1
|
Vahdatpour C, Collins D and Goldberg S: Cardiogenic shock. J Am Heart Assoc. 8(e011991)2019.PubMed/NCBI View Article : Google Scholar
|
2
|
van Diepen S, Katz JN, Albert NM, Henry TD, Jacobs AK, Kapur NK, Kilic A, Menon V, Ohman EM, Sweitzer NK, et al: Contemporary management of cardiogenic shock: A scientific statement from the American heart association. Circulation. 136:e232–e268. 2017.PubMed/NCBI View Article : Google Scholar
|
3
|
Goldberg RJ, Makam RCP, Yarzebski J, McManus DD, Lessard D and Gore JM: Decade-long trends (2001-2011) in the incidence and hospital death rates associated with the in-hospital development of cardiogenic shock after acute myocardial infarction. Circ Cardiovasc Qual Outcomes. 9:117–125. 2016.PubMed/NCBI View Article : Google Scholar
|
4
|
Bahtouee M, Eghbali SS, Maleki N, Rastgou V and Motamed N: Acute physiology and chronic health evaluation II score for the assessment of mortality prediction in the intensive care unit: A single-centre study from Iran. Nurs Crit Care. 24:375–380. 2019.PubMed/NCBI View Article : Google Scholar
|
5
|
Alizadeh AM, Hassanian-Moghaddam H, Shadnia S, Zamani N and Mehrpour O: Simplified acute physiology score II/acute physiology and chronic health evaluation II and prediction of the mortality and later development of complications in poisoned patients admitted to intensive care unit. Basic Clin Pharmacol Toxicol. 115:297–300. 2014.PubMed/NCBI View Article : Google Scholar
|
6
|
Miller RJH, Southern D, Wilton SB, James MT, Har B, Schnell G, van Diepen S and Grant ADM: Comparative prognostic accuracy of risk prediction models for cardiogenic shock. J Intensive Care Med. 35:1513–1519. 2020.PubMed/NCBI View Article : Google Scholar
|
7
|
Harjola VP, Lassus J, Sionis A, Køber L, Tarvasmäki T, Spinar J, Parissis J, Banaszewski M, Silva-Cardoso J, Carubelli V, et al: Clinical picture and risk prediction of short-term mortality in cardiogenic shock. Eur J Heart Fail. 17:501–509. 2015.PubMed/NCBI View Article : Google Scholar
|
8
|
Pöss J, Köster J, Fuernau G, Eitel I, de Waha S, Ouarrak T, Lassus J, Harjola VP, Zeymer U, Thiele H and Desch S: Risk stratification for patients in cardiogenic shock after acute myocardial infarction. J Am Coll Cardiol. 69:1913–1920. 2017.PubMed/NCBI View Article : Google Scholar
|
9
|
Sleeper LA, Reynolds HR, White HD, Webb JG, Dzavík V and Hochman JS: A severity scoring system for risk assessment of patients with cardiogenic shock: A report from the SHOCK trial and registry. Am Heart J. 160:443–450. 2010.PubMed/NCBI View Article : Google Scholar
|
10
|
Charlson M, Szatrowski TP, Peterson J and Gold J: Validation of a combined comorbidity index. J Clin Epidemiol. 47:1245–1251. 1994.PubMed/NCBI View Article : Google Scholar
|
11
|
Lin JX, Huang YQ, Xie JW, Wang JB, Lu J, Chen QY, Cao LL, Lin M, Tu R, Huang ZN, et al: Association of the age-adjusted Charlson comorbidity index and systemic inflammation with survival in gastric cancer patients after radical gastrectomy. Eur J Surg Oncol. 45:2465–2472. 2019.PubMed/NCBI View Article : Google Scholar
|
12
|
Jiang L, Chou ACC, Nadkarni N, Ng CEQ, Chong YS, Howe TS and Koh JSB: Charlson comorbidity index predicts 5-year survivorship of surgically treated hip fracture patients. Geriatr Orthop Surg Rehabil. 9(2151459318806442)2018.PubMed/NCBI View Article : Google Scholar
