Secondary Logo

Share this article on:

Premise for Standardized Sepsis Models

Remick, Daniel G.*; Ayala, Alfred; Chaudry, Irshad H.; Coopersmith, Craig M.§; Deutschman, Clifford||; Hellman, Judith; Moldawer, Lyle**; Osuchowski, Marcin F.††

doi: 10.1097/SHK.0000000000001164
Editor's Choice

ABSTRACT Sepsis morbidity and mortality exacts a toll on patients and contributes significantly to healthcare costs. Preclinical models of sepsis have been used to study disease pathogenesis and test new therapies, but divergent outcomes have been observed with the same treatment even when using the same sepsis model. Other disorders such as diabetes, cancer, malaria, obesity, and cardiovascular diseases have used standardized, preclinical models that allow laboratories to compare results. Standardized models accelerate the pace of research and such models have been used to test new therapies or changes in treatment guidelines. The National Institutes of Health mandated that investigators increase data reproducibility and the rigor of scientific experiments and has also issued research funding announcements about the development and refinement of standardized models. Our premise is that refinement and standardization of preclinical sepsis models may accelerate the development and testing of potential therapeutics for human sepsis, as has been the case with preclinical models for other disorders. As a first step toward creating standardized models, we suggest standardizing the technical standards of the widely used cecal ligation and puncture model and creating a list of appropriate organ injury and immune dysfunction parameters. Standardized sepsis models could enhance reproducibility and allow comparison of results between laboratories and may accelerate our understanding of the pathogenesis of sepsis.

*Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, Massachusetts

Division of Surgical Research, Department of Surgery, Rhode Island Hospital, Alpert School of Medicine at Brown University, Providence, Rhode Island

Department of Surgery and Center for Surgical Research, University of Alabama at Birmingham, Birmingham, Alabama

§Department of Surgery and Emory Critical Care Center, Emory University School of Medicine, Atlanta, Georgia

||Department of Pediatrics and the Feinstein Institute for Medical Research, Northwell Health, Manhasset, New York

Department of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California, San Francisco, California

**Department of Surgery, University of Florida College of Medicine, Gainesville, Florida

††Ludwig Boltzmann Institute for Experimental and Clinical Traumatology in the AUVA Research Center, Vienna, Austria

Address reprint requests to Daniel G. Remick, MD, 670 Albany Street, Boston, MA 02118. E-mail:

Received 14 August, 2017

Revised 17 October, 2017

Accepted 11 April, 2018

Supported by T32GM86308 (DGR), R21AI112887 (DGR), R01 GM 117519 (DGR) R35 GM118097 (AA), DoD Contract #W911QY-15-C-0134 (IC), R01GM072808 (CMC), T32GM095442 (CMC), R01GM104323 (CMC), R01GM109779 (CMC), R01GM113228 (CMC), R01GM121102 (CSD), T32 GM008440 (JH), International Anesthesia Research Society FARA (JH), R01 GM-040586 (LM), P50 GM-111152 (LM), FWF Grant T707-B13 (MFO).

The authors report no conflicts of interest.

Back to Top | Article Outline


  • Standardized sepsis models should allow comparison of results between laboratories, increasing scientific integrity and directly addressing the data reproducibility mandate from the National Institutes of Health (NIH).
  • Standardized sepsis models should ensure that the heterogeneity in the response is due to the disease process, rather than technical differences between laboratories.
  • New investigators entering the field of sepsis, or new lab members, may be trained to standardized models to ensure data reproducibility.
  • Testing therapeutic interventions may proceed more quickly and reproducibly with standardized models.
  • Fewer experimental animals may be required when results could be compared with standardized models, as proposed for other preclinical models.
  • Defining appropriate organ injury and immune dysfunction parameters will allow consistent reporting of results, without dictating that those parameters need to be measured.
  • A web-based repository of results, such as Research Electronic Date Capture (REDCap), could be created for sharing information, and become an integral part of the resource sharing plan for grant applications.
  • Standardization should be applied to more than one sepsis model. No single sepsis model recapitulates the heterogeneity of sepsis, similar to how a single cancer model cannot replicate all cancer biology. For example, preclinical breast cancer models allowed the testing of antibodies directed against the epidermal growth factor receptor (Herceptin and Perjeta) which are now in routine clinical use. Although these revolutionary drugs will not reduce mortality in other types of cancer, they greatly improve survival in patients with certain types of breast cancer.
Back to Top | Article Outline


