Yoğun Bakım Ünitesinde yatan Covid-19'lu Gebe ve Lohusaların Mortalite Risk Faktörleri

Abstract

Amaç: Bu çalışmada yoğun bakımda yatan COVID-19 tanılı gebe ve lohusalarda mortalite prediksiyon modeli oluşturarak APACHE II, SAPS II ve SOFA skorları ile karşılaştırılması amaçlanmıştır. Gereç ve Yöntem: Hastanemizin COVID-19 yoğun bakım ünitelerine yatan Covid-19 tanısı doğrulanmış gebe ve lohusaların demografik, laboratuvar, radyolojik ve klinik verileri geriye dönük olarak kaydedildi. Bulgular: Çalışmaya dahil edilen 50 hastadan 13’ü kaybedildi. Yaş ortalaması ölen grupta 35.54±4.24 yıl, yaşayan grupta 30.03±4.91 yıl idi (p=0.002). Lojistik regresyon modeli, yaş, lenfopeni, yüksek CRP ve IL-6 düzeylerinin mortalite ile ilişkili olduğunu ortaya koydu. Modelin mortalite (AUC) için prediktif gücü 0.946±0.045 (p<0,001) idi. ROC eğrisi altında kalan alan (AUC) APACHE II skoru için 0.712±0.085 (p=0.024), SAPS II skoru için 0.481±0.102 (p=0.842) ve SOFA skoru için 0.656±0.089 (p=0.097) idi. Modelimizin özgüllüğü %97.3, duyarlılığı %84.6, prediktif değeri %91.7 ve negative prediktif değeri %94.7 idi. Sonuç: Oluşturduğumuz tahmin modeli klinisyene, yoğun bakım ünitesine kabul edilen COVID-19 tanılı gebe ve lohusalarda yüksek mortalite riski olan vakaların belirlenmesine olanak tanıyacaktır.

Keywords

• Covid*19
• mortalite
• gebe
• SARS-CoV-2
• lenfopeni
• yoğun bakım

A mortality prediction model in pregnant and postpartum women with Covid-19 admitted to the intensive care unit

Abstract

Objective: In this study, it was aimed to compare with APACHE II, SAPS II and SOFA scores by creating a mortality prediction model in pregnant and postpartum women with a diagnosis of COVID-19 in intensive care (ICU). Materials and Methods: Demographic, laboratory, radiological and clinical data of pregnant and postpartum women with confirmed COVID-19 diagnosis who were admitted to the COVID-19 ICUs of our hospital were recorded retrospectively. Results: Of the 50 patients included in the study, 13 died. The mean age was 35.54±4.24 years in the non-surviving group and 30.03±4.91 years in the surviving group (p=0.002). A logistic regression model revealed age, lymphopenia, elevated CRP and IL-6 levels to be associated with mortality. The predictive power of the model for mortality (AUC) was 0.946±0.045 (p<0.001). The area under an ROC curve (AUC) was 0.712±0.085 for the APACHE II score (p=0.024), 0.481±0.102 (p=0.842) for the SAPS II score and 0.656±0.089 for the SOFA score (p=0.097). Our model had a specificity of 97.3%, a sensitivity of 84.6%, a predictive value of 91.7%, and a negative predictive value of 94.7%. Conclusion: The prediction model we created will allow the clinician to identify cases with a high risk of mortality risk in pregnant and postpartum women with a diagnosis of COVID-19 admitted to the ICU.

Keywords

• Covid-19; mortality; pregnant women; SARS CoV-2; lymphopenia; critical care

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