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Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19

Year 2021, Volume: 13 Issue: 1, 36 - 44, 11.03.2021
https://doi.org/10.18521/ktd.841884

Abstract

Objective: In this study, we aimed to determine the factors that contribute to the early determination of mortality risk in patients hospitalized with COVID-19.

Methods: We included 941 adult inpatients (474 male [50.4%], mean age, 53.5±17.0. The patients were divided into two groups: the discharge group and the death group. Epidemiological data, medical history, underlying comorbidities, laboratory findings, chest computed tomographic scans, real-time reverse transcription-polymerase chain reaction detection results, and survival data were obtained with retrospective recordings on admission and follow-up. The statistical relationship between survival data and parameters was analyzed. A mathematical model was created from the data of both groups.

Results: While 863 patients survived, 78 were non-survivors. During the study period, the preliminary case fatality rate of the inpatients was 8.3%. The mean age of the non-survivors was 71.7±11.2 SD ( P <0.001). Laboratory findings showed that mortality was high in those with high D-dimer, sodium, lactate dehydrogenase (LDH), troponin, creatine kinase-myocardial band (CK-MB), ferritin, blood lactate, activated partial thromboplastin time, and high blood glucose levels ( P <0.05). Furthermore, mortality was high in patients with low albumin, lymphocyte, and platelet levels ( P <0.05). The logistic regression model showed that advanced age, hypertension, high d-dimer (>1000 ng/ml), high C-reactive protein (CRP), CK-MB, and LDH, and low lymphocyte count were associated with poor prognosis.

Conclusion: According to week 1 data of patients with COVID-19, advanced age, hypertension, d-dimer, CRP, CK-MB, high LDH, and low lymphocyte were associated with poor prognosis. We believe that this model will be useful in predicting patient mortality.

References

  • References 1. Kobayashi T, Jung S-M, Linton NM, Kinoshita R, Hayashi K, Miyama T, et al. Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19). J Clin Med Res 2020;9. https://doi.org/10.3390/jcm9020580. 2. Jin H, Liu J, Cui M, Lu L. Novel coronavirus pneumonia emergency in Zhuhai: impact and challenges. Journal of Hospital Infection 2020;104:452–3. https://doi.org/10.1016/j.jhin.2020.02.005.

COVID-19 Tanısıyla Hastaneye Yatırılan Yetişkin Hastaların İlk Verilerini Kullanarak Ölüm Oranını Tahmin Etmek Mümkün Müdür? COVID-19'un Erken Evresinde Bir Ölüm Tahmin Modeli

Year 2021, Volume: 13 Issue: 1, 36 - 44, 11.03.2021
https://doi.org/10.18521/ktd.841884

Abstract

Amaç: Bu çalışmada COVID-19 tanısıyla hastaneye yatırılan hastalarda mortalite riskinin erken dönemde belirlenmesine katkıda bulunan faktörleri belirlemeyi amaçladık.

Yöntem: Hastanede yatan 941 COVID-19 tanılı erişkin hasta (474 erkek [% 50.4], yaş ortalaması 53.5 ± 17 çalışmaya dahil edildi. Hastalar taburcu edilenler ve mortal seyredenler olarak iki gruba ayrıldı. Epidemiyolojik veriler, tıbbi öykü, altta yatan komorbiditeler, laboratuvar sonuçları, akciğer bilgisayarlı tomografi görüntüleri, PCR sonuçları, sağkalım verileri, başvuru ve takipte geriye dönük olarak kaydedildi. Sağkalım verileri ile parametreler arasındaki istatistiksel ilişki incelendi.Her iki grup verilerinden matematiksel bir model oluşturuldu.

Bulgular: 863 hasta hayatta kalırken, 78 hasta mortal seyretti. Çalışma süresi boyunca, yatan hastaların ilk vaka ölüm oranı % 8.3 idi. Mortal grupta hastaların ortalama yaşı 71.7 ± 11.2 SD idi (P <0.001). Laboratuvar bulgularında, D-Dimer, sodyum, laktat dehidrojenaz (LDH), troponin, kreatin kinaz-miyokardiyal bant (CK-MB), ferritin, kan laktat, aktive parsiyel tromboplastin zamanı ve kan şekeri düzeyleri yüksek olanlarda ölüm oranının yüksek olduğu tespit edilmiştir (P <0.05). Ayrıca; albümin, lenfosit ve trombosit düzeyi düşük hastalarda da mortalite yükse saptandı (P <0.05). Lojistik regresyon modeli, ileri yaş, hipertansiyon, yüksek D-Dimer (> 1000 ng / ml), yüksek C-reaktif protein (CRP), CK-MB ve LDH ve düşük lenfosit sayısının kötü prognozla ilişkili olduğunu gösterdi.

