The Effect of Out-of-Hours Admission on Mortality in Patients Who Underwent Thrombectomy Due to Ischemic Stroke

Background

It is important to investigate the factors that may delay the diagnosis and treatment process of ischemic stroke. The aim of this study was to investigate whether in-hospital mortality increased in patients who presented to the emergency department out-of-hours and underwent thrombectomy.

Methods

A total of 59 patients who applied to the emergency department between January 1, 2018 and November 1, 2021 and underwent thrombectomy due to ischemic stroke were included in the study. Patient age, gender, thrombectomy success (successful recanalization), in-hospital mortality status, intracranial hemorrhage status after thrombectomy, and out-of-hours admission status were recorded and compared according to out-of-hours admission status.

Results

Twenty-seven (45.8%) patients were male, and the median age was 74 (61-81) years. Forty-two (71.2%) patients applied to the emergency department out-of-hours. In-hospital mortality occurred in 27 (45.8%) patients. There was no statistically significant difference in out-of-hours admission status between the non-survivor group and the survivor group (non-survivor: 24 [75%]; survivor: 18 [66.7%], p = 0.481). Nor was a statistically significant difference found in the intracranial hemorrhage complication rate of the patients admitted out-of-hours compared to the patients admitted during working hours (out-of-hours: 17 [40.5%]; during working hours: 6 [35.3%], p = 0.712).

Conclusion

No statistically significant difference was found in the rate of in-hospital mortality and intracranial bleeding complications in patients who underwent thrombectomy out of working hours compared to during working hours.

An Evaluation of the National Early Warning Score 2 and the Laboratory Data Decision Tree Early Warning Score in Predicting Mortality in Geriatric Patients

BACKGROUND

Due to the high rate of geriatric patient visits, scoring systems are needed to predict increasing mortality rates.

OBJECTIVE

In this study, we aimed to investigate the in-hospital mortality prediction power of the National Early Warning Score 2 (NEWS2) and the Laboratory Data Decision Tree Early Warning Score (LDT-EWS), which consists of frequently performed laboratory parameters.

METHODS

We retrospectively analyzed 651 geriatric patients who visited the emergency department (ED), were not discharged on the same day from ED, and were hospitalized. The patients were categorized according to their in-hospital mortality status. The NEWS2 and LDT-EWS values of these patients were calculated and compared on the basis of deceased and living patients.

RESULTS

Median (interquartile range [IQR]) NEWS2 and LDT-EWS values of the 127 patients who died were found to be statistically significantly higher than those of the patients who survived (NEWS2: 5 [3-8] vs. 3 [1-5]; p < 0.001; LDT-EWS: 8 [7-10] vs. 6 [5-8]; p < 0.001). In the receiver operating characteristic curve analysis, the NEWS2, LDT-EWS, and NEWS2+LDT-EWS-formed by the sum of the two scoring systems-resulted in 0.717, 0.705, and 0.775 area under curve values, respectively.

CONCLUSIONS

The NEWS2 and LDT-EWS were found to be valuable for predicting in-hospital mortality in geriatric patients. The power of the NEWS2 to predict in-hospital mortality increased when used with the LDT-EWS.

The Role of Procalcitonin/Albumin Ratio and CRP/Albumin Ratio in Predicting In-hospital Mortality in COVID-19 Patients

Background

Hospitalized coronavirus disease 2019 (COVID-19) patients have higher mortality rates. Parameters to predict mortality are needed. Therefore, we investigated the power of procalcitonin/albumin ratio (PAR) and C-reactive protein/albumin ratio (CAR) to predict in-hospital mortality in hospitalized COVID-19 patients.

Methods

In this study, 855 patients were included. Patients' PAR and CAR values were recorded from the hospital information management system. The patients were evaluated in two groups according to their in-hospital mortality status.

Results

In-hospital mortality was observed in 163 patients (19.1%). The median PAR and CAR values of patients in the non-survivor group were statistically significantly higher than those of patients in the survivor group, PAR (median: 0.07, interquartile range [IQR]: 0.03-0.33 vs. median: 0.02, IQR: 0.01-0.04, respectively; p < 0.001); CAR (median: 27.60, IQR: 12.49-44.91 vs. median: 7.47, IQR: 2.66-18.93, respectively; p < 0.001). The area under the curve (AUC) and odds ratio (OR) values obtained by PAR to predict in-hospital mortality were higher than the values obtained by procalcitonin, CAR, albumin, and CRP (AUCs of PAR, procalcitonin, CAR, albumin, and CRP: 0.804, 0.792, 0.762, 0.755, and 0.748, respectively; OR: PAR > 0.04, procalcitonin > 0.14, CAR > 20.59, albumin < 4.02, and CRP > 63; 8.215, 7.134, 5.842, 6.073, and 5.07, respectively). Patients with concurrent PAR > 0.04 and CAR > 20.59 had an OR of 15.681 compared to patients with concurrent PAR < 0.04 and CAR < 20.59.

Conclusions

In this study, PAR was found to be more valuable for predicting in-hospital COVID-19 mortality than all other parameters. In addition, concurrent high levels of PAR and CAR were found to be more valuable than a high level of PAR or CAR alone.