Sepsis imposes a substantial burden on society with an annual estimate of 31.5 million cases and 5.3 million deaths across the world (1). The mortality of sepsis has decreased in the past decade (2) although this may be due to sepsis being diagnosed earlier and more frequently (3). The 28-day mortality still remains above 20% even with optimal care (4), excess mortality continues after 28 days (5) and many sepsis survivors do not return to full function or paid employment (6, 7). More needs to be done beyond searching for the “magic bullet” that will cure sepsis (8). Standardized sepsis models may accelerate the discovery of disease pathways and testing of new therapies.

Back to Top | Article Outline


Numerous examples demonstrate that standardization, driven by checklists, provides better results in disciplines ranging from academic libraries (9) to clinical care (10). Checklists have been proposed to standardize animal experiments to improve rigor and reproducibility (11). Standardization has been applied to diseases such as diabetes, which has been investigated using more than one standardized model. For example, there are more than two dozen transgenic murine models of type I diabetes (12) and a “roadmap” was proposed to allow better interpretation of therapies for type I diabetes. Importantly, this roadmap did not suggest a single model. Table 1 provides examples of preclinical models that have been standardized or proposed for standardization (13–20). The NIH recognizes the need to develop standardized animal models to ensure reproducible results with several Research Funding Announcements addressing a range of diseases. For example, PAR-16-215 on developmental disorders specifically requests “.. . rigorous, controlled and standardized preclinical animal” (emphasis added).

Table 1

Table 1

There is value in standardizing preclinical models of disease, analogous to how standardization delivers better quality health care. Healthcare workers are in a unique position to understand the benefits of standardization. When they were surveyed about the benefits of animal research, respondents felt that results should be reproducible between laboratories (21). Despite the importance of standardization, an analysis of dozens of manuscripts found that the published methodology was not sufficient to verify standardization of the experiments (22). Standardized sepsis models would address these issues, allowing investigators to include a simple statement in the methods such as “The studies were performed using a standardized sepsis model,” and then detail if any modifications were incorporated.

The creation of a web-based repository of results, such as REDCap, could provide an additional benefit for sepsis studies. Investigators using preclinical models of epilepsy proposed creating a REDCap database with common design elements to allow harmonization of preclinical studies (13). One of the goals of the epilepsy proposal was to assist underpowered preclinical studies by providing a database for comparison. A REDCap database of sepsis results, such as changes in white blood cell counts, would centralize data to allow investigators quick access to data.

Back to Top | Article Outline


There have been initiatives to increase standardization and rigor in preclinical studies in other areas such as cardiovascular disease to increase the reproducibility of the results. A 2017 paper (23) analyzed the level of rigor in preclinical cardiovascular studies by examining nearly 30,000 published studies. The authors observed significant shortcomings in the description of experimental details and noted that the reporting had not improved over the last 10 years. The only cardiovascular preclinical studies showing improvement were in the area of stroke. A checklist for stroke studies has been published (14) resulting in the publication of higher quality science (24). Several authors have proposed checklists to standardize other animal models (11, 25).

The NIH has supported standardized approaches for conducting experiments and reporting results. The NIH has used the R funding mechanism to support studies to develop criteria for new models. For example, R01 HL126429 created a central IRB model called “IRBchoice” ( Another study was funded to determine the criteria when research results should be returned to patients (R21 HG00612). Despite not being hypothesis driven, both of these programs were supported to increase standardization. The NIH has also launched an initiative to improve the rigor of data and reproducibility of results (26, 27). Grant proposals are now expected to address data reproducibility in the research plan and a specific page needs to specify authentication of key resources. Even with these initiatives, NIH leaders have raised concerns about preclinical research and “subtle changes in protocol” (26). There was specific praise for the use of a checklist when reporting methodological details.

Back to Top | Article Outline


An important element of the premise is that preclinical models of disease will provide information that actually translates into better patient care. The literature was reviewed to determine if findings from preclinical models of disease have been reproduced in clinical trials. A review of 2,000 animal studies showed that 37% were replicated in subsequent human trials (28). While not all studies could be reproduced, there are notable successes when translating results from preclinical studies when standardized disease models were used (29–37) which are listed in Table 2. Included in this group are the Utstein criteria for resuscitation research (30, 31).

