Predictors of mortality and morbidity in critically ill COVID‐19 patients: An experience from a low mortality country

COVID-19: The Development and Validation of a New Mortality Risk Score

Background: The coronavirus disease 2019 (COVID-19) pandemic has found the whole world unprepared for its correct management. Italy was the first European country to experience the spread of the SARS-CoV-2 virus at the end of February 2020. As a result of hospital overcrowding, the quality of care delivered was not always optimal. A substantial number of patients admitted to non-ICU units could have been treated at home. It would have been extremely useful to have a score that, based on personal and clinical characteristics and simple blood tests, could have predicted with sufficient reliability the probability that a patient had or did not have a disease that could have led to their death. This study aims to develop a scoring system to identify which patients with COVID-19 are at high mortality risk upon hospital admission, to expedite and enhance clinical decision making. Methods: A retrospective analysis was performed to develop a multivariable prognostic prediction model. Results: Derivation and external validation cohorts were obtained from two Italian University Hospital databases, including 388 (10.31% deceased) and 1357 (7.68% deceased) patients with confirmed COVID-19, respectively. A multivariable logistic model was used to select seven variables associated with in-hospital death (age, baseline oxygen saturation, hemoglobin value, white blood cell count, percentage of neutrophils, platelet count, and creatinine value). Calibration and discrimination were satisfactory with a cumulative AUC for prediction mortality of 0.924 (95% CI: 0.893-0.944) in derivation cohorts and 0.808 (95% CI: 0.886-0.828) in external validation cohorts. The risk score obtained was compared with the ISARIC 4C Mortality Score, and with all the other most important scores considered so far, to evaluate the risk of death of patients with COVID-19. It performed better than all the above scores to evaluate the predictability of dying. Its sensitivity, specificity, and AUC were higher than the other COVID-19 scoring systems when the latter were calculated for the 388 patients in our derivation cohort. Conclusions: In conclusion, the CZ-COVID-19 Score may help all physicians by identifying those COVID-19 patients who require more attention to provide better therapeutic regimens or, on the contrary, by identifying those patients for whom hospitalization is not necessary and who could therefore be sent home without overcrowding healthcare facilities. We developed and validated a new risk score based on seven variables for upon-hospital admission of COVID-19 patients. It is very simple to calculate and performs better than all the other similar scores to evaluate the predictability of dying.

Effects of the pre-existing coronary heart disease on the prognosis of COVID-19 patients: A systematic review and meta-analysis

Although studies have shown severe Coronavirus disease 2019 (COVID-19) outcomes in patients with pre-existing coronary heart disease (CHD), the prognosis of COVID-19 patients with pre-existing CHD remains uncertain primarily due to the limited number of patients in existing studies. This study aimed to investigate the impacts of pre-existing CHD on the prognosis of COVID-19 patients. Five electronic databases were searched for eligible studies. This article focused on cohort and case-control studies involving the prognosis of COVID-19 patients with pre-existing CHD. The meta-analysis was performed using a random effects model. The odds ratios (ORs) and 95% confidence intervals (CIs) were used as valid indicators. The study was registered in PROSPERO with the identifier: CRD42022352853. A total of 81 studies, involving 157,439 COVID-19 patients, were included. The results showed that COVID-19 patients with pre-existing CHD exhibited an elevated risk of mortality (OR = 2.45; 95%CI: [2.04, 2.94], P < 0.001), severe/critical COVID-19 (OR = 2.57; 95%CI: [1.98, 3.33], P < 0.001), Intensive Care Unit or Coronary Care Unit (ICU/CCU) admission: (OR = 2.75, 95%CI: [1.61, 4.72], P = 0.002), and reduced odds of discharge/recovery (OR = 0.43, 95%CI: [0.28, 0.66], P < 0.001) compared to COVID-19 patients without pre-existing CHD. Subgroup analyses indicated that the prognosis of COVID-19 patients with pre-existing CHD was influenced by publication year, follow-up duration, gender, and hypertension. In conclusion, pre-existing CHD significantly increases the risk of poor prognosis in patients with COVID-19, particularly in those male or hypertensive patients.

From past to present: Exploring COVID-19 in Qatar's hemodialysis population across Omicron dominant and pre-Omicron periods

COVID-19 carries a high risk of morbidity and mortality in dialysis patients. Multiple SARS-CoV-2 variants have been identified since the start of the COVID-19 pandemic. The current study aimed to compare the incidence and outcomes of the COVID-19 Omicron dominant period versus other pre-Omicron period in hemodialysis patients. In this observational, analytical, retrospective, nationwide study, we reviewed adult chronic hemodialysis patients between March 1, 2020, and January 31, 2022. Four hundred twenty-one patients had COVID-19 during the study period. The incidence of COVID-19 due to the Omicron dominant period was significantly higher than other pre-Omicron period (30.3% vs. 18.7%, P<0.001). In contrast, the admission rate to ICU was significantly lower in the Omicron dominant period than in the pre-Omicron period (2.8% vs. 25%, P<0001) but with no significant difference in ICU length of stay. The mortality rate was lower in the Omicron dominant period compared to the pre-Omicron period (2.4% vs. 15.5%, P<0.001). Using multivariate analysis, older age [OR 1.093 (95% CI 1.044-1.145); P<0.0001] and need for mechanical ventilation [OR 70.4 (95% CI 20.39-243.1); P<0.0001] were identified as two independent risk factors for death in hemodialysis patients with COVID-19. In Conclusion, the COVID-19 Omicron variant had a higher incidence and lower morbidity and mortality than pre-Omicron period in our hemodialysis population.

