Research Article
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Year 2022, Volume: 5 Issue: 5, 1399 - 1404, 25.09.2022
https://doi.org/10.32322/jhsm.1147178

Abstract

References

  • Higgins TL, McGee WT, Steingrub JS, Rapoport J, Lemeshow S, Teres D. Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay. Crit Care Med 2003; 31: 45-51.
  • Toptas M, Sengul Samanci N, Akkoc İ, et al. Factors affecting the length of stay in the ıntensive care unit: our clinical experience. Biomed Res Int 2018; 2018: 9438046.
  • Li XL, Yao ZH, Wan YY, et al. Prognostic impact of prognostic nutritional index in advanced (stage IIIB/IV) non-small cell lung cancer patients. Neoplasma 2019; 66: 971-7.
  • Machado Dos Reis A, Marchetti J, Forte Dos Santos A, Franzosi OS, Steemburgo T. NUTRIC Score: ısolated and combined use with the NRS-2002 to predict hospital mortality in critically ill patients. JPEN J Parenter Enteral Nutr 2020; 44: 1250-6.
  • Vermeulen KM, Leal LL, Furtado MC, Vale SH, Lais LL. Phase angle and Onodera's prognostic nutritional index in critically ill patients. Nutr Hosp 2016; 33: 1268-75.
  • Yin M, Si L, Qin W, et al. Predictive value of serum albumin level for the prognosis of severe sepsis without exogenous human albumin administration: a prospective cohort study. J Intensive Care Med 2018; 33: 687–94.
  • Ho KM, Dobb GJ, Knuiman M, Finn J, Lee KY, Webb SA. A comparison of admission and worst 24-hour Acute Physiology and Chronic Health Evaluation II scores in predicting hospital mortality: a retrospective cohort study. Crit Care 2006; 10: R4.
  • Stavem K, Hoel H, Skjaker SA, Haagensen R. Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients. Clin Epidemiol 2017; 9: 311-20.
  • Lambden S, Laterre PF, Levy MM, Francois B. The SOFA score-development, utility and challenges of accurate assessment in clinical trials. Crit Care 2019; 23: 374.
  • Olejarova M, Dobisova A, Suchankova M, et al. Vitamin D deficiency-a potential risk factor for sepsis development, correlation with inflammatory markers, SOFA score and higher early mortality risk in sepsis. Bratisl Med J 2019; 120: 284-90.
  • Ofer-Shiber S, Molad Y. Association of the Charlson comorbidity index with renal outcome and all-cause mortality in antineutrophil cytoplasmatic antibody-associated vasculitis. Medicine (Baltimore) 2014; 93: e152.
  • Mete B, Pehlivan E, Gülbaş G, Günen H. Prevalence of malnutrition in COPD and its relationship with the parameters related to disease severity. Int J Chron Obstruct Pulmon Dis 2018; 13: 3307-12.
  • Ayık DB, Büyükbayram Z, Can G. Determination of malnutrition status in palliative care patients. J Med Palliat Care 2020; 1: 64-70.
  • Suárez-Llanos JP, Benítez-Brito N, Vallejo-Torres L, et al. Clinical and cost-effectiveness analysis of early detection of patients at nutrition risk during their hospital stay through the new screening method CIPA: a study protocol. BMC Health Serv Res 2017; 17: 292.
  • de Vries MC, Koekkoek WK, Opdam MH, van Blokland D, van Zanten AR. Nutritional assessment of critically ill patients: validation of the modified NUTRIC score. Eur J Clin Nutr 2018; 72: 428-35.
  • Jian-Hui C, Iskandar EA, Cai ShI, et al. Significance of Onodera's prognostic nutritional index in patients with colorectal cancer: a large cohort study in a single Chinese institution. Tumour Biol 2016; 37: 3277-83.
  • McClave SA, Taylor BE, Martindale RG, et al. Guidelines for the Provision and Assessment of Nutrition Support Therapy in the Adult Critically Ill Patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.). JPEN J Parenter Enteral Nutr 2016; 40: 159-211.
  • Onodera T, Goseki N, Kosaki G. Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients. Nihon Geka Gakkai Zasshi 1984; 85: 1001-5.
  • Sağır M, Kaplan M, Tanoğlu A, Demirel F. Relationship between vitamin D levels and mortality rates of critically ill patients in intensive care unit. Anatolian Curr Med J 2021; 3: 171-6.
  • Rapsang AG, Shyam DC. Scoring systems in the intensive care unit: A compendium. Indian J Crit Care Med 2014; 18: 220-8.
  • Güzel S, Keser A, Kepenekci Bayram İ. Risk of malnutrition in general surgical patients. J Health Sci Med 2021; 4: 55-62.
  • Pylväläinen J, Talala K, Murtola T, et al. Charlson comorbidity ındex based on hospital episode statistics performs adequately ın predicting mortality, but its discriminative ability diminishes over time. Clin Epidemiol 2019; 11: 923-32.
  • Wu CC, Hsu TW, Chang CM, Yu CH, Lee CC. Age-adjusted Charlson comorbidity index scores as predictor of survival in colorectal cancer patients who underwent surgical resection and chemoradiation. Medicine (Baltimore) 2015; 94: e431.
  • Ofori-Asenso R, Zomer E, Chin KL, et al. Effect of comorbidity assessed by the Charlson comorbidity ındex on the length of stay, costs and mortality among older adults hospitalised for acute stroke. Int J Environ Res Public Health 2018; 15: 2532.
  • Jelicic J, Todorovic Balint M, Sretenovic DA, et al. Enhanced ınternational prognostic ındex (NCCN-IPI), Charlson comorbidity ındex and absolute lymphocyte count as predictors for survival of elderly patients with diffuse large B cell lymphoma treated by immunochemotherapy. Neoplasma 2015; 62: 988-95.
  • Atik B, Kilinc G, Yarar V. Predictive value of prognostic factors at multiple trauma patients in intensive care admission. Bratisl Med J 2021; 122: 277-9.
  • Pettilä V, Pettilä M, Sarna S, Voutilainen P, Takkunen O. Comparison of multiple organ dysfunction scores in the prediction of hospital mortality in the critically ill. Crit Care Med 2002; 30: 1705–11.
  • Maccariello ER, Valente C, Nogueira L, et al. Performance of six prognostic scores in critically ill patients receiving renal replacement therapy. Rev Bras Ter Intensiva 2008; 20: 115–23.
  • Tuty Kuswardhani RA, Henrina J, Pranata R, Anthonius Lim M, Lawrensia S, Suastika K. Charlson comorbidity index and a composite of poor outcomes in COVID-19 patients: a systematic review and meta-analysis. Diabetes Metab Syndr 2020; 14: 2103-9.
  • Iaccarino G, Grassi G, Borghi C, Ferri C, Salvetti M, Volpe M; SARS-RAS Investigators. Age and multimorbidity predict death among COVID-19 patients: results of the SARS-RAS study of the Italian Society of Hypertension. Hypertension 2020; 76: 366-72.