Table 2

Table 2

Back to Top | Article Outline


There has been robust discussion about the applicability of murine models of acute inflammation for the study of human disease. A high profile paper showing a lack of correlation of the gene signatures in mice and men after inflammatory insults (38) triggered vigorous debate (39). One rebuttal manuscript provided more than two dozen examples where animal models predicted the human responses to sepsis (29), including the failure of tumor necrosis factor (TNF) inhibitors for the treatment of sepsis before the clinical trials (40). A 2017 paper highlighted the heterogeneity in the cause of death among septic patients where a careful analysis showed that the majority of septic patients die from either refractory shock or changing to comfort care only (41). Standardized animal models should replicate the heterogeneity of human sepsis, and ensure that different responses are part of the septic response rather than differences in the technical aspects of the procedure to cause sepsis. Standardized sepsis models may also help identify specific subgroups who will benefit from therapeutic interventions (42).

A review of preclinical sepsis models concluded that sepsis models are heterogeneous, but standardization may reduce the observed differences between animal and human studies, enhancing translational value (43). This paper identified areas of concern including the duration of the experiment, monitoring of animals and use of supportive therapy, issues in virtually all preclinical sepsis models. Numerous examples demonstrate that lack of standardization leads to discordant results. The cecal ligation and puncture (CLP) is a widely used model of sepsis that has been used to test different therapies to improve survival (44, 45). Table 3 gives five examples where divergent results were obtained when testing a potential treatment option or examining the role of a specific molecule in the pathogenesis of the disease (46–55). For example, the role of the cannabinoid two receptor was examined using knockout mice. One study showed improved survival (from 20% to 60% (46)) while another showed a decline (from 60% to 20% (47)). There were two important variations in the CLP procedure that probably accounted for these differences. In wild-type mice, the higher mortality study used a larger gauge needle (20 vs. 23) and did not include postoperative warming or oxygen.

Table 3

Table 3

Table 3 demonstrates that models with low survival demonstrate better survival with different interventions, while high survival models show no benefit or a worse outcome, regardless of treatment. This survival-dependent benefit effect was previously described when evaluating either preclinical models or actual human sepsis studies (56).

Back to Top | Article Outline


The CLP model of sepsis was described 37 years ago in a landmark paper that has been cited more than 1,200 times (44). Despite the availability of this model there is tremendous variation in the CLP procedure resulting in different mortality, as highlighted in Table 3. It was proposed over 7 years ago that a standardized preclinical model of sepsis would accelerate the pace of discovery (43). That manuscript specifically showed that many animal models of sepsis do not include the administration of antibiotics, one of the most important elements in the treatment of sepsis. It is acknowledged that absolute reproducibility will probably not be achieved, even with a standardized model.

The CLP model of sepsis has also been criticized since source control (resecting the necrotic cecum (57) or peritoneal drainage) is typically not done although several investigators do a second procedure to remove the dead tissue (58, 59). However, with fluid resuscitation and appropriate antibiotics it is possible to have 20% lethality over 7 days (60) even without resection, resulting in mortality similar to patients. It is important to use a lower lethality model since it has the potential to discover both injurious pathways in the mice that die, as well as protective pathways in the mice that live. A clinical scoring system that predicts mortality in the standardized model will identify mice several hours prior to their death to allow careful dissection of the pathways that lead to organ injury or immune dysfunction. Such sepsis scoring systems have previously been published (61–63). Additionally, physiological monitoring (64) may also be included to identify animals at risk of death (65) in addition to well-described plasma biomarkers (61, 66, 67). The premise for standardized sepsis models is that such models will embrace the inherent heterogeneity of the host response to infection, even when treated with appropriate antibiotic therapy and fluid resuscitation (68, 69). Standardized models may also identify subgroups who respond to treatment (42).

Therapies effective in standardized sepsis models may be more easily translated into the clinical arena, since an inappropriate model does not translate into better patient care. As one specific example, findings from an animal model led to the development of antibodies to TNF for the treatment of sepsis (70). The original model was a non-human primate, acute bacteremia model where blocking TNFα improved survival. In subsequent large-scale clinical studies, TNFα inhibitors were not effective, since the animal model did not recapitulate the human disease. However, when the CLP model of sepsis was used, antibodies to TNFα were not effective. These results were published in 1992 (71), more than 3 years before clinical trials reported that blockade of TNFα did not improve survival (72). The murine study also showed that the TNFα inhibitor accelerated mortality, foreshadowing one clinical trial where TNF inhibition actually increased mortality in patients (73).