Sonuç: COVID-19 hastalarının 1. hafta verilerine göre ileri yaş, hipertansiyon, yüksek D-Dimer, CRP, CK-MB, LDH ve düşük lenfosit kötü prognozla ilişkilendirildi. Bu modelin hasta ölümlerini tahmin etmede faydalı olacağına inanıyoruz.

References

  • References 1. Kobayashi T, Jung S-M, Linton NM, Kinoshita R, Hayashi K, Miyama T, et al. Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19). J Clin Med Res 2020;9. https://doi.org/10.3390/jcm9020580. 2. Jin H, Liu J, Cui M, Lu L. Novel coronavirus pneumonia emergency in Zhuhai: impact and challenges. Journal of Hospital Infection 2020;104:452–3. https://doi.org/10.1016/j.jhin.2020.02.005.
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Details

Primary Language English
Subjects Health Care Administration
Journal Section Articles
Authors

Oğuz Karabay 0000-0003-1514-1685

Mustafa Baran İnci 0000-0003-1893-5368

Aziz Öğütlü 0000-0003-3840-4038

Hasan Ekerbiçer 0000-0003-0064-3893

Ertuğrul Güçlü 0000-0003-2860-2831

Hamad Dheir 0000-0002-3569-6269

Selcuk Yaylacı 0000-0002-6768-7973

Meltem Karabay 0000-0001-7105-7176

Necip Gökhan Guner 0000-0001-5052-9242

Mehmet Köroğlu 0000-0002-1192-4159

Alper Karacan 0000-0001-8930-9546

Erdem Çokluk 0000-0002-6205-5109

Yakup Tomak 0000-0002-4347-8923

Publication Date March 11, 2021
Acceptance Date January 28, 2021
Published in Issue Year 2021 Volume: 13 Issue: 1

Cite

APA Karabay, O., İnci, M. B., Öğütlü, A., Ekerbiçer, H., et al. (2021). Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19. Konuralp Medical Journal, 13(1), 36-44. https://doi.org/10.18521/ktd.841884
AMA Karabay O, İnci MB, Öğütlü A, Ekerbiçer H, Güçlü E, Dheir H, Yaylacı S, Karabay M, Guner NG, Köroğlu M, Karacan A, Çokluk E, Tomak Y. Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19. Konuralp Medical Journal. March 2021;13(1):36-44. doi:10.18521/ktd.841884
Chicago Karabay, Oğuz, Mustafa Baran İnci, Aziz Öğütlü, Hasan Ekerbiçer, Ertuğrul Güçlü, Hamad Dheir, Selcuk Yaylacı, Meltem Karabay, Necip Gökhan Guner, Mehmet Köroğlu, Alper Karacan, Erdem Çokluk, and Yakup Tomak. “Is It Possible to Predict Mortality Using Initial Data of Adult Patients Hospitalized With COVID-19? A Mortality Prediction Model in the Early Phase of COVID-19”. Konuralp Medical Journal 13, no. 1 (March 2021): 36-44. https://doi.org/10.18521/ktd.841884.
EndNote Karabay O, İnci MB, Öğütlü A, Ekerbiçer H, Güçlü E, Dheir H, Yaylacı S, Karabay M, Guner NG, Köroğlu M, Karacan A, Çokluk E, Tomak Y (March 1, 2021) Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19. Konuralp Medical Journal 13 1 36–44.
IEEE O. Karabay, “Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19”, Konuralp Medical Journal, vol. 13, no. 1, pp. 36–44, 2021, doi: 10.18521/ktd.841884.
ISNAD Karabay, Oğuz et al. “Is It Possible to Predict Mortality Using Initial Data of Adult Patients Hospitalized With COVID-19? A Mortality Prediction Model in the Early Phase of COVID-19”. Konuralp Medical Journal 13/1 (March 2021), 36-44. https://doi.org/10.18521/ktd.841884.
JAMA Karabay O, İnci MB, Öğütlü A, Ekerbiçer H, Güçlü E, Dheir H, Yaylacı S, Karabay M, Guner NG, Köroğlu M, Karacan A, Çokluk E, Tomak Y. Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19. Konuralp Medical Journal. 2021;13:36–44.
MLA Karabay, Oğuz et al. “Is It Possible to Predict Mortality Using Initial Data of Adult Patients Hospitalized With COVID-19? A Mortality Prediction Model in the Early Phase of COVID-19”. Konuralp Medical Journal, vol. 13, no. 1, 2021, pp. 36-44, doi:10.18521/ktd.841884.
Vancouver Karabay O, İnci MB, Öğütlü A, Ekerbiçer H, Güçlü E, Dheir H, Yaylacı S, Karabay M, Guner NG, Köroğlu M, Karacan A, Çokluk E, Tomak Y. Is it possible to predict mortality using initial data of adult patients hospitalized with COVID-19? A mortality prediction model in the early phase of COVID-19. Konuralp Medical Journal. 2021;13(1):36-44.