The relationship between acute physiology and chronic health evaluation-II, sequential organ failure assessment, Charlson comorbidity index and nutritional scores and length of intensive care unit stay of patients hospitalized in the intensive care unit due to chronic obstructive pulmonary disease

Year 2022, Volume: 5 Issue: 5, 1399 - 1404, 25.09.2022
https://doi.org/10.32322/jhsm.1147178

Abstract

Aim: It is known that disease severity and nutritional status are determinants of prognosis in patients hospitalized in the intensive care unit (ICU). Different scoring systems are used to evaluate the nutritional status and disease severity of intensive care patients. It will be very useful in clinical practice to determine the intensive care scores that are in harmony with the nutritional parameters and affect the length of stay in the ICU in patients hospitalized with the diagnosis of chronic obstructive pulmonary disease (COPD). It was aimed to determine the relationship between acute physiology and chronic health evaluation-II (Apache-II), sequential organ failure assessment (SOFA), and Charlson comorbidity index (CCI) with nutritional scores in intensive care patients with a diagnosis of COPD. Also, it was aimed to determine the scoring systems that affect the length of stay in the ICU.
Material and Method: Nutritional risk score-2002 (NRS-2002), prognostic nutritional index (PNI), modified nutritional risk in critically ill (mNutric) score, albumin, Apache-II, SOFA and CCI values and intensive care unit length of stay of the patients hospitalized in the intensive care unit due to COPD were recorded. The scoring systems that affect the length of stay in the ICU and the relationship between nutritional scores and Apache-II, SOFA and CCI was analyzed using statistical methods.
Results: A significant correlation was found between only CCI and all nutritional scores. Only the CCI value was found to be significantly higher in those found to be at high risk compared to all nutritional scoring systems. CCI cut-off value determined according to nutritional scoring was determined as 4.5 according to PNI and albumin, and 5.5 according to mNutric score and NRS-2002. It was determined that CCI affects the length of stay in the intensive care unit.
Conclusion: CCI is a scoring system that is compatible with nutritional parameters and affects the length of stay in the intensive care unit. Therefore, we think that CCI can be used to predict prognosis and nutritional risk in patients with COPD in the intensive care unit and to predict the length of stay in the intensive care unit. In terms of malnutrition risk, a cut-off value of ≥6 can be used for CCI.