Back to Top | Article Outline


We recognize that some investigators will not embrace developing standardized models. Grant and journal reviewers may consider that studies done using a non-standardized model are not valid. This concern could be easily rebutted by providing information in the methods about how the model differs from the standard with an explanation for the deviation. Some regulatory agencies may not approve experiments if they do not conform to the standardized model. However, the availability of standardized protocols should streamline approvals when using that model. If not using a standardized model, the deviations could be clearly delineated, which is not a significant change from current approval processes. The changes from standardized models will also be easier to defend since there is a clear standard for comparison. The initial standardized models will probably not include comorbid conditions such as diabetes or advanced age which are frequently found in patients (68, 69). A standardized model actually makes subsequent models easier to develop and implement, since there will be baseline for comparison. Investigators may be concerned about the cost of measuring the parameters to document organ injury. Standardized models would not dictate that every parameter be measured, but they would provide guidelines.

Back to Top | Article Outline


Development of standardized sepsis models would be a first step toward improving preclinical sepsis experiments so that the model more closely recapitulates the heterogeneity of human sepsis. We propose developing two sets of criteria for standardized sepsis models, starting with the CLP model of sepsis. The first set would consist of standardizing the technical elements for the model, since technical differences resulting in different mortality have been well described by several laboratories (44, 57, 74). Despite these prior publications, there is still wide variation in how this model is actually used, as highlighted in Table 3. As a starting point, we propose discussing the technical elements listed in Table 4 to reach consensus. It should be noted that these technical elements such as resuscitation would also be applicable to preclinical studies with larger animals such as sheep or pigs (69).The second criteria are probably more important, and would describe the parameters that should be measured to document organ injury or the dysregulated response to infection. These parameters are listed in Table 5 and would be measured regardless of the sepsis model. This table lists the different organs and immune functions that should be evaluated, with the understanding that not every study would need to measure all parameters. As an example, we anticipate that the recommendations would follow previously published guidelines, such as the American Thoracic Society guidelines on measurements of acute lung injury (75).

Table 4

Table 4

Table 5

Table 5

We would envision a series of white papers with recommendations for standardized sepsis models. These standardized sepsis models represent an important initial stage of increasing the reproducibility of sepsis science, leading to the development and implementation of better therapies to address this lethal disease.