|
13
|
Stavem K, Hoel H, Skjaker SA and Haagensen R: Charlson comorbidity index derived from chart review or administrative data: Agreement and prediction of mortality in intensive care patients. Clin Epidemiol. 9:311–320. 2017.PubMed/NCBI View Article : Google Scholar
|
14
|
Minol JP, Dimitrova V, Petrov G, Langner R, Boeken U, Rellecke P, Aubin H, Kamiya H, Sixt S, Huhn R, et al: The age-adjusted Charlson comorbidity index in minimally invasive mitral valve surgery. Eur J Cardiothorac Surg. 56:1124–1130. 2019.PubMed/NCBI View Article : Google Scholar
|
15
|
Charlson ME, Carrozzino D, Guidi J and Patierno C: Charlson comorbidity index: A critical review of clinimetric properties. Psychother Psychosom. 91:8–35. 2022.PubMed/NCBI View Article : Google Scholar
|
16
|
Johnson Alistair, Bulgarelli Lucas, Pollard Tom, Horng Steven, Celi Leo Anthony and Roger Mark: MIMIC-IV (version 2.0). Available from: https://doi.org/10.13026/7vcr-e114.
|
17
|
World Health Organization (WHO). International classification of diseases: [9th] ninth revision, basic tabulation list with alphabetic index. WHO, Geneva, 1978. https://apps.who.int/iris/handle/10665/39473.
|
18
|
World Health Organization (WHO). International statistical classification of diseases and related health problems. 10th revision. 5th edition. WHO, Geneva, 2016. https://apps.who.int/iris/handle/10665/246208.
|
19
|
Chang CM, Yin WY, Wei CK, Wu CC, Su YC, Yu CH and Lee CC: Adjusted age-adjusted charlson comorbidity index score as a risk measure of perioperative mortality before cancer surgery. PLoS One. 11(e0148076)2016.PubMed/NCBI View Article : Google Scholar
|
20
|
Saji M, Katz MR, Ailawadi G, Fowler DE, Ragosta M and Lim DS: Predictive value of age-adjusted charlson co-morbidity index for 1-, 3-, and 5-year mortality in patients requiring transcatheter mitral valve repair. Am J Cardiol. 120:309–314. 2017.PubMed/NCBI View Article : Google Scholar
|
21
|
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC and Vandenbroucke JP: The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Lancet. 370:1453–1457. 2007.PubMed/NCBI View Article : Google Scholar
|
22
|
Yu X, Chen J, Li Y, Liu H, Hou C, Zeng Q, Cui Y, Zhao L, Li P, Zhou Z, et al: Threshold effects of moderately excessive fluoride exposure on children's health: A potential association between dental fluorosis and loss of excellent intelligence. Environ Int. 118:116–124. 2018.PubMed/NCBI View Article : Google Scholar
|
23
|
Kong X, Huang X, Zhao M, Xu B, Xu R, Song Y, Yu Y, Yang W, Zhang J, Liu L, et al: Platelet count affects efficacy of folic acid in preventing first stroke. J Am Coll Cardiol. 71:2136–2146. 2018.PubMed/NCBI View Article : Google Scholar
|
24
|
Park SY, Freedman ND, Haiman CA, Le Marchand L, Wilkens LR and Setiawan VW: Association of coffee consumption with total and cause-specific mortality among nonwhite populations. Ann Intern Med. 167:228–235. 2017.PubMed/NCBI View Article : Google Scholar
|
25
|