Predictive value of D-dimer/albumin ratio and fibrinogen/albumin ratio for in-hospital mortality in patients with COVID-19

INTRODUCTION

Due to the high mortality of coronavirus disease 2019 (COVID-19), there are difficulties in the managing emergency department. We investigated whether the D-dimer/albumin ratio (DAR) and fibrinogen/albumin ratio (FAR) predict mortality in the COVID-19 patients.

METHODS

A total of 717 COVID-19 patients who were brought to the emergency department from March to October 2020 were included in the study. Levels of D-dimer, fibrinogen and albumin, as well as DAR, FAR, age, gender and in-hospital mortality status of the patients, were recorded. The patients were grouped by in-hospital mortality. Statistical comparison was conducted between the groups.

RESULTS

Of the patients included in the study, 371 (51.7%) were male, and their median age was 64 years (50-74). There was in-hospital mortality in 126 (17.6%) patients. The area under the curve (AUC) and odds ratio values obtained by DAR to predict in-hospital mortality were higher than the values obtained by the all other parameters (AUC of DAR, albumin, D-dimer, FAR and fibrinogen: 0.773, 0.766, 0.757, 0.703 and 0.637, respectively; odds ratio of DAR > 56.36, albumin < 4.015, D-dimer > 292.5, FAR > 112.33 and fibrinogen > 423:7.898, 6.216, 6.058, 4.437 and 2.794, respectively). In addition; patients with concurrent DAR > 56.36 and FAR > 112.33 had an odds ratio of 21.879 with respect to patients with concurrent DAR < 56.36 and FAR < 112.33.

CONCLUSION

DAR may be used as a new marker to predict mortality in COVID-19 patients. In addition, the concurrent high DARs and FARs were found to be more valuable in predicting in-hospital mortality than either separately.

The role of the BUN/albumin ratio in predicting mortality in COVID-19 patients in the emergency department

Introduction

Due to the high mortality and spread rates of coronavirus disease 2019 (COVID-19), there are currently serious challenges in emergency department management. As such, we investigated whether the blood urea nitrogen (BUN)/albumin ratio (BAR) predicts mortality in the COVID-19 patients in the emergency department.

Methods

A total of 602 COVID-19 patients who were brought to the emergency department within the period from March to September 2020 were included in the study. The BUN level, albumin level, BAR, age, gender, and in-hospital mortality status of the patients were recorded. The patients were grouped by in-hospital mortality. Statistical comparison was conducted between the groups.

Results

Of the patients who were included in the study, 312(51.8%) were male, and their median age was 63 years (49–73). There was in-hospital mortality in 96(15.9%) patients. The median BUN and BAR values of the patients in the non-survivor group were significantly higher than those in the survivor group (BUN: 24.76 [17.38–38.31] and 14.43 [10.84–20.42], respectively [p < 0.001]; BAR: 6.7 [4.7–10.1] and 3.4 [2.5–5.2], respectively [p < 0.001]). The mean albumin value in the non-survivor group was significantly lower than that in the survivor group (3.60 ± 0.58 and 4.13 ± 0.51, respectively; p < 0.001). The area-under-the-curve (AUC) and odds ratio values obtained by BAR to predict in-hospital COVID-19 mortality were higher than the values obtained by BUN and albumin (AUC of BAR, BUN, and albumin: 0.809, 0.771, and 0.765, respectively; odds ratio of BAR>3.9, BUN>16.05, and albumin<4.01: 10.448, 7.048, and 6.482, respectively).

Conclusion

The BUN, albumin, and BAR levels were found to be reliable predictors of in-hospital mortality in COVID-19 patients, but BAR was found to be a more reliable predictor than the BUN and albumin levels.

The role of soluble urokinase plasminogen activator receptor (SuPAR) as an indicator of the severity of acute pancreatitis

Background/aim

Soluble urokinase plasminogen activator receptor (suPAR) has been reported to have a positive correlation with the activation degree of the immune system. This study’s aim is to investigate the efficiency of SuPAR serum levels in acute pancreatitis (AP) patients in determining the severity of disease.

Materials and methods

This prospective research involves patients who arrived at the emergency service, were over 18 years old, had nontraumatic abdominal pain and diagnosis of AP, and agreed to join the study. Demographic characteristics, contact information, laboratory and imaging test parameters, Ranson’s criteria, the Balthazar Severity Index, the Rapid Acute Physiologic Score (RAPS), and the modified Glasgow (Imrie) score of all patients were recorded. Two study groups were created as score of <3 (mild, Group I) and ≥3 (severe, Group II) for pancreatitis according to Ranson’s criteria.

Results

During the study period, 59 sequential patients with AP were included in the study. It was seen that 79.7% of the study group (n = 47) were in Group I. Etiologically 67.8% (n = 40) cases were biliary and 32.3% (n = 19) were nonbiliary diseases. According to the results, suPAR level was effective in distinguishing the severity of AP (AUC = 0.902, P < 0.001 (95% CI: 0.821–0.984)). With regard to determining severe disease, suPAR had an optimum cutoff value of 6.815 ng/mL, sensitivity of 91.66%, specificity of 82.97%, and negative predictive value of 97.5%.

Conclusion

Our study was performed the determine the efficiency of suPAR level in predicting severe disease in AP patients. We found it significant in indicating the severity of disease according to the study results.