Back to Top | Article Outline


1. Fleischmann C, Scherag A, Adhikari NK, Hartog CS, Tsaganos T, Schlattmann P, Angus DC, Reinhart K. International Forum of Acute Care TrialistsAssessment of global incidence and mortality of hospital-treated sepsis. Current estimates and limitations. Am J Respir Crit Care Med 2016; 193 3:259–272.
2. Stevenson EK, Rubenstein AR, Radin GT, Wiener RS, Walkey AJ. Two decades of mortality trends among patients with severe sepsis: a comparative meta-analysis. Crit Care Med 2014; 42 3:625–631.
3. Sjoding MW, Prescott HC, Wunsch H, Iwashyna TJ, Cooke CR. Longitudinal changes in ICU admissions among elderly patients in the United States. Crit Care Med 2016; 44 7:1353–1360.
4. Seymour CW, Gesten F, Prescott HC, Friedrich ME, Iwashyna TJ, Phillips GS, Lemeshow S, Osborn T, Terry KM, Levy MM. Time to treatment and mortality during mandated emergency care for sepsis. N Engl J Med 2017; 376:2235–2244.
5. Prescott HC, Osterholzer JJ, Langa KM, Angus DC, Iwashyna TJ. Late mortality after sepsis: Propensity matched cohort study. BMJ 2016; 353:i2375.
6. Odden AJ, Rohde JM, Bonham C, Kuhn L, Malani PN, Chen LM, Flanders SA, Iwashyna TJ. Functional outcomes of general medical patients with severe sepsis. BMC Infect Dis 2013; 13:588.
7. Prescott HC, Langa KM, Liu V, Escobar GJ, Iwashyna TJ. Increased 1-year healthcare use in survivors of severe sepsis. Am J Respir Crit Care Med 2014; 190 1:62–69.
8. Headley P, Russell C. A magic bullet for sepsis—a needle in a haystack or barking up the wrong tree. Surgery 2015; 33 11:521–527.
9. England L, Fu L, Miller S. Checklist manifesto for electronic resources: getting ready for the fiscal year and beyond. J Electron Resources Librarianship 2011; 23 4:307–326.
10. Duff P. A simple checklist for preventing major complications associated with cesarean delivery. Obstet Gynecol 2010; 116 6:1393–1396.
11. van der Worp HB, Howells DW, Sena ES, Porritt MJ, Rewell S, O’Collins V, Macleod MR. Can animal models of disease reliably inform human studies? PLoS Med 2010; 7 3:e1000245.
12. Roep BO, Atkinson M, von Herrath M. Satisfaction (not) guaranteed: re-evaluating the use of animal models of type 1 diabetes. Nat Rev Immunol 2004; 4 12:989–997.
13. Lapinlampi N, Melin E, Aronica E, Bankstahl JP, Becker A, Bernard C, Gorter JA, Gröhn O, Lipsanen A, Lukasiuk K, et al. Common data elements and data management: remedy to cure underpowered preclinical studies. Epilepsy Res 2017; 129:87–90.
14. Vahidy F, Schabitz WR, Fisher M, Aronowski J. Reporting standards for preclinical studies of stroke therapy. Stroke 2016; 47 10:2435–2438.
15. Craig AG, Grau GE, Janse C, Kazura JW, Milner D, Barnwell JW, Turner G. Langhorne J and participants of the Hinxton Retreat meeting on Animal Models for Research on Severe MThe role of animal models for research on severe malaria. PLoS Pathog 2012; 8 2:e1002401.
16. King A, Bowe J. Animal models for diabetes: Understanding the pathogenesis and finding new treatments. Biochem Pharmacol 2016; 99:1–10.
17. Auer JA, Goodship A, Arnoczky S, Pearce S, Price J, Claes L, von Rechenberg B, Hofmann-Amtenbrinck M, Schneider E, Müller-Terpitz R, et al. Refining animal models in fracture research: seeking consensus in optimising both animal welfare and scientific validity for appropriate biomedical use. BMC Musculoskelet Disord 2007; 8:72.
18. Rice AS, Cimino-Brown D, Eisenach JC, Kontinen VK, Lacroix-Fralish ML, Machin I, Preclinical Pain C, Mogil JS, Stohr T. Animal models and the prediction of efficacy in clinical trials of analgesic drugs: a critical appraisal and call for uniform reporting standards. Pain 2008; 139 2:243–247.
19. Nilsson C, Raun K, Yan FF, Larsen MO, Tang-Christensen M. Laboratory animals as surrogate models of human obesity. Acta Pharmacol Sin 2012; 33 2:173–181.
20. Getz GS, Reardon CA. Animal models of atherosclerosis. Arterioscler Thromb Vasc Biol 2012; 32:1104–1115.