References

  • Higgins TL, McGee WT, Steingrub JS, Rapoport J, Lemeshow S, Teres D. Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and pre-intensive care unit length of stay. Crit Care Med 2003; 31: 45-51.
  • Toptas M, Sengul Samanci N, Akkoc İ, et al. Factors affecting the length of stay in the ıntensive care unit: our clinical experience. Biomed Res Int 2018; 2018: 9438046.
  • Li XL, Yao ZH, Wan YY, et al. Prognostic impact of prognostic nutritional index in advanced (stage IIIB/IV) non-small cell lung cancer patients. Neoplasma 2019; 66: 971-7.
  • Machado Dos Reis A, Marchetti J, Forte Dos Santos A, Franzosi OS, Steemburgo T. NUTRIC Score: ısolated and combined use with the NRS-2002 to predict hospital mortality in critically ill patients. JPEN J Parenter Enteral Nutr 2020; 44: 1250-6.
  • Vermeulen KM, Leal LL, Furtado MC, Vale SH, Lais LL. Phase angle and Onodera's prognostic nutritional index in critically ill patients. Nutr Hosp 2016; 33: 1268-75.
  • Yin M, Si L, Qin W, et al. Predictive value of serum albumin level for the prognosis of severe sepsis without exogenous human albumin administration: a prospective cohort study. J Intensive Care Med 2018; 33: 687–94.
  • Ho KM, Dobb GJ, Knuiman M, Finn J, Lee KY, Webb SA. A comparison of admission and worst 24-hour Acute Physiology and Chronic Health Evaluation II scores in predicting hospital mortality: a retrospective cohort study. Crit Care 2006; 10: R4.
  • Stavem K, Hoel H, Skjaker SA, Haagensen R. Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients. Clin Epidemiol 2017; 9: 311-20.
  • Lambden S, Laterre PF, Levy MM, Francois B. The SOFA score-development, utility and challenges of accurate assessment in clinical trials. Crit Care 2019; 23: 374.
  • Olejarova M, Dobisova A, Suchankova M, et al. Vitamin D deficiency-a potential risk factor for sepsis development, correlation with inflammatory markers, SOFA score and higher early mortality risk in sepsis. Bratisl Med J 2019; 120: 284-90.
  • Ofer-Shiber S, Molad Y. Association of the Charlson comorbidity index with renal outcome and all-cause mortality in antineutrophil cytoplasmatic antibody-associated vasculitis. Medicine (Baltimore) 2014; 93: e152.
  • Mete B, Pehlivan E, Gülbaş G, Günen H. Prevalence of malnutrition in COPD and its relationship with the parameters related to disease severity. Int J Chron Obstruct Pulmon Dis 2018; 13: 3307-12.
  • Ayık DB, Büyükbayram Z, Can G. Determination of malnutrition status in palliative care patients. J Med Palliat Care 2020; 1: 64-70.
  • Suárez-Llanos JP, Benítez-Brito N, Vallejo-Torres L, et al. Clinical and cost-effectiveness analysis of early detection of patients at nutrition risk during their hospital stay through the new screening method CIPA: a study protocol. BMC Health Serv Res 2017; 17: 292.
  • de Vries MC, Koekkoek WK, Opdam MH, van Blokland D, van Zanten AR. Nutritional assessment of critically ill patients: validation of the modified NUTRIC score. Eur J Clin Nutr 2018; 72: 428-35.
  • Jian-Hui C, Iskandar EA, Cai ShI, et al. Significance of Onodera's prognostic nutritional index in patients with colorectal cancer: a large cohort study in a single Chinese institution. Tumour Biol 2016; 37: 3277-83.
  • McClave SA, Taylor BE, Martindale RG, et al. Guidelines for the Provision and Assessment of Nutrition Support Therapy in the Adult Critically Ill Patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.). JPEN J Parenter Enteral Nutr 2016; 40: 159-211.
  • Onodera T, Goseki N, Kosaki G. Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients. Nihon Geka Gakkai Zasshi 1984; 85: 1001-5.
