scholarly journals Development a Nomogram to Predict Prognosis in Severe and Critically Ill Patients with COVID-19

2020 ◽  
Author(s):  
Weiping Tan ◽  
Ying Zhu ◽  
Hui Yi ◽  
Yingyu Lin ◽  
Yumei Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Severity ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Poor Prognosis ◽  
Total Bilirubin ◽  
Lung Involvement ◽  
Factors Associated ◽  
Independent Risk Factors ◽  
D Dimer

Abstract Background: The number of deaths caused by COVID-19 are on the rising worldwide. This study focused on severe and critically ill COVID-19, aim to explore independent risk factors associated with disease severity and to build a nomogram to predict patients’ prognosis.Methods: Patients with laboratory-confirmed COVID-19 admitted to the Union Hospital, Tongji Medical College and Hankou Hospital of Wuhan, China, from February 8th to April 6th, 2020. LASSO Regression and Multivariate Analysis were applied to screen independent factors. COX Nomogram was built to predict the 7-day, 14-day and 1-month survival probability.Results: A total of 115 severe [73 (63.5%)] and critically ill [42 (36.5%)] patients were included in this study, containing 93 (80.9%) survivors and 22 (19.1%) non-survivors. For disease severity, D-dimer [OR 6.33 (95%CI, 1.27-45.57], eosinophil percentage [OR 8.02 (95%CI, 1.82-45.04)], total bilirubin [OR 12.38 (95%CI, 1.24-223.65)] and lung involvement score [OR 1.22 (95%CI, 1.08-1.40)] were the independent factors associated with critical illness. Troponin [HR 9.02 (95%CI, 3.02, 26.97)] and total bilirubin [HR 3.16 (95%CI, 1.13, 8.85)] were the independent predictors for patients’ prognosis. Troponin≥26.2 ng/L and total bilirubin＞20 μmol/L were associated with poor prognosis. The nomogram based on the independent risk factors had a C-index of 0.92 (95%CI, 0.87, 0.98) for predicting survival probability. The survival nomogram validated in the critically ill patients had a C-index of 0.83 (95%CI: 0.75, 0.94).Conclusions: In conclusion, in severe and critically ill patients with COVID-19, D-dimer, eosinophil percentage, total bilirubin and lung involvement score were the independent risk factors associated with disease severity. The proposed survival nomogram accurately predicted prognosis. The survival analysis may suggest that early incidence of multiple organ dysfunction may be an important predictor of poor prognosis.

scholarly journals Factors associated with 90-day acute ischemic stroke in patients ≥70 years old with total hip arthroplasty for hip fracture

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui He ◽  
Guoyou Wang ◽  
Ting Li ◽  
Huarui Shen ◽  
LijuanZhang
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Hip Fracture ◽  
Total Hip Arthroplasty ◽  
Older Age ◽  
Factors Associated ◽  
Independent Risk Factors ◽  
D Dimer

Abstract Background Postoperative ischemic stroke is a devastating complication following total hip arthroplasty (THA). The purpose of the current study was to investigate the incidence of postoperative acute ischemic stroke (AIS) in patients ≥70 years old with THA for hip fracture after 90 days and independent risk factors associated with 90-day AIS. Methods A multicenter retrospective study was conducted, patients ≥70 years old with THA for hip fracture under general anesthesia were included from February 2017 to March 2020. Patients with AIS within 90 days after THA were identified as AIS group; patients with no AIS were identified as no AIS group. The baseline characteristics and risk factors were collected, multivariable logistic regression was used to identify independent risk factors of 90-dayAIS. Results: 2517 patients (mean age 76.18 ± 6.01) were eligible for inclusion in the study. 2.50% (63/2517) of patients had 90-day AIS. Compared with no AIS, older age, diabetes, hyperlipidemia, atrial fibrillation (AF) and higher D-dimer value were more likely in patients with AIS (P < 0.05), and anticoagulant use was fewer in patients with AIS. ROC curve analysis showed that the optimal cut point of D-dimer for AIS was D-dimer≥4.12 μg/ml. Multivariate logistic regression analysis showed that D-dimer≥4.12 μg/ml [adjusted odds ratio (aOR), 4.44; confidence interval (CI), 2.50–7.72; P < 0.001], older age (aOR, 1.08; 95%CI, 1.03–1.12; P < 0.001), hyperlipidemia (aOR, 2.28; 95%CI, 1.25–4.16; P = 0.007), atrial fibrillation (aOR, 5.84; 95% CI, 1.08–15.68; P = 0.001), and diabetes (aOR, 2.60; 95% CI, 1.56–4.39; P < 0.001) were associated with increased risk of 90-day AIS after THA. Conclusions In conclusion, we found that the incidence of 90-day AIS in patients≥70 years old with THA for hip fracture was 2.5%. Older age, diabetes, hyperlipidemia, AF and higher D-dimer value were independent risk factors for 90-day AIS in patients≥70 years old with THA for hip fracture.