21. Joffe AR, Bara M, Anton N, Nobis N. Expectations for methodology and translation of animal research: a survey of health care workers. BMC Med Ethics 2015; 16:29.
22. Bara M, Joffe AR. The methodological quality of animal research in critical care: the public face of science. Ann Intensive Care 2014; 4:26.
23. Ramirez FD, Motazedian P, Jung RG, Di Santo P, MacDonald ZD, Moreland R, Simard T, Clancy AA, Russo JJ, Welch VA, et al. Methodological rigor in preclinical cardiovascular studies: targets to enhance reproducibility and promote research translation. Circ Res 2017; 120:1916–1926.
24. Minnerup J, Zentsch V, Schmidt A, Fisher M, Schabitz WR. Methodological quality of experimental stroke studies published in the stroke journal: time trends and effect of the basic science checklist. Stroke 2016; 47 1:267–272.
25. Sams-Dodd F. Strategies to optimize the validity of disease models in the drug discovery process. Drug Discov Today 2006; 11 (7–8):355–363.
26. Collins FS, Tabak LA. Policy: NIH plans to enhance reproducibility. Nature 2014; 505 7485:612–613.
27. Hsieh T, Vaickus MH, Remick DG. Enhancing scientific foundations to ensure reproducibility: a new paradigm. Am J Pathol 2018; 188 1:6–10.
28. Hackam DG, Redelmeier DA. Translation of research evidence from animals to humans. JAMA 2006; 296 14:1731–1732.
29. Osuchowski MF, Remick DG, Lederer JA, Lang CH, Aasen AO, Aibiki M, Azevedo LC, Bahrami S, Boros M, Cooney R, et al. Abandon the mouse research ship? Not just yet! Shock 2014; 41 6:463–475.
30. Idris AH, Becker LB, Ornato JP, Hedges JR, Bircher NG, Chandra NC, Cummins RO, Dick W, Ebmeyer U, Halperin HR, et al. Utstein-style guidelines for uniform reporting of laboratory CPR research. A statement for healthcare professionals from a task force of the American Heart Association, the American College of Emergency Physicians, the American College of Cardiology, the European Resuscitation Council, the Heart and Stroke Foundation of Canada, the Institute of Critical Care Medicine, the Safar Center for Resuscitation Research, and the Society for Academic Emergency Medicine. Writing Group. Circulation 1996; 94 9:2324–2336.
31. Idris AH, Becker LB, Wenzel V, Fuerst RS, Gravenstein N. Lack of uniform definitions and reporting in laboratory models of cardiac arrest: a review of the literature and a proposal for guidelines. Ann Emerg Med 1994; 23 1:9–16.
32. Torres VE, Harris PC. Polycystic kidney disease: genes, proteins, animal models, disease mechanisms and therapeutic opportunities. J Intern Med 2007; 261 1:17–31.
33. Ortiz A, Sanchez-Niño MD, Izquierdo MC, Martin-Cleary C, Garcia-Bermejo L, Moreno JA, Ruiz-Ortega M, Draibe J, Cruzado JM, Garcia-Gonzalez MA, et al. Translational value of animal models of kidney failure. Eur J Pharmacol 2015; 759:205–220.
34. Picard C, Burtey S, Bornet C, Curti C, Montana M, Vanelle P. Pathophysiology and treatment of typical and atypical hemolytic uremic syndrome. Pathol Biol (Paris) 2015; 63 3:136–143.
35. Cofiell R, Kukreja A, Bedard K, Yan Y, Mickle AP, Ogawa M, Bedrosian CL, Faas SJ. Eculizumab reduces complement activation, inflammation, endothelial damage, thrombosis, and renal injury markers in aHUS. Blood 2015; 125 21:3253–3262.
36. Zhang L, Qiu W, Crooke S, Li Y, Abid A, Xu B, Finn MG, Lin F. Development of autologous C5 vaccine nanoparticles to reduce intravascular hemolysis in vivo. ACS Chem Biol 2017; 12 2:539–547.
37. Cummins RO, Chamberlain D, Hazinski MF, Nadkarni V, Kloeck W, Kramer E, Becker L, Robertson C, Koster R, Zaritsky A, et al. Recommended guidelines for reviewing, reporting, and conducting research on in-hospital resuscitation: the in-hospital ’Utstein style’. American Heart Association. Circulation 1997; 95 8:2213–2239.
38. Seok J, Warren HS, Cuenca AG, Mindrinos MN, Baker HV, Xu W, Richards DR, McDonald-Smith GP, Gao H, Hennessy L, et al. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci U S A 2013; 110 9:3507–3512.
39. Remick D. Use of animal models for the study of human disease-a shock society debate. Shock 2013; 40 4:345–346.
