (56.7%) | 0.035 |
Norepinephrine equivalents total * (μg/kg/min), median (IQR) | 0.24 (0–1.20) | 0.11 (0–0.32) | 0.32 (0.06–1.48) | <0.001 |
Mortality on day 28, n (%) | 104 (45.6%) | 17 (35.4%) | 87 (48.3%) | 0.110 |
Variables | Day 1 of ICU Admission | p Value | Day 4 of ICU Admission | p Value | ||
---|---|---|---|---|---|---|
Beta-Blocker (n = 48) | No Beta-Blocker (n = 180) | Beta-Blocker (n = 37) | No Beta-Blocker (n = 116) | |||
PT (s), | 17.5 | 17.8 | 0.511 | 14 | 14.6 | 0.818 |
median (IQR) | (15.8–21.4) | (16.1–21.8) | (13.0–17.3) | (13.0–17.4) | ||
APTT (s), | 35.8 | 38.1 | 0.057 | 33.9 | 33.4 | 0.777 |
median (IQR) | (32.8–39.0) | (32.6–48.5) | (30.1–38.2) | (29.8–41.2) | ||
TT (s), | 15.2 | 15.4 | 0.554 | 15.9 | 16 | 0.516 |
median (IQR) | (13.8–17.2) | (14.0–17.8) | (14.0–16.6) | (14.0–18.2) | ||
FIB (mg/dL), | 394 | 370.5 | 0.604 | 334 | 337 | 0.895 |
median (IQR) | (283.5–431.8) | (243.3–452.3) | (219.0–380.0) | (228.5–432.0) | ||
DD (ng/mL), | 2474 | 3138 | 0.016 | 2009 | 2722 | 0.131 |
median (IQR) | (993–3571) | (1428–5923) | (1225–3158) | (1383–4286) |
Variables | Univariate | Multivariate * | ||
---|---|---|---|---|
Hazard Ratio | p Value | Adjusted Hazard Ratio | p Value | |
Beta-Blocker | 0.59 (0.35–1.00) | 0.048 | 0.55 (0.32–0.94) | 0.03 |
Age | 1.01 (1.00–1.02) | 0.259 | - | - |
Comorbidities | ||||
Hypertension | 1.41 (0.96–2.08) | 0.078 | - | - |
Diabetes | 0.98 (0.61–1.57) | 0.943 | - | - |
Chronic lung disease | 1.70 (0.99–2.90) | 0.051 | - | - |
Coronary heart disease | 1.61 (1.05–2.47) | 0.03 | 1.83 (1.18–2.83) | 0.007 |
Cerebrovascular disease | 1.10 (0.69–1.76) | 0.687 | - | - |
Source of infection | ||||
Pulmonary infection | 1.21 (0.83–1.79) | 0.319 | - | - |
Intraabdominal infection | 0.97 (0.64–1.47) | 0.884 | - | - |
Urinary infections | 0.75 (0.44–1.25) | 0.27 | - | - |
WBC | 0.99 (0.96–1.01) | 0.195 | - | - |
Lymphocytes | 1.02 (1.01–1.03) | <0.001 | 1.01 (1.00–1.03) | 0.153 |
PLT | 0.99 (0.99–1.00) | 0.008 | 1.00 (1.00–1.01) | 0.663 |
INR | 1.41 (1.14–1.74) | 0.001 | 1.27 (0.97–1.67) | 0.087 |
FIB | 1.00 (1.00–1.00) | <0.001 | 1.00 (1.00–1.00) | 0.04 |
DD | 1.00 (1.00–1.00) | 0.474 | - | - |
ALB | 0.93 (0.90–0.97) | 0.001 | 0.97 (0.93–1.01) | 0.178 |
Glucose | 1.02 (0.99–1.06) | 0.246 | - | - |
Bilirubin | 1.00 (1.00–1.00) | 0.435 | - | - |
Creatinine | 1.00 (1.00–1.00) | 0.081 | - | - |
SOFA score | 1.25 (1.19–1.31) | <0.001 | 1.22 (1.15–1.28) | <0.001 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ma, Y.; Ma, J.; Yang, J. Association between Pre-Existing Long-Term β-Blocker Therapy and the Outcomes of Sepsis-Associated Coagulopathy: A Retrospective Study. Medicina 2022, 58, 1843. https://doi.org/10.3390/medicina58121843
Ma Y, Ma J, Yang J. Association between Pre-Existing Long-Term β-Blocker Therapy and the Outcomes of Sepsis-Associated Coagulopathy: A Retrospective Study. Medicina. 2022; 58(12):1843. https://doi.org/10.3390/medicina58121843
Chicago/Turabian StyleMa, Ying, Jie Ma, and Jiong Yang. 2022. "Association between Pre-Existing Long-Term β-Blocker Therapy and the Outcomes of Sepsis-Associated Coagulopathy: A Retrospective Study" Medicina 58, no. 12: 1843. https://doi.org/10.3390/medicina58121843
APA StyleMa, Y., Ma, J., & Yang, J. (2022). Association between Pre-Existing Long-Term β-Blocker Therapy and the Outcomes of Sepsis-Associated Coagulopathy: A Retrospective Study. Medicina, 58(12), 1843. https://doi.org/10.3390/medicina58121843