Clinical and Laboratory Factors in Predicting Mortality Among COVID-19 RT-PCR Positive Patients: A Retrospective Observational Study From a Tertiary Care Center

Abstract

Background: In coronavirus disease 2019 (COVID-19) patients, risk stratification based on clinical presentation, co-morbid illness, and combined laboratory parameters is essential to provide an adequate, timely intervention based on an individual’s conditions to prevent mortality among cases. Methods: A retrospective observational study was carried out from June to October 2020, including all reverse transcription-polymerase chain reaction (RT-PCR) positive COVID-19 non-survivors and control group survivors randomly selected after age and sex matching. Clinical and demographic information was collected from the medical records. Categorical variables were expressed by frequency and percentage. To explore the risk factors associated with mortality, univariable and multivariable logistic regression models were used. Results and discussions: All non-survivors (n = 100) and 100 survivors (out of 1,018) were analyzed. Male gender (67.4%) was the independent risk factor for COVID-19 infection. Advanced age group, diabetes, cardiovascular, neurological, and hypertensive co-morbidities were statistically associated with mortality. Cardiac arrest and acute kidney injury (AKI) were the most common complications. Mortality is significantly associated with lymphopenia and raised lactate dehydrogenase (LDH), as shown by higher odds. In addition, raised neutrophils, monocytes, aspartate aminotransferase (AST), serum creatinine, interleukin 6 (IL-6), and C-reactive protein (CRP) are also significantly associated with mortality. The most common causes of death were respiratory failure (84%) and acute respiratory distress syndrome (77%). Of the non-survivors, 92% received corticosteroids, 63% were on high-flow nasal cannula oxygen therapy, 29% were mechanically ventilated, and 29% received tocilizumab. Conclusion: Serial monitoring of neutrophils, lymphocytes, D-dimer, procalcitonin, AST, LDH, CRP, IL-6, serum creatinine, and albumin might provide a reliable and convenient method for classifying and predicting the severity and outcomes of patients with COVID-19.

Prediction of Mortality in Inpatients of Covid-19 Using Statistical and Artificial Intelligence Approaches: A Case Study in Sakarya

“…A case study conducted in Malaysia also highlighted the profound impact of Covid-19 on mental health and general well-being [41]. In our study, the high fibrinogen ratio and low lymphocyte level trigger mortality is consistent with previous studies [40], [42].…”

Neurological Prognostic Factors in Hospitalized Patients with COVID-19

“…On the other hand, in a Korean study of more than 5000 patients with COVID-19, logistic regression analyses showed that male sex and older age increased the risk of oxygen therapy requirements during hospitalization [ 42 ], similar to the findings in our study. A recent analysis from one of the Indian tertiary centers revealed that patients with SARS-CoV-2 infection who died in the course of the disease received high flow nasal cannula oxygen nearly four times more often than survivors [ 43 ].…”

Predictors of fatal neurological complications among admitted COVID-19 patients with their implication in outcome: A Case Control study

“…There are several clinical, laboratory and radiological investigations that can predict the severity of disease and outcome in COVID-19 patients assigned to respiratory complications [ 12 ]. The vast majority of studies on neurological complications, including meta-analyses, focus on the kind of neurological complication and the outcome, while predictors of neurological sequelae are underexplored [ 13 , 14 ], but there are hardly any relevant predictors for neurological sequelae.…”