40. Remick D, Manohar P, Bolgos G, Rodriguez J, Moldawer L, Wollenberg G. Blockade of tumor necrosis factor reduces lipopolysaccharide lethality, but not the lethality of cecal ligation and puncture. Shock 1995; 4 2:89–95.
41. Moskowitz A, Omar Y, Chase M, Lokhandwala S, Patel P, Andersen LW, Cocchi MN, Donnino MW. Reasons for death in patients with sepsis and septic shock. J Crit Care 2017; 38:284–288.
42. Osuchowski MF, Connett J, Welch K, Granger J, Remick DG. Stratification is the key: Inflammatory biomarkers accurately direct immunomodulatory therapy in experimental sepsis. Crit Care Med 2009; 37:1567–1573.
43. Dyson A, Singer M. Animal models of sepsis: why does preclinical efficacy fail to translate to the clinical setting? Crit Care Med 2009; 37 (1 suppl):S30–S37.
44. Wichterman KA, Baue AE, Chaudry IH. Sepsis and septic shock—a review of laboratory models and a proposal. J Surg Res 1980; 29:189–201.
45. Chang R, Holcomb JB, Johansson PI, Pati S, Schreiber MA, Wade CE. Plasma resuscitation improved survival in a cecal ligation and puncture rat model of sepsis. Shock 2018; 49:53–61.
46. Csoka B, Németh ZH, Mukhopadhyay P, Spolarics Z, Rajesh M, Federici S, Deitch EA, Bátkai S, Pacher P, Haskó G. CB2 cannabinoid receptors contribute to bacterial invasion and mortality in polymicrobial sepsis. PLoS One 2009; 4 7:e6409.
47. Tschop J, Kasten KR, Nogueiras R, Goetzman HS, Cave CM, England LG, Dattilo J, Lentsch AB, Tschöp MH, Caldwell CC. The cannabinoid receptor 2 is critical for the host response to sepsis. J Immunol 2009; 183 1:499–505.
48. Benjamim CF, Canetti C, Cunha FQ, Kunkel SL, Peters-Golden M. Opposing and hierarchical roles of leukotrienes in local innate immune versus vascular responses in a model of sepsis. J Immunol 2005; 174 3:1616–1620.
49. Rios-Santos F, Benjamim CF, Zavery D, Ferreira SH, Cunha Fde Q. A critical role of leukotriene B4 in neutrophil migration to infectious focus in cecal ligaton and puncture sepsis. Shock 2003; 19 1:61–65.
50. Nullens S, Staessens M, Peleman C, Plaeke P, Malhotra-Kumar S, Francque S, De Man JG, De Winter BY. Beneficial effects of anti-interleukin-6 antibodies on impaired gastrointestinal motility, inflammation and increased colonic permeability in a murine model of sepsis are most pronounced when administered in a preventive setup. PLoS One 2016; 11 4:e0152914.
51. Vyas D, Javadi P, Dipasco PJ, Buchman TG, Hotchkiss RS, Coopersmith CM. Early antibiotic administration but not antibody therapy directed against IL-6 improves survival in septic mice predicted to die on basis of high IL-6 levels. Am J Physiol Regul Integr Comp Physiol 2005; 289 4:R1048–R1053.
52. Ozer EK, Goktas MT, Kilinc I, Bariskaner H, Ugurluoglu C, Iskit AB. Celecoxib administration reduced mortality, mesenteric hypoperfusion, aortic dysfunction and multiple organ injury in septic rats. Biomed Pharmacother 2017; 86:583–589.
53. Fredenburgh LE, Velandia MM, Ma J, Olszak T, Cernadas M, Englert JA, Chung SW, Liu X, Begay C, Padera RF, et al. Cyclooxygenase-2 deficiency leads to intestinal barrier dysfunction and increased mortality during polymicrobial sepsis. J Immunol 2011; 187 10:5255–5267.
54. Belikoff BG, Hatfield S, Georgiev P, Ohta A, Lukashev D, Buras JA, Remick DG, Sitkovsky M. A2B adenosine receptor blockade enhances macrophage-mediated bacterial phagocytosis and improves polymicrobial sepsis survival in mice. J Immunol 2011; 186 4:2444–2453.
55. Csoka B, Németh ZH, Mukhopadhyay P, Spolarics Z, Rajesh M, Federici S, Deitch EA, Bátkai S, Pacher P, Haskó G. A2B adenosine receptors protect against sepsis-induced mortality by dampening excessive inflammation. J Immunol 2010; 185 1:542–550.
56. Eichacker PQ, Parent C, Kalil A, Esposito C, Cui X, Banks SM, Gerstenberger EP, Fitz Y, Danner RL, Natanson C. Risk and the efficacy of antiinflammatory agents: retrospective and confirmatory studies of sepsis. Am J Respir Crit Care Med 2002; 166 9:1197–1205.