  • Sağır M, Kaplan M, Tanoğlu A, Demirel F. Relationship between vitamin D levels and mortality rates of critically ill patients in intensive care unit. Anatolian Curr Med J 2021; 3: 171-6.
  • Rapsang AG, Shyam DC. Scoring systems in the intensive care unit: A compendium. Indian J Crit Care Med 2014; 18: 220-8.
  • Güzel S, Keser A, Kepenekci Bayram İ. Risk of malnutrition in general surgical patients. J Health Sci Med 2021; 4: 55-62.
  • Pylväläinen J, Talala K, Murtola T, et al. Charlson comorbidity ındex based on hospital episode statistics performs adequately ın predicting mortality, but its discriminative ability diminishes over time. Clin Epidemiol 2019; 11: 923-32.
  • Wu CC, Hsu TW, Chang CM, Yu CH, Lee CC. Age-adjusted Charlson comorbidity index scores as predictor of survival in colorectal cancer patients who underwent surgical resection and chemoradiation. Medicine (Baltimore) 2015; 94: e431.
  • Ofori-Asenso R, Zomer E, Chin KL, et al. Effect of comorbidity assessed by the Charlson comorbidity ındex on the length of stay, costs and mortality among older adults hospitalised for acute stroke. Int J Environ Res Public Health 2018; 15: 2532.
  • Jelicic J, Todorovic Balint M, Sretenovic DA, et al. Enhanced ınternational prognostic ındex (NCCN-IPI), Charlson comorbidity ındex and absolute lymphocyte count as predictors for survival of elderly patients with diffuse large B cell lymphoma treated by immunochemotherapy. Neoplasma 2015; 62: 988-95.
  • Atik B, Kilinc G, Yarar V. Predictive value of prognostic factors at multiple trauma patients in intensive care admission. Bratisl Med J 2021; 122: 277-9.
  • Pettilä V, Pettilä M, Sarna S, Voutilainen P, Takkunen O. Comparison of multiple organ dysfunction scores in the prediction of hospital mortality in the critically ill. Crit Care Med 2002; 30: 1705–11.
  • Maccariello ER, Valente C, Nogueira L, et al. Performance of six prognostic scores in critically ill patients receiving renal replacement therapy. Rev Bras Ter Intensiva 2008; 20: 115–23.
  • Tuty Kuswardhani RA, Henrina J, Pranata R, Anthonius Lim M, Lawrensia S, Suastika K. Charlson comorbidity index and a composite of poor outcomes in COVID-19 patients: a systematic review and meta-analysis. Diabetes Metab Syndr 2020; 14: 2103-9.
  • Iaccarino G, Grassi G, Borghi C, Ferri C, Salvetti M, Volpe M; SARS-RAS Investigators. Age and multimorbidity predict death among COVID-19 patients: results of the SARS-RAS study of the Italian Society of Hypertension. Hypertension 2020; 76: 366-72.
There are 30 citations in total.

Details

Primary Language English
Subjects Health Care Administration
Journal Section Original Article
Authors

Ramazan Baldemir 0000-0003-3661-4277

Güler Eraslan Doğanay 0000-0003-2420-7607

Mustafa Özgür Cırık 0000-0002-9449-9302

Gülay Ülger 0000-0003-1926-4770

Gulsah Yurtseven 0000-0003-4441-6377

Musa Zengin 0000-0003-2249-6521

Publication Date September 25, 2022
Published in Issue Year 2022 Volume: 5 Issue: 5

Cite

AMA Baldemir R, Eraslan Doğanay G, Cırık MÖ, Ülger G, Yurtseven G, Zengin M. The relationship between acute physiology and chronic health evaluation-II, sequential organ failure assessment, Charlson comorbidity index and nutritional scores and length of intensive care unit stay of patients hospitalized in the intensive care unit due to chronic obstructive pulmonary disease. J Health Sci Med / JHSM. September 2022;5(5):1399-1404. doi:10.32322/jhsm.1147178

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