MuLBSTA skorunun şiddetli akut solunum sendromu koronavirüs 2019 pnömonili hospitalize hastalarda kritik klinik sonuçları öngörmedeki prediktif değerinin incelenmesi
Abstract
Amaç: Multilobar infiltrasyon, lenfositopeni, bakteriyel koenfeksiyon, sigara öyküsü, hipertansiyon ve yaş>65 (MuLBSTA) skoru, viral pnömonisi olan hastaları beklenen mortaliteye göre sınıflandırmak için kullanılan bir klinik tahmin kuralıdır. Hastanede yatan SARS-CoV-2 hastalarında kötü klinik sonuçlar için MuLBSTA’nın prediktif performansını PSI, CURB-65 ve qSOFA ile karşılaştırdık.
Yöntemler: Bu çalışma 11 Mart 2020 ile 31 Mayıs 2020 tarihleri arasında üçüncü basamak bir üniversite hastanesinde yatan SARS-CoV-2’li hastalar üzerinde geriye dönük yapıldı. SARS-CoV-2 testi pozitif çıkan 900 hastadan 271’i çalışmaya dâhil edildi. Tüm hastalarda 30 günlük mortalite, Yoğun bakım ünitesi (YBÜ) ihtiyacı, mekanik ventilasyon gereksinimi ve akut respiratuar distress (ARDS) gelişimini değerlendirmek için MuLBSTA, PSI, CURB-65 ve qSOFA skoru kullanıldı. Otuz günlük mortalite için prognostik faktörler de analiz edildi.
Bulgular: Hastanede yatan 271 hastanın 150’si (%55.3) erkekti. Ortalama yaş 54.2±15.4 yıldı. Otuz günlük ölüm oranı %10,7 idi. Çalışmaya dâhil edilen hastalardan; 39 hasta (%14,3) YBÜ’ye yatırıldı, 32 hasta (%11,8) mekanik ventilatör desteği aldı ve 23 hasta (%8,4) ARDS tanısı aldı. Mortaliteyi tahmin etmede MuLBSTA, PSI, CURB-65 ve qSOFA skorlarının eğri altında kalan alan (AUC) değerleri sırasıyla 0.877 (%95 CI 0.832 0.914), 0.853 (%95 CI 0.806-0.893), 0.769 (95% CI 0,714-0,817) ve 0,769 (95% CI 0,715-0,818). MuLBSTA puanı, diğer tahmin puanlarına kıyasla daha yüksek bir AUC değeri gösterdi. MuLBSTA ve PSI skorları, YBÜ ihtiyacı, mekanik ventilasyon gereksinimive ARDS gelişimi olan hastaları belirlemede CURB-65 ve qSOFA skorlarından daha iyi performans gösterdi.
Sonuç: MuLBSTA skoru, hastanede yatan SARS-CoV-2 hastalarında kötü klinik sonuçları tahmin etmek için etkili bir araçtır. Kullanımını doğrulamak için daha fazla çalışmaya ihtiyaç vardır.
Supporting Institution
Yoktur
Project Number
Yoktur
References
- Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis. 2007;44(suppl 2):27-72.
- Lim WS, Baudouin SV, George RC, et al. Pneumonia Guidelines Committee of the BTS Standards of Care Committee. BTS guidelines for the management of community acquired pneumonia in adults: update 2009. Thorax. 2009;64(suppl 3):S1-S55.
- Mulrennan S, Tempone SS, Ling IT, et al. Pandemic influenza (H1N1) 2009 pneumonia: CURB-65 score for predicting severity and nasopharyngeal sampling for diagnosis are unreliable. PLoS One. 2010;5:e12849.
- Estella A. Usefulness of CURB-65 and pneumonia severity index for influenza A H1N1v pneumonia. Monaldi Arch Chest Dis. 2012;77:118–21.
- Brandao-Neto RA, Goulart AC, Santana AN, et al. The role of pneumonia scores in the emergency room in patients infected by 2009 H1N1 infection. Eur J Emerg Med. 2012;19:200–2.
- Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315:801–10.
- Chen YX, Wang JY, Guo SB. Use of CRB-65 and quick Sepsis related Organ Failure Assessment to predict site of care and mortality in pneumonia patients in the emergency department: a retrospective study. Crit Care. 2016;20(1):167.
- Kolditz M, Scherag A, Rohde G, et al. Comparison of the qSOFA and CRB-65 for risk prediction in patients with community-acquired pneumonia. Intensive Care Med. 2016;42 (12):2108–10.