57. Alverdy JC, Krezalek MA. Collapse of the microbiome, emergence of the pathobiome, and the immunopathology of sepsis. Crit Care Med 2017; 45:337–347.
58. Hubbard WJ, Choudhry M, Schwacha MG, Kerby JD, Rue LW 3rd, Bland KI, Chaudry IH. Cecal ligation and puncture. Shock 2005; 24 (suppl 1):52–57.
59. Wu R, Dong W, Zhou M, Zhang F, Marini CP, Ravikumar TS, Wang P. Ghrelin attenuates sepsis-induced acute lung injury and mortality in rats. Am J Respir Crit Care Med 2007; 176 8:805–813.
60. Iskander KN, Vaickus M, Duffy ER, Remick DG. Shorter duration of post-operative antibiotics for cecal ligation and puncture does not increase inflammation or mortality. PLoS One 2016; 11 9:e0163005.
61. Remick DG, Bolgos GR, Siddiqui J, Shin J, Nemzek JA. Six at six: interleukin-6 measured 6 h after the initiation of sepsis predicts mortality over 3 days. Shock 2002; 17 6:463–467.
62. Huet O, Ramsey D, Miljavec S, Jenney A, Aubron C, Aprico A, Stefanovic N, Balkau B, Head GA, de Haan JB, et al. Ensuring animal welfare while meeting scientific aims using a murine pneumonia model of septic shock. Shock 2013; 39 6:488–494.
63. Shrum B, Anantha RV, Xu SX, Donnelly M, Haeryfar SM, McCormick JK, Mele T. A robust scoring system to evaluate sepsis severity in an animal model. BMC Res Notes 2014; 7:233.
64. Mella JR, Chiswick E, Stepien D, Moitra R, Duffy ER, Stucchi A, Remick D. Antagonism of the neurokinin-1 receptor improves survival in a mouse model of sepsis by decreasing inflammation and increasing early cardiovascular function. Crit Care Med 2017; 45 2:e213–e221.
65. Lewis AJ, Yuan D, Zhang X, Angus DC, Rosengart MR, Seymour CW. Use of biotelemetry to define physiology-based deterioration thresholds in a murine cecal ligation and puncture model of sepsis. Crit Care Med 2016; 44 6:e420–e431.
66. Chiswick EL, Mella JR, Bernardo J, Remick DG. Acute-phase deaths from murine polymicrobial sepsis are characterized by innate immune suppression rather than exhaustion. J Immunol 2015; 195 8:3793–3802.
67. Turnbull IR, Javadi P, Buchman TG, Hotchkiss RS, Karl IE, Coopersmith CM. Antibiotics improve survival in sepsis independent of injury severity but do not change mortality in mice with markedly elevated interleukin 6 levels. Shock 2004; 21 2:121–125.
68. Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med 2013; 369 9:840–851.
69. Traber DL. Expired nitric oxide and shock in higher order species. Crit Care Med 1999; 27 2:255–256.
70. Tracey KJ, Fong Y, Hesse DG, Manogue KR, Lee AT, Kuo GC, Lowry SF, Cerami A. Anti-cachectin/TNF monoclonal antibodies prevent septic shock during lethal bacteraemia. Nature 1987; 330:662–664.
71. Eskandari MK, Bolgos G, Miller C, Nguyen DT, DeForge LE, Remick DG. Anti-tumor necrosis factor antibody therapy fails to prevent lethality after cecal ligation and puncture or endotoxemia. J Immunol 1992; 148 9:2724–2730.
72. Abraham E, Wunderink R, Silverman H, Perl TM, Nasraway S, Levy H, Bone R, Wenzel RP, Balk R, Allred R, et al. Efficacy and safety of monoclonal antibody to human tumor necrosis factor alpha in patients with sepsis syndrome. A randomized, controlled, double-blind, multicenter clinical trial. TNF-alpha MAb Sepsis Study Group. JAMA 1995; 273:934–941.
73. Fisher CJ Jr, Agosti JM, Opal SM, Lowry SF, Balk RA, Sadoff JC, Abraham E, Schein RM, Benjamin E. Treatment of septic shock with the tumor necrosis factor receptor:Fc fusion protein. The Soluble TNF Receptor Sepsis Study Group. N Engl J Med 1996; 334 26:1697–1702.
74. Ebong S, Call D, Nemzek J, Bolgos G, Newcomb D, Remick D. Immunopathologic alterations in murine models of sepsis of increasing severity. Infect Immun 1999; 67 12:6603–6610.
75. Matute-Bello G, Downey G, Moore BB, Groshong SD, Matthay MA, Slutsky AS, Kuebler WM. Acute Lung Injury in Animals Study GAn official American Thoracic Society workshop report: features and measurements of experimental acute lung injury in animals. Am J Respir Cell Mol Biol 2011; 44 5:725–738.

Animal models; guidelines; reproducibility

© 2019 by the Shock Society