Barssoum K, Patel HP, Abdelmaseih R, Hassib M, Victor V, Mohamed A, Jazar DA, Mai S, Ibrahim F, Patel B, et al: Characteristics and outcomes of early vs late initiation of mechanical circulatory support in non-acute myocardial infarction related cardiogenic shock: An analysis of the national inpatient sample database. Curr Probl Cardiol. 48(101584)2023.PubMed/NCBI View Article : Google Scholar
|
26
|
Assali AR, Iakobishvili Z, Zafrir N, Solodky A, Teplitsky I, Rechavia E, Butto N, Shor N, Hasdai D, Fuchs S, et al: Characteristics and clinical outcomes of patients with cardiogenic shock complicating acute myocardial infarction treated by emergent coronary angioplasty. Int J Cardiovasc Intervent. 7:193–198. 2005.PubMed/NCBI View Article : Google Scholar
|
27
|
Lee SI, Koh Y, Huh JW, Hong SB and Lim CM: Factors and outcomes of intensive care unit readmission in elderly patients. Gerontology. 68:280–288. 2022.PubMed/NCBI View Article : Google Scholar
|
28
|
Wang Y, Yuan M, Ma Y, Shao C, Wang Y, Qi M, Ren B and Gao D: The admission (Neutrophil+Monocyte)/lymphocyte ratio is an independent predictor for in-hospital mortality in patients with acute myocardial infarction. Front Cardiovasc Med. 9(870176)2022.PubMed/NCBI View Article : Google Scholar
|
29
|
Feng M, McSparron JI, Kien DT, Stone DJ, Roberts DH, Schwartzstein RM, Vieillard-Baron A and Celi LA: Transthoracic echocardiography and mortality in sepsis: Analysis of the MIMIC-III database. Intensive Care Med. 44:884–892. 2018.PubMed/NCBI View Article : Google Scholar
|
30
|
Chen H, Zhu Z, Zhao C, Guo Y, Chen D, Wei Y and Jin J: Central venous pressure measurement is associated with improved outcomes in septic patients: An analysis of the MIMIC-III database. Crit Care. 24(433)2020.PubMed/NCBI View Article : Google Scholar
|
31
|
Feinstein AR: The pre-therapeutic classification of co-morbidity in chronic disease. J Chronic Dis. 23:455–468. 1970.PubMed/NCBI View Article : Google Scholar
|
32
|
Charlson ME, Pompei P, Ales KL and MacKenzie CR: A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis. 40:373–383. 1987.PubMed/NCBI View Article : Google Scholar
|
33
|
Wu CC, Hsu TW, Chang CM, Yu CH and Lee CC: Age-adjusted Charlson comorbidity index scores as predictor of survival in colorectal cancer patients who underwent surgical resection and chemoradiation. Medicine (Baltimore). 94(e431)2015.PubMed/NCBI View Article : Google Scholar
|
34
|
Yang CC, Fong Y, Lin LC, Que J, Ting WC, Chang CL, Wu HM, Ho CH, Wang JJ and Huang CI: The age-adjusted Charlson comorbidity index is a better predictor of survival in operated lung cancer patients than the Charlson and Elixhauser comorbidity indices. Eur J Cardiothorac Surg. 53:235–240. 2018.PubMed/NCBI View Article : Google Scholar
|
35
|
Hoang TH, Maiskov VV, Merai IA and Kobalava ZD: Development and validation of a model for predicting 18-month mortality in type 2 myocardial infarction. Am J Emerg Med. 48:224–230. 2021.PubMed/NCBI View Article : Google Scholar
|
36
|
Shebeshi DS, Dolja-Gore X and Byles J: Charlson Comorbidity index as a predictor of repeated hospital admission and mortality among older women diagnosed with cardiovascular disease. Aging Clin Exp Res. 33:2873–2878. 2021.PubMed/NCBI View Article : Google Scholar
|
37
|
Hsu YT, He YT, Ting CK, Tsou MY, Tang GJ and Pu C: Administrative and claims data help predict patient mortality in intensive care units by logistic regression: A nationwide database study. Biomed Res Int. 2020(9076739)2020.PubMed/NCBI View Article : Google Scholar