Rhabdomyolysis in Critically Ill Patients With COVID-19: A Retrospective Study

INTRODUCTION

The total number of ICU admissions for COVID-19 patients has increased steadily. Based on the research team's clinical observations, many patients developed rhabdomyolysis, but few cases were reported in the literature. This study explores the incidence of rhabdomyolysis and its outcomes, like mortality, the need for intubation, acute kidney injury, and the need for renal replacement therapy (RRT).

METHODS

We retrospectively reviewed the characteristics and outcomes of patients admitted to the ICU at a COVID-19-designated hospital in Qatar between March and July 2020. Logistic regression analysis was used to determine factors associated with mortality.

RESULTS

1079 patients with COVID-19 were admitted to the ICU, and 146 developed rhabdomyolysis. Overall, 30.1% died (n = 44), and 40.4% developed Acute Kidney Injury (AKI) (n = 59), with only 19 cases (13%) recovering from the AKI. AKI was significantly associated with increased mortality rates among rhabdomyolysis patients. Moreover, significant differences were found between groups regarding the subject's age, calcium level, phosphorus level, and urine output. However, the AKI was the best predictor of mortality for those who got the COVID-19 infection and rhabdomyolysis.

CONCLUSION

Rhabdomyolysis increases the risk of death in COVID-19 patients admitted to the ICU. The strongest predictor of a fatal outcome was acute kidney injury. The findings of this study emphasize the importance of early identification and prompt treatment of rhabdomyolysis in patients with severe COVID-19.

Lifestyle, course of COVID-19, and risk of Long-COVID in non-hospitalized patients

INTRODUCTION

The coronavirus disease (COVID) 2019 pandemic remains a great challenge for the healthcare system. The widely reported prolonged signs and symptoms resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (Long-COVID) require medical care. The aim of the study was to assess factors, including lifestyle variables, related to the course of COVID-19 infection and to assess their impact on prolonged symptoms in non-hospitalized patients with COVID-19.

METHODS

A total of 1,847 (637 men and 1,210 women) non-hospitalized participants of the STOP-COVID registry of the PoLoCOV-Study who, following the COVID-19, underwent check-up examinations at the cardiology outpatient clinic were included in the analysis.

RESULTS

The study participants (median age 51 [41-62] years) were evaluated at 13.4 (8.4-23.6) weeks following the diagnosis of COVID-19. Female sex (odds ratio [OR] 1.46 [95% CI 1.19-1.78]), body mass index (BMI; per 1 kg/m2: 1.02 [1.00-1.04]), hypertension (1.39 [1.07-1.81]), asthma (1.55 [1.06-2.27]), stress or overworking (1.54 [1.25-1.90]), and nightshift work (1.51 [1.06-2.14]) were independently related to the severity of symptoms during acute phase of the COVID-19 infection. The Long-COVID syndrome was independently related to the female sex (1.42 [1.13-1.79]), history of myocardial infarction (2.57 [1.04-6.32]), asthma (1.56 [1.01-2.41]), and severe course of the acute phase of the COVID-19 infection (2.27 [1.82-2.83]).

CONCLUSION

Female sex, BMI, asthma, hypertension, nightshifts, and stress or overworking are significantly related to the severity of the acute phase of the COVID-19 infection, while female sex, asthma, history of myocardial infarction, and the severity of symptoms in the acute phase of COVID-19 are the predictors of Long-COVID in non-hospitalized patients. We did not find an independent relation between Long-COVID and the studied lifestyle factors.

Predictive Value of Systemic Immune-Inflammation index and Neutrophil-to-Lymphocyte Ratio in Patients with Severe COVID-19

Objective: It was initially reported that a novel coronavirus (COVID-19) had been identified in Wuhan, China, in December 2019.To date, COVID-19 is still threatening all humanity and has affected the public healthcare system and the world economic situation. Neutrophil-to-lymphocyte ratio (NLR) has also been demonstrated that associated with severity of COVID-19, but little is known about systemic immune-inflammation index (SII) relation with COVID-19. Methods: One hundred and twenty-five patients with diagnosed COVID-19 including non-severe cases (n = 77) and severe cases (n = 48) were enrolled in this study. Each patient of clinical characteristic information, blood routine parameters, and the haemogram-derived ratios were collected, calculated, and retrospectively analyzed. Receiver operating characteristics (ROC) was performed to investigate whether these parameters could be used to the predictive value of patients with severe COVID-19. Results: White blood cell count (WBC), neutrophil count (NEU), red cell volume distribution width (RDW), NLR, Platelet to lymphocyte ratio (PLR), neutrophil-to-platelet ratio (NPR), and SII were significantly higher in the severe groups than in the non-severe group (p < 0.01).Conversely, the severe group had a markedly decreased lymphocyte count, basophil (Baso#) count, red blood cell count (RBC), Hemoglobin (HGB), hematocrit (HCT), and lymphocyte-to-monocyte ratio (LMR) (P < 0.01).ROC curve analysis showed the AUC, optimal cut-off value, sensitivity, specificity of NLR and SII to early predict severe-patients with COVID-19 were 0.867, 7.25, 70.83%, 92.21% and 0.860, 887.20, 81.25%, 81.82%, respectively. Conclusion The results suggest that the SII and NLR is a potential new diagnosed biomarker in severe-patients with COVID-19.