Simple demographic characteristics and laboratory findings on admission may predict in-hospital mortality in patients with SARS-CoV-2 infection: development and validation of the covid-19 score

Analysing COVID-19 treatment outcomes in dedicated wards at a large university hospital in northern Poland: a result-based observational study

OBJECTIVES

Presenting outcomes of patients hospitalised for COVID-19 should be put in context and comparison with other facilities. However, varied methodology applied in published studies can impede or even hinder a reliable comparison. The aim of this study is to share our experience in pandemic management and highlight previously under-reported factors affecting mortality. We present outcomes of COVID-19 treatment in our facility that will allow for an intercentre comparison. We use simple statistical parameters-case fatality ratio (CFR) and length of stay (LOS).

SETTING

Large clinical hospital in northern Poland serving over 120 000 patients annually.

PARTICIPANTS

Data were collected from patients hospitalised in COVID-19 general and intensive care unit (ICU) isolation wards from November 2020 to June 2021. The sample consisted of 640 patients-250 (39.1 %) were women and 390 (60.9 %) were men, with a median age of 69 (IQR 59-78) years.

RESULTS

Values of LOS and CFR were calculated and analysed. Overall CFR for the analysed period was 24.8%, varying from 15.9 % during second quarter 2021 to 34.1% during fourth quarter 2020. The CFR was 23.2% in the general ward and 70.7% in the ICU. All ICU patients required intubation and mechanical ventilation, and 44 (75.9 %) of them developed acute respiratory distress syndrome. The average LOS was 12.6 (±7.5) days.

CONCLUSIONS

We highlighted the importance of some of the under-reported factors affecting CFR, LOS and thus, mortality. For further multicentre analysis, we recommend broad analysis of factors affecting mortality in COVID-19 using simple and transparent statistical and clinical parameters.

Characteristics, Mortality, and Clinical Outcomes of Hospitalized Patients with COVID-19 and Diabetes: A Reference Single-Center Cohort Study from Poland

BACKGROUND

Diabetes is a risk factor for a severe course of COVID-19. We evaluated the characteristics and risk factors associated with undesirable outcomes in diabetic patients (DPs) hospitalized due to COVID-19.

MATERIALS AND METHODS

The data analysis of patients admitted between March 6, 2020, and May 31, 2021, to the University Hospital in Krakow (Poland), a reference center for COVID-19, was performed. The data were gathered from their medical records.

RESULTS

A total number of 5191 patients were included, of which 2348 (45.2%) were women. The patients were at the median age of 64 (IQR: 51-74) years, and 1364 (26.3%) were DPs. DPs, compared to nondiabetics, were older (median age: 70 years, IQR: 62-77 vs. 62, IQR: 47-72, and p < 0.001) and had a similar gender distribution. The DP group had a higher mortality rate (26.2% vs. 15.7%, p < 0.001) and longer hospital stays (median: 15 days, IQR: 10-24 vs. 13, IQR: 9-20, and p < 0.001). DPs were admitted to the ICU more frequently (15.7% vs. 11.0%, p < 0.001) and required mechanical ventilation more often (15.5% vs. 11.3%, p < 0.001). In a multivariate logistic regression, factors associated with a higher risk of death were age >65 years, glycaemia >10 mmol/L, CRP and D-dimer level, prehospital insulin and loop diuretic use, presence of heart failure, and chronic kidney disease. Factors contributing to lower mortality were in-hospital use of statin, thiazide diuretic, and calcium channel blocker.

CONCLUSION

In this large COVID-19 cohort, DPs constituted more than a quarter of hospitalized patients. The risk of death and other outcomes compared to nondiabetics was higher in this group. We identified a number of clinical, laboratory, and therapeutic variables associated with the risk of hospital death in DPs.

Admission Predictors of Mortality in Hospitalized COVID-19 Patients-A Serbian Cohort Study

Background: Early prediction of COVID-19 patients’ mortality risk may be beneficial in adequate triage and risk assessment. Therefore, we aimed to single out the independent morality predictors of hospitalized COVID-19 patients among parameters available on hospital admission. Methods: An observational, retrospective−prospective cohort study was conducted on 703 consecutive COVID-19 patients hospitalized in the University Clinical Center Kragujevac between September and December 2021. Patients were followed during the hospitalization, and in-hospital mortality was observed as a primary end-point. Within 24 h of admission, patients were sampled for blood gas and laboratory analysis, including complete blood cell count, inflammation biomarkers and other biochemistry, coagulation parameters, and cardiac biomarkers. Socio-demographic and medical history data were obtained using patients’ medical records. Results: The overall prevalence of mortality was 28.4% (n = 199). After performing multiple regression analysis on 20 parameters, according to the initial univariate analysis, only four independent variables gave statistically significant contributions to the model: SaO2 < 88.5 % (aOR 3.075), IL-6 > 74.6 pg/mL (aOR 2.389), LDH > 804.5 U/L (aOR 2.069) and age > 69.5 years (aOR 1.786). The C-index of the predicted probability calculated using this multivariate logistic model was 0.740 (p < 0.001). Conclusions: Parameters available on hospital admission can be beneficial in predicting COVID-19 mortality.

Could red cell distribution width be used for predicting cardiac injury in neonates with COVID-19?

BACKGROUND

Coronavirus disease 2019 (COVID-19) can affect people of all age groups and it can occasionally cause life-threatening clinical illnesses in immunologically immature populations, especially in newborns. High red cell distribution width (RDW) values were used as an early prognostic biomarker of some neonatal diseases. We aimed to determine the prognostic value of RDW in severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infected neonates.

