The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Sepsis: Multiple Abnormalities, Heterogeneous Responses, and Evolving Understanding
Open accessAbstract
Sepsis represents the host's systemic inflammatory response to a severe infection. It causes substantial human morbidity resulting in hundreds of thousands of deaths each year. Despite decades of intense research, the basic mechanisms still remain elusive. In either experimental animal models of sepsis or human patients, there are substantial physiological changes, many of which may result in subsequent organ injury. Variations in age, gender, and medical comorbidities including diabetes and renal failure create additional complexity that influence the outcomes in septic patients. Specific system-based alterations, such as the coagulopathy observed in sepsis, offer both potential insight and possible therapeutic targets. Intracellular stress induces changes in the endoplasmic reticulum yielding misfolded proteins that contribute to the underlying pathophysiological changes. With these multiple changes it is difficult to precisely classify an individual's response in sepsis as proinflammatory or immunosuppressed. This heterogeneity also may explain why most therapeutic interventions have not improved survival. Given the complexity of sepsis, biomarkers and mathematical models offer potential guidance once they have been carefully validated. This review discusses each of these important factors to provide a framework for understanding the complex and current challenges of managing the septic patient. Clinical trial failures and the therapeutic interventions that have proven successful are also discussed.
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Cites
Safety, activity, and immune correlates of anti–PD-1 antibody in cancer
Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., Atkins, M. B., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200690 · Cited by 12,628
Early goal-directed therapy in the treatment of severe sepsis and septic shock
Rivers, E., Nguyen, B., Havstad, S., Ressler, J., Muzzin, A., Knoblich, B., Peterson, E., & Tomlanovich, M. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa010307 · Cited by 10,743
Surviving Sepsis Campaign: International Guidelines for Management of Severe Sepsis and Septic Shock
Dellinger, R. P., Levy, M. M., Rhodes, A., Annane, D., Gerlach, H., Opal, S. M., Sevransky, J. E., Sprung, C. L., Douglas, I. S., Jaeschke, R., et al. (2013) · Critical Care Medicine · doi:10.1097/ccm.0b013e31827e83af · Cited by 9,694
Kumar, A., Roberts, D., Wood, K. E., Light, B., Parrillo, J. E., Sharma, S., Suppes, R., Feinstein, D., Zanotti, S., Taiberg, L., et al. (2006) · Critical Care Medicine · doi:10.1097/01.ccm.0000217961.75225.e9 · Cited by 6,109
The epidemiology of sepsis in the United States from 1979 through 2000
Martin, G. S., Mannino, D. M., Eaton, S., & Moss, M. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa022139 · Cited by 5,841
Intensive versus Conventional Glucose Control in Critically Ill Patients
(2009) · New England Journal of Medicine · doi:10.1056/nejmoa0810625 · Cited by 5,119
Circulating mitochondrial DAMPs cause inflammatory responses to injury
Zhang, Q., Raoof, M., Chen, Y., Sumi, Y., Sursal, T., Junger, W., Brohi, K., Itagaki, K., & Hauser, C. J. (2010) · Nature · doi:10.1038/nature08780 · Cited by 3,812
Intensive insulin therapy in the medical ICU
Van den Berghe, G., Wilmer, A., Hermans, G., Meersseman, W., Wouters, P. J., Milants, I., Van Wijngaerden, E., Bobbaers, H., & Bouillon, R. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa052521 · Cited by 3,639
Naturally occurring antibodies devoid of light chains
Hamers-Casterman, C., Atarhouch, T., Muyldermans, S., Robinson, G., Hammers, C., Songa, E. B., Bendahman, N., & Hammers, R. (1993) · Nature · doi:10.1038/363446a0 · Cited by 3,241
Anti-cachectin/TNF monoclonal antibodies prevent septic shock during lethal bacteraemia
Tracey, K. J., Fong, Y., Hesse, D. G., Manogue, K. R., Lee, A. T., Kuo, G. C., Lowry, S. F., & Cerami, A. (1987) · Nature · doi:10.1038/330662a0 · Cited by 2,448
Cited by
The third international consensus definitions for sepsis and septic shock (Sepsis-3).