|
38
|
Hadique S, Culp S, Sangani RG, Chapman KD, Khan S, Parker JE and Moss AH: Derivation and validation of a prognostic model to predict 6-month mortality in an intensive care unit population. Ann Am Thorac Soc. 14:1556–1561. 2017.PubMed/NCBI View Article : Google Scholar
|
39
|
Radovanovic D, Seifert B, Urban P, Eberli FR, Rickli H, Bertel O, Puhan MA and Erne P: Validity of Charlson Comorbidity index in patients hospitalised with acute coronary syndrome. Insights from the nationwide AMIS Plus registry 2002-2012. Heart. 100:288–294. 2014.PubMed/NCBI View Article : Google Scholar
|
40
|
Jepma P, Verweij L, Tijssen A, Heymans MW, Flierman I, Latour CHM, Peters RJG, Reimer WJM, Buurman BM and Riet GT: The performance of the dutch safety management system frailty tool to predict the risk of readmission or mortality in older hospitalised cardiac patients. BMC Geriatr. 21(299)2021.PubMed/NCBI View Article : Google Scholar
|
41
|
George S, Kwok CS, Martin GP, Babu A, Shufflebotham A, Nolan J, Ratib K, Bagur R, Gunning M and Mamas M: The influence of the Charlson Comorbidity index on procedural characteristics, VARC-2 endpoints and 30-day mortality among patients who undergo transcatheter aortic valve implantation. Heart Lung Circ. 28:1827–1834. 2019.PubMed/NCBI View Article : Google Scholar
|
42
|
Abraham J, Blumer V, Burkhoff D, Pahuja M, Sinha SS, Rosner C, Vorovich E, Grafton G, Bagnola A, Hernandez-Montfort JA and Kapur NK: Heart failure-related cardiogenic shock: Pathophysiology, evaluation and management considerations: Review of heart failure-related cardiogenic shock. J Card Fail. 27:1126–1140. 2021.PubMed/NCBI View Article : Google Scholar
|
43
|
Dalzell JR: Review of cardiogenic shock after acute myocardial infarction. JAMA. 327(878)2022.PubMed/NCBI View Article : Google Scholar
|
44
|
Bertini P and Guarracino F: Pathophysiology of cardiogenic shock. Curr Opin Crit Care. 27:409–415. 2021.PubMed/NCBI View Article : Google Scholar
|
45
|
Lassus J, Tarvasmäki T and Tolppanen H: Biomarkers in cardiogenic shock. Adv Clin Chem. 109:31–73. 2022.PubMed/NCBI View Article : Google Scholar
|
46
|
Krychtiuk KA, Vrints C, Wojta J, Huber K and Speidl WS: Basic mechanisms in cardiogenic shock: Part 1-definition and pathophysiology. Eur Heart J Acute Cardiovasc Care. 11:356–365. 2022.PubMed/NCBI View Article : Google Scholar
|
47
|
Wireklint SC, Elmqvist C, Fridlund B and Göransson KE: A longitudinal, retrospective registry-based validation study of RETTS©, the Swedish adult ED context version. Scand J Trauma Resusc Emerg Med. 30(27)2022.PubMed/NCBI View Article : Google Scholar
|
48
|
Lu KJ, Kearney LG, Ord M, Jones E, Burrell LM and Srivastava PM: Age adjusted Charlson Co-morbidity index is an independent predictor of mortality over long-term follow-up in infective endocarditis. Int J Cardiol. 168:5243–5248. 2013.PubMed/NCBI View Article : Google Scholar
|
49
|
Zhang N, Lin Q, Jiang H and Zhu H: Age-adjusted Charlson Comorbidity index as effective predictor for in-hospital mortality of patients with cardiac arrest: A retrospective study. BMC Emerg Med. 23(7)2023.PubMed/NCBI View Article : Google Scholar
|