METHODS

Newborns with positive SARS-CoV-2 polymerase chain reaction (PCR) test from a nasopharyngeal swab sample, who had refractory fever (>38°C and lasting more than 24 h during hospitalization), were screened for multisystem inflammatory syndrome in newborns (MIS-N), systemic inflammatory indexes calculated and cardiologic evaluations. Due to troponin levels (high: >45 ng/L and low: ≤45 ng/L) patients were grouped.

RESULTS

Out of the 68 SARS-CoV-2 PCR-positive newborns, 26 patients had refractory fever. Comparison of laboratory findings between the high and low-troponin groups showed that RDW and neutrophil/lymphocyte ratio values were significantly higher in patients with high troponin levels (p = 0.022 and p = 0.030, respectively). The cut-off values with optimal sensitivity and specificity were determined as 1.00 for neutrophil/lymphocyte ratio (p = 0.205) and 16.6 for RDW (p = 0.014). None of the patients died.

CONCLUSIONS

Neonatal COVID-19 generally has a benign prognosis, but can progress to severe disease and cases of MIS-N are rare. RDW could be prognostic in the diagnosis and management of neonates with SARS-CoV-2 infection with high troponin levels.

Spatial Variability of COVID-19 Hospitalization in the Silesian Region, Poland

Assessment of regional variation in the COVID-19 epidemic is an important task for the implementation of effective action in public health, especially in densely populated regions. In this descriptive study, the temporal and spatial variability of morbidity and in-hospital mortality of COVID-19 in the Silesian Voivodship (Poland) was analyzed. Secondary epidemiological data of hospitalized patients due to COVID-19 from 1 March to 31 December 2020 and from 1 January to 31 December 2021 were obtained from the regional registry of the Silesian Voivodship Office in Katowice. A year by year (2020 versus 2021) comparative analysis showed a similar course pattern of the COVID-19 pandemic in the Silesian Voivodeship; with the worst situation occurring in the colder months of the year. The percentage of in-hospital mortality remained at a high level, close to 20% during the second year of observation. The risk of death in patients hospitalized due to COVID-19 increased with the number of comorbidities. The highest number of patients was documented in densely inhabited regions with intensive population movement (Częstochowa and border counties). The epidemiological ‘map’ facilitates the generation of hypotheses needed for the explanation of the observed epidemic hazard in one of the most populated regions of Poland.

Predicting progression to severe COVID-19 using the PAINT score

Objectives

One of the major challenges in treating patients with coronavirus disease 2019 (COVID-19) is predicting the severity of disease. We aimed to develop a new score for predicting progression from mild/moderate to severe COVID-19.

Methods

A total of 239 hospitalized patients with COVID-19 from two medical centers in China between February 6 and April 6, 2020 were retrospectively included. The prognostic abilities of variables, including clinical data and laboratory findings from the electronic medical records of each hospital, were analysed using the Cox proportional hazards model and Kaplan–Meier methods. A prognostic score was developed to predict progression from mild/moderate to severe COVID-19.

Results

Among the 239 patients, 216 (90.38%) patients had mild/moderate disease, and 23 (9.62%) progressed to severe disease. After adjusting for multiple confounding factors, pulmonary disease, age > 75, IgM, CD16⁺/CD56⁺ NK cells and aspartate aminotransferase were independent predictors of progression to severe COVID-19. Based on these five factors, a new predictive score (the ‘PAINT score’) was established and showed a high predictive value (C-index = 0.91, 0.902 ± 0.021, p < 0.001). The PAINT score was validated using a nomogram, bootstrap analysis, calibration curves, decision curves and clinical impact curves, all of which confirmed its high predictive value.

Conclusions

The PAINT score for progression from mild/moderate to severe COVID-19 may be helpful in identifying patients at high risk of progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07466-4.

The MaD-CLINYC score: An easy tool for the prediction of the outcome of hospitalized COVID-19 patients

BACKGROUND

Most outcome-predictive models for COVID-19 patients use hospital admission data, offering a spontaneous mortality risk estimation. We aimed to elaborate on a tool that could be applied repeatedly, thus being more suitable for these patients' rapidly changing clinical course.

METHODS

In this prospective study, we evaluated 560 samples derived from 156 patients hospitalized for COVID-19 in a single center. Age >61 years, male sex, comorbidities >2, need for intensive care unit admission, lactate dehydrogenase (LDH) >408 U/L, Neutrophil/Lymphocyte Ratio (NLR) >17, C-reactive protein (CRP) >10 mg/dl, and D-dimers >3,200 ng/ml were incorporated in an eight-scale score (MaD-CLINYC) after optimal scaling, ridge regression, and bootstrapping, which was documented to correlate with outcome independently of one or more samples analyzed, day from admission at sampling, and need for delivery. Validation process was performed over 574 samples derived from three centers.

RESULTS

The developing and the validation cohort Area under Curve (AUC) was 0.90 (95 % Confidence Interval: 0.82-0.98) and 0.91 (0.88-0.94), respectively (p =0.822). A MaD-CLINYC score ≥4 had 75 % sensitivity and 81 % specificity to predict fatal outcome.

CONCLUSIONS

MaD-CLINYC score is a powerful, feasible, easy-to-use, dynamic tool to assess the risk of the outcome, thus assisting clinicians in close monitoring and timely decisions in COVID-19 hospitalized patients. HIPPOKRATIA 2021, 25 (3):119-125.