- Ranzani OT, Prina E, Menendez R, et al. New Sepsis Definition (Sepsis-3) and Community-acquired Pneumonia Mortality: A Validation and Clinical Decision-making Study. Am J Respir Crit Care Med. 2017;196(10):1287–97.
- Asai N, Watanabe H, Shiota A, et al. Efficacy and accuracy of qSOFA and SOFA scores as prognostic tools for community-acquired and healthcare-associated pneumonia. Int J Infect Dis. 2019;84:89-96.
- Guo L, Wei D, Zhang X, et al. Clinical features predicting mortality risk in patients with viral pneumonia: the MuLBSTA score. Front Microbiol. 2019;10:2752.
- Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497-506.
- Zhu N, Zhang D, Wang W, et al. China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727-33.
- Wang D, Hu B, Hu C, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA, 2020;323(11):1061–9.
- Wu C, Chen X, Cai Y, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):934-43.
- Zheng Z, Peng F, Xu B, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020;81(2):e16-e25.
- Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-13.
- Xu R, Hou K, Zhang K, et al. Performance of Two Risk-Stratification Models in Hospitalized Patients With Coronavirus Disease. Front Med (Lausanne). 2020;7:518.
- García Clemente MM, Herrero Huertas J, Fernández Fernández A, et al. Assessment of risk scores in Covid-19. Int J Clin Pract. 2021;75(12):e13705.
- Artero A, Madrazo M, Fernández-Garcés M, et al. Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study. J Gen Intern Med. 2021;36(5):1338-1345.
- Iijima Y, Okamoto T, Shirai T, et al. MuLBSTA score is a useful tool for predicting COVID-19 disease behavior. J Infect Chemother. 2021;27(2):284-90.
- Liang W, Liang H, Ou L, et al. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med. 2020;180:1081–9.
- Haimovich AD, Ravindra NG, Stoytchev S, et al. Development and validation of the quick COVID-19 severity index: a prognostic tool for early clinical decompensation. Ann Emerg Med. 2020;76:442–53.
- Huespe I, Carboni Bisso I, Di Stefano S, et al. COVID-19 severity index: a predictive score for hospitalized patients. Med Intensiva. 2022;46(2):98–101.
- Ji D, Zhang D, Xu J, et al. Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score. Clin Infect Dis. 2020;71(6):1393-9.
- Knight SR, Ho A, Pius R, et al. Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score [published correction appears in BMJ. 2020 Nov 13;371:m4334]. BMJ. 2020;370:m3339.
Investigation of the predictive value of MuLBSTA score in predicting critical clinical outcomes in hospitalized patients with severe acute respiratory syndrome-coronavirus-2 pneumonia
Abstract
Aim: Multilobar infiltration, lymphocytopenia, bacterial co-infection, smoking history, hypertension, and age>65 (MuLBSTA) score is a clinical prediction rule used to classify patients with viral pneumonia by expected mortality. We compared the predictive performance of MuLBSTA with PSI, CURB-65, and qSOFA for poor clinical outcomes in hospitalized severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) patients.
Methods: A retrospective study was conducted on patients with SARS-CoV-2 who were hospitalized in a tertiary medical center between March 11, 2020, and May 31, 2020. 271 out of 900 patients who tested positive for SARS-CoV-2 were included in the study. The MuLBSTA, PSI, CURB-65, and qSOFA scores were used to assess thirty-day mortality, need for intensive care unit (ICU), mechanical ventilation (MV) requirement, and development of acute respiratory distress syndrome (ARDS) in all patients. Prognostic factors were also analyzed for thirty-day mortality.
Results: Among all 271 hospitalized patients, 150 males (55.3%) were included. The mean age was 54.2±15.4 years. The 30-day mortality rate was 10.7%. Of the patients included in the study; 39 patients (14.3%) were admitted to the intensive care unit, 32 patients (11.8%) received mechanical ventilator support, and 23 patients (8.4%) were diagnosed with ARDS. In predicting mortality, the area under the curve (AUC) of the MuLBSTA, PSI, CURB-65 and qSOFA scores were 0.877 (95% CI 0,832 0,914), 0.853 (95% CI 0,806-0,893), 0.769 (95% CI 0,714-0,817) and 0.769 (95% CI 0,715-0,818), respectively. The MuLBSTA score showed a higher AUC value compared to other prediction scores. The MuLBSTA and PSI scores performed better than CURB-65 and qSOFA scores in determining patients’ need for ICU, MV requirement, and ARDS development.