scholarly journals Risk Factors For Kidney Damage In COVID-19 Patients Admitted To The Intensive Care Unit

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Diana K. Sarkisian ◽  
Natalia V. Chebotareva ◽  
Valerie McDonnell ◽  
Armen V. Oganesyan ◽  
Tatyana N. Krasnova ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Kidney Injury ◽  
Kidney Damage ◽  
Elderly Age ◽  
Total Blood ◽  
Independent Risk Factors

Background — Acute kidney injury (AKI) reaches 29% in the intensive care unit (ICU). Our study aimed to determine the prevalence, features, and the main AKI factors in critically ill patients with coronavirus disease 2019 (COVID-19). Material and Methods — The study included 37 patients with COVID-19. We analyzed the total blood count test results, biochemical profile panel, coagulation tests, and urine samples. We finally estimated the markers of kidney damage and mortality. Result — All patients in ICU had proteinuria, and 80.5% of patients had hematuria. AKI was observed in 45.9% of patients. Independent risk factors were age more than 60 years, increased C-reactive protein (CRP) level, and decreased platelet count. Conclusion — Kidney damage was observed in most critically ill patients with COVID-19. The independent risk factors for AKI in critically ill patients were elderly age, a cytokine response with a high CRP level.

scholarly journals Risk factors associated with Acinetobacter baumannii septicemia and its mortality rates in critically ill patients

Critical Care ◽  
2013 ◽  
Vol 17 (S2) ◽  
Author(s):  
K Kontopoulou ◽  
K Tsepanis ◽  
I Sgouropoulos ◽  
A Triantafyllidou ◽  
D Socratous ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acinetobacter Baumannii ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Mortality Rates ◽  
Factors Associated

Risk factors associated with the onset of daptomycin non-susceptibility in Staphylococcus aureus infections in critically ill patients

2014 ◽  
Vol 41 (2) ◽  
pp. 366-368 ◽  
Author(s):  
Matteo Bassetti ◽  
Giovanni Villa ◽  
Filippo Ansaldi ◽  
Daniela De Florentiis ◽  
Carlo Tascini ◽  
...  
Keyword(s):  
Risk Factors ◽  
Staphylococcus Aureus ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Factors Associated

Intraoperative Risk Factors Associated With Postoperative Pressure Ulcers in Critically Ill Patients

2014 ◽  
Vol 42 (1) ◽  
pp. 40-47 ◽  
Author(s):  
Denise D. O’Brien ◽  
Amy M. Shanks ◽  
AkkeNeel Talsma ◽  
Phyllis S. Brenner ◽  
Satya Krishna Ramachandran
Keyword(s):  
Risk Factors ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Pressure Ulcers ◽  
Factors Associated

scholarly journals Diabetes and Hemoglobin A1c as Risk Factors for Nosocomial Infections in Critically Ill Patients

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Eirini Tsakiridou ◽  
Demosthenes Makris ◽  
Vasiliki Chatzipantazi ◽  
Odysseas Vlachos ◽  
Grigorios Xidopoulos ◽  
...  
Keyword(s):  
Risk Factors ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Prospective Observational Study ◽  
Hemoglobin A1c ◽  
District Hospital ◽  
Bloodstream Infections ◽  
Inclusion Criteria ◽  
Icu Mortality ◽  
Independent Risk Factors

Objective. To evaluate whether diabetes mellitus (DM) and hemoglobin A1c (HbA1c) are risk factors for ventilator-associated pneumonia (VAP) and bloodstream infections (BSI) in critically ill patients.Methods. Prospective observational study; patients were recruited from the intensive care unit (ICU) of a general district hospital between 2010 and 2012. Inclusion criteria: ICU hospitalization >72 hours and mechanical ventilation >48 hours. HbA1c was calculated for all participants. DM, HbA1c, and other clinical and laboratory parameters were assessed as risk factors for VAP or BSI in ICU.Results. The overall ICU incidence of VAP and BSI was 26% and 30%, respectively. Enteral feeding OR (95%CI) 6.20 (1.91–20.17;P=0.002) and blood transfusion 3.33 (1.23–9.02;P=0.018) were independent risk factors for VAP. BSI in ICU (P=0.044) and ICU mortality (P=0.038) were significantly increased in diabetics. Independent risk factors for BSI in ICU included BSI on admission 2.45 (1.14–5.29;P=0.022) and stroke on admission2.77 (1.12–6.88;P=0.029). Sepsis 3.34 (1.47–7.58;P=0.004) and parenteral feeding 6.29 (1.59–24.83;P=0.009) were independently associated with ICU mortality. HbA1c ≥ 8.1% presented a significant diagnostic performance in diagnosing repeated BSI in ICU.Conclusion. DM and HbA1c were not associated with increased VAP or BSI frequency. HbA1c was associated with repeated BSI episodes in the ICU.

scholarly journals Accuracy of a Bedside Swallow Test After Extubation in ICU: A Prospective Validation of a Clinical Test Compared to a Fiberoptic Endoscopy.