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. (2016) · JAMA · doi:10.1001/jama.2016.0287 · Cited by 28,250
Calfee, C. S., Delucchi, K., Parsons, P. E., Thompson, B. T., Ware, L. B., & Matthay, M. A. (2014) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(14)70097-9 · Cited by 1,544
Sepsis: Current Dogma and New Perspectives
Deutschman, C. S., & Tracey, K. J. (2014) · Immunity · doi:10.1016/j.immuni.2014.04.001 · Cited by 677
Liu, S., Wang, Z.-F., Su, Y.-S., Ray, R. S., Jing, X.-H., Wang, Y.-Q., & Ma, Q. (2020) · Neuron · doi:10.1016/j.neuron.2020.07.015 · Cited by 385
Endothelial barrier dysfunction in septic shock
Opal, S. M., & van der Poll, T. (2015) · Journal of Internal Medicine · doi:10.1111/joim.12331 · Cited by 353
Cytokine Storm—Definition, Causes, and Implications
Jarczak, D., & Nierhaus, A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231911740 · Cited by 304
Cholinergic modulation of the immune system presents new approaches for treating inflammation
Hoover, D. B. (2017) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2017.05.002 · Cited by 300
Pathologic function and therapeutic potential of exosomes in cardiovascular disease
Ailawadi, S., Wang, X., Gu, H., & Fan, G.-C. (2015) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2014.10.008 · Cited by 260
Hou, J., Zhang, J., Cui, P., Zhou, Y., Liu, C., Wu, X., Ji, Y., Wang, S., Cheng, B., Ye, H., et al. (2021) · Journal of Clinical Investigation · doi:10.1172/jci135197 · Cited by 239
Bioresponsive Nanoparticles Targeted to Infectious Microenvironments for Sepsis Management
Zhang, C. Y., Gao, J., & Wang, Z. (2018) · Advanced Materials · doi:10.1002/adma.201803618 · Cited by 222
Blood platelets and sepsis pathophysiology: A new therapeutic prospect in critical ill patients?
Dewitte, A., Lepreux, S., Villeneuve, J., Rigothier, C., Combe, C., Ouattara, A., & Ripoche, J. (2017) · Annals of Intensive Care · doi:10.1186/s13613-017-0337-7 · Cited by 194
The clinical importance of a cytokine network in the acute phase of sepsis
Matsumoto, H., Ogura, H., Shimizu, K., Ikeda, M., Hirose, T., Matsuura, H., Kang, S., Takahashi, K., Tanaka, T., & Shimazu, T. (2018) · Scientific Reports · doi:10.1038/s41598-018-32275-8 · Cited by 193
Cytokine removal in human septic shock: Where are we and where are we going?
Honore, P. M., Hoste, E., Molnár, Z., Jacobs, R., Joannes-Boyau, O., Malbrain, M. L. N. G., & Forni, L. G. (2019) · Annals of Intensive Care · doi:10.1186/s13613-019-0530-y · Cited by 192
Yan, M. Y., Gustad, L. T., & Nytrø, Ø. (2022) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab236 · Cited by 119
Sepsis prediction model for determining sepsis vs SIRS, qSOFA, and SOFA
Schertz, A. R., Lenoir, K. M., Bertoni, A. G., Levine, B. J., Mongraw-Chaffin, M., & Thomas, K. W. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.29729 · Cited by 78
Ibrahim, Y. F., Moussa, R. A., Bayoumi, A. M. A., & Ahmed, A.-S. F. (2020) · Inflammopharmacology · doi:10.1007/s10787-019-00628-y · Cited by 75
Comprehensive metabolic amino acid flux analysis in critically ill patients
Deutz, N. E. P., Singer, P., Wierzchowska-McNew, R. A., Viana, M. V., Ben-David, I. A., Pantet, O., Thaden, J. J., Ten Have, G. A. M., Engelen, M. P. K. J., & Berger, M. M. (2021) · Clinical Nutrition · doi:10.1016/j.clnu.2021.03.015 · Cited by 47
Metadata
- Authors
- Iskander, K. N., Osuchowski, M. F., Stearns-Kurosawa, D. J., Kurosawa, S., Stepien, D., Valentine, C., & Remick, D. G.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2013-07
- Volume
- 93
- Issue
- 3
- Pages
- 1247-1288
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W2142093121
- Cited by
- 453
- References
- 29
- FWCI
- 4.11
- Type
- journal article
- Language
- en
- Open access
- green
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