Conclusion: The MuLBSTA score is an efficient tool to predict poor clinical outcomes in hospitalized patients with SARS-CoV-2. Further studies are warranted to validate its use.
Keywords
Project Number
Yoktur
References
- Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults. Clin Infect Dis. 2007;44(suppl 2):27-72.
- Lim WS, Baudouin SV, George RC, et al. Pneumonia Guidelines Committee of the BTS Standards of Care Committee. BTS guidelines for the management of community acquired pneumonia in adults: update 2009. Thorax. 2009;64(suppl 3):S1-S55.
- Mulrennan S, Tempone SS, Ling IT, et al. Pandemic influenza (H1N1) 2009 pneumonia: CURB-65 score for predicting severity and nasopharyngeal sampling for diagnosis are unreliable. PLoS One. 2010;5:e12849.
- Estella A. Usefulness of CURB-65 and pneumonia severity index for influenza A H1N1v pneumonia. Monaldi Arch Chest Dis. 2012;77:118–21.
- Brandao-Neto RA, Goulart AC, Santana AN, et al. The role of pneumonia scores in the emergency room in patients infected by 2009 H1N1 infection. Eur J Emerg Med. 2012;19:200–2.
- Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315:801–10.
- Chen YX, Wang JY, Guo SB. Use of CRB-65 and quick Sepsis related Organ Failure Assessment to predict site of care and mortality in pneumonia patients in the emergency department: a retrospective study. Crit Care. 2016;20(1):167.
- Kolditz M, Scherag A, Rohde G, et al. Comparison of the qSOFA and CRB-65 for risk prediction in patients with community-acquired pneumonia. Intensive Care Med. 2016;42 (12):2108–10.
- Ranzani OT, Prina E, Menendez R, et al. New Sepsis Definition (Sepsis-3) and Community-acquired Pneumonia Mortality: A Validation and Clinical Decision-making Study. Am J Respir Crit Care Med. 2017;196(10):1287–97.
- Asai N, Watanabe H, Shiota A, et al. Efficacy and accuracy of qSOFA and SOFA scores as prognostic tools for community-acquired and healthcare-associated pneumonia. Int J Infect Dis. 2019;84:89-96.
- Guo L, Wei D, Zhang X, et al. Clinical features predicting mortality risk in patients with viral pneumonia: the MuLBSTA score. Front Microbiol. 2019;10:2752.
- Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497-506.
- Zhu N, Zhang D, Wang W, et al. China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727-33.
- Wang D, Hu B, Hu C, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA, 2020;323(11):1061–9.
- Wu C, Chen X, Cai Y, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):934-43.
- Zheng Z, Peng F, Xu B, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020;81(2):e16-e25.
- Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-13.
- Xu R, Hou K, Zhang K, et al. Performance of Two Risk-Stratification Models in Hospitalized Patients With Coronavirus Disease. Front Med (Lausanne). 2020;7:518.
- García Clemente MM, Herrero Huertas J, Fernández Fernández A, et al. Assessment of risk scores in Covid-19. Int J Clin Pract. 2021;75(12):e13705.
- Artero A, Madrazo M, Fernández-Garcés M, et al. Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study. J Gen Intern Med. 2021;36(5):1338-1345.
- Iijima Y, Okamoto T, Shirai T, et al. MuLBSTA score is a useful tool for predicting COVID-19 disease behavior. J Infect Chemother. 2021;27(2):284-90.
- Liang W, Liang H, Ou L, et al. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med. 2020;180:1081–9.
- Haimovich AD, Ravindra NG, Stoytchev S, et al. Development and validation of the quick COVID-19 severity index: a prognostic tool for early clinical decompensation. Ann Emerg Med. 2020;76:442–53.
- Huespe I, Carboni Bisso I, Di Stefano S, et al. COVID-19 severity index: a predictive score for hospitalized patients. Med Intensiva. 2022;46(2):98–101.
- Ji D, Zhang D, Xu J, et al. Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score. Clin Infect Dis. 2020;71(6):1393-9.
- Knight SR, Ho A, Pius R, et al. Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score [published correction appears in BMJ. 2020 Nov 13;371:m4334]. BMJ. 2020;370:m3339.
Details
| Primary Language | English |
|---|---|
| Subjects | Health Care Administration |
| Journal Section | ORIGINAL ARTICLE |
| Authors | |
| Project Number | Yoktur |
| Publication Date | September 27, 2022 |
| Acceptance Date | August 22, 2022 |
| Published in Issue | Year 2022 Volume: 27 Issue: 3 |
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