2020 ◽  
Author(s):  
Adel Maamar ◽  
Valentine Parent ◽  
Emmanuel Guérot ◽  
Pauline Berneau ◽  
Aurélien Frérou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Validation Cohort ◽  
Clinical Test ◽  
Exclusion Criteria ◽  
Predictive Values ◽  
Swallowing Evaluation ◽  
Independent Risk Factors ◽  
Preliminary Study

Abstract Background: Swallowing disorders (SDs) are frequent after extubation in intensive care unit (ICU) exposing patients to aspiration pneumonia. There is no validated bedside swallowing evaluation (BSE) after extubation. We aimed to evaluate the accuracy of our BSE in comparison with fiberoptic endoscopic evaluation of swallowing (FEES) in critically ill patients after extubation, and to identify the incidence and risk factors of SD.Methods: After a preliminary study in a first center, we conducted a 1-year prospective study as a validation cohort in a second center. Patients intubated for longer than 48 hours were included. Exclusion criteria were a known laryngeal pathology, a preexisting SD and an admission for stroke. FEES of the larynx and BSE were assessed within 24 hours after extubation to compare the accuracy of the BSE to the FEES procedure.Results: One hundred and twenty eight patients were included, respectively 69 and 79 in the preliminary study and the validation cohort. Thirteen of 69 (19%) and 33/79 (42%) had SD assessed by FEES. The area under curve (AUC) reached respectively 0.86 (95% CI 0.73-0.98) and 0.83 (95% CI 0.74-0.92). Sensitivities were 77% (95% CI 0.54-0.99) and 85% (95% CI 0.73-0.94), specificities 94% (95% CI 0.87-0.98) and 80% (95% CI 0.7-0.91), and negative predictive values (NPV) were 95% and 90% in respectively preliminary study and validation cohort. Independent risk factors for SD were duration of intubation (OR=1.08; 95% CI 1.02-1.17, p=0.03) and hemodynamic failure (OR=4.46; 95% CI 1.27-21, p=0.03).Conclusion: Our BSE is accurate to detect SDs after extubation in critically ill patients and can easily be implemented in an ICU setting.

scholarly journals Mortality Predictors in Severe COVID-19 Patients from an East European Tertiary Center: A Never-Ending Challenge for a No Happy Ending Pandemic

2021 ◽  
Vol 11 (1) ◽  
pp. 58
Author(s):  
Amalia-Stefana Timpau ◽  
Radu-Stefan Miftode ◽  
Antoniu Octavian Petris ◽  
Irina-Iuliana Costache ◽  
Ionela-Larisa Miftode ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hospital Mortality ◽  
Poor Prognosis ◽  
Survival Rates ◽  
C Reactive Protein ◽  
Happy Ending ◽  
Factors Associated ◽  
Reactive Protein ◽  
Tertiary Center ◽  
D Dimer

(1) Background: There are limited clinical data in patients from the Eastern European regions hospitalized for a severe form of Coronavirus disease 2019 (COVID-19). This study aims to identify risk factors associated with intra-hospital mortality in patients with COVID-19 severe pneumonia admitted to a tertiary center in Iasi, Romania. (2) Methods: The study is of a unicentric retrospective observational type and includes 150 patients with severe COVID-19 pneumonia divided into two subgroups, survivors and non-survivors. Demographic and clinical parameters, as well as comorbidities, laboratory and imaging investigations upon admission, treatments, and evolution during hospitalization were recorded. First, we sought to identify the risk factors associated with intra-hospital mortality using logistic regression. Secondly, we assessed the correlations between D-Dimer and C-reactive protein and predictors of poor prognosis. (3) Results: The predictors of in-hospital mortality identified in the study are D-dimers >0.5 mg/L (p = 0.002), C-reactive protein >5mg/L (p = 0.001), and heart rate above 100 beats per minute (p = 0.001). The biomarkers were also significantly correlated the need for mechanical ventilation, admission to intensive care unit, or multiple organ dysfunction syndrome. By area under the curve (AUC) analysis, we noticed that both D-Dimer (AUC 0.741) and C-reactive protein (AUC 0.707) exhibit adequate performance in predicting a poor prognosis in patients with severe viral infection. (4) Conclusions: COVID-19′s outcome is significantly influenced by several laboratory and clinical factors. As mortality induced by severe COVID-19 pneumonia is considerable, the identification of risk factors associated with negative outcome coupled with an early therapeutic approach are of paramount importance, as they may significantly improve the outcome and survival rates.

scholarly journals Characteristics and Risk Factors Associated With Mortality in Critically Ill Patients With COVID-19

Cureus ◽  
2021 ◽  
Author(s):  
Yannick Vogels ◽  
Sjaak Pouwels ◽  
Jos van Oers ◽  
Dharmanand Ramnarain
Keyword(s):  
Risk Factors ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Factors Associated
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