scholarly journals Prognostic assessment in community-acquired pneumonia by pneumonia severity scores and biomarkers

Critical Care ◽  
2010 ◽  
Vol 14 (Suppl 1) ◽  
pp. P75
Author(s):  
F Dusemund ◽  
W Albrich ◽  
P Schuetz ◽  
B Müller
2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jin-liang Liu ◽  
Feng Xu ◽  
Hui Zhou ◽  
Xue-jie Wu ◽  
Ling-xian Shi ◽  
...  

Abstract Aim of this study was to develop a new simpler and more effective severity score for community-acquired pneumonia (CAP) patients. A total of 1640 consecutive hospitalized CAP patients in Second Affiliated Hospital of Zhejiang University were included. The effectiveness of different pneumonia severity scores to predict mortality was compared, and the performance of the new score was validated on an external cohort of 1164 patients with pneumonia admitted to a teaching hospital in Italy. Using age ≥ 65 years, LDH > 230 u/L, albumin < 3.5 g/dL, platelet count < 100 × 109/L, confusion, urea > 7 mmol/L, respiratory rate ≥ 30/min, low blood pressure, we assembled a new severity score named as expanded-CURB-65. The 30-day mortality and length of stay were increased along with increased risk score. The AUCs in the prediction of 30-day mortality in the main cohort were 0.826 (95% CI, 0.807–0.844), 0.801 (95% CI, 0.781–0.820), 0.756 (95% CI, 0.735–0.777), 0.793 (95% CI, 0.773–0.813) and 0.759 (95% CI, 0.737–0.779) for the expanded-CURB-65, PSI, CURB-65, SMART-COP and A-DROP, respectively. The performance of this bedside score was confirmed in CAP patients of the validation cohort although calibration was not successful in patients with health care-associated pneumonia (HCAP). The expanded CURB-65 is objective, simpler and more accurate scoring system for evaluation of CAP severity, and the predictive efficiency was better than other score systems.


2020 ◽  

Objective: In this study, we aimed to explore the role of the plasma presepsin level in patients with community-acquired pneumonia during admission to the emergency department in assessing the diagnosis, severity, and prognosis of the disease. In addition, we wanted to investigate the relationship of presepsinin with procalcitonin, C-reactive protein and pneumonia severity scores. Methods: One hundred twenty-three patients over the age of 18 who presented with a diagnosis of pneumonia to the emergency department were included in the study. The vital signs, symptoms, examination findings, background information, laboratory results, and radiological imaging results of the patients were recorded. The 30-day mortality rates of the patients were determined. Results: A statistically significant difference was found between the presepsin levels of the patients diagnosed with pneumonia and those of healthy subjects (p < 0.05). The plasma presepsin levels of the patients who died (8.63 ± 6.46) were significantly higher than those of the patients who lived (5.82 ± 5.97) (p < 0.05). The plasma procalcitonin and C-reactive protein levels of the dead patients were significantly higher than those living (p < 0.05). A presepsin cut-off value of 3.3 ng/mL for 30-day mortality was established (AUROC, 0.65; specificity, 45%; sensitivity, 82%). Procalcitonin is the most successful biomarker in the determination of mortality (AUROC, 0.70). A significant correlation was available between presepsin and lactate, C-reactive protein and procalcitonin (p < 0.05). There was a significant correlation between the Pneumonia Severity Index values and presepsin levels (p < 0.001, r = 0.311). Conclusion: The plasma presepsin level can be utilized for diagnosing community-acquired pneumonia. Plasma presepsin, procalcitonin and C-reactive protein levels can be used to predict the severity and mortality of community-acquired pneumonia.


2021 ◽  
Vol 8 (1) ◽  
pp. e001045
Author(s):  
Jessica Quah ◽  
Charlene Jin Yee Liew ◽  
Lin Zou ◽  
Xuan Han Koh ◽  
Rayan Alsuwaigh ◽  
...  

BackgroundChest radiograph (CXR) is a basic diagnostic test in community-acquired pneumonia (CAP) with prognostic value. We developed a CXR-based artificial intelligence (AI) model (CAP AI predictive Engine: CAPE) and prospectively evaluated its discrimination for 30-day mortality.MethodsDeep-learning model using convolutional neural network (CNN) was trained with a retrospective cohort of 2235 CXRs from 1966 unique adult patients admitted for CAP from 1 January 2019 to 31 December 2019. A single-centre prospective cohort between 11 May 2020 and 15 June 2020 was analysed for model performance. CAPE mortality risk score based on CNN analysis of the first CXR performed for CAP was used to determine the area under the receiver operating characteristic curve (AUC) for 30-day mortality.Results315 inpatient episodes for CAP occurred, with 30-day mortality of 19.4% (n=61/315). Non-survivors were older than survivors (mean (SD)age, 80.4 (10.3) vs 69.2 (18.7)); more likely to have dementia (n=27/61 vs n=58/254) and malignancies (n=16/61 vs n=18/254); demonstrate higher serum C reactive protein (mean (SD), 109 mg/L (98.6) vs 59.3 mg/L (69.7)) and serum procalcitonin (mean (SD), 11.3 (27.8) μg/L vs 1.4 (5.9) μg/L). The AUC for CAPE mortality risk score for 30-day mortality was 0.79 (95% CI 0.73 to 0.85, p<0.001); Pneumonia Severity Index (PSI) 0.80 (95% CI 0.74 to 0.86, p<0.001); Confusion of new onset, blood Urea nitrogen, Respiratory rate, Blood pressure, 65 (CURB-65) score 0.76 (95% CI 0.70 to 0.81, p<0.001), respectively. CAPE combined with CURB-65 model has an AUC of 0.83 (95% CI 0.77 to 0.88, p<0.001). The best performing model was CAPE incorporated with PSI, with an AUC of 0.84 (95% CI 0.79 to 0.89, p<0.001).ConclusionCXR-based CAPE mortality risk score was comparable to traditional pneumonia severity scores and improved its discrimination when combined.


Author(s):  
Luis Alberto Ruiz Iturriaga ◽  
Ainhoa Gomez Bonilla ◽  
Rafael Zalacain Jorge ◽  
Lorea Martinez-Indart ◽  
Leyre Serrano Fernandez ◽  
...  

2021 ◽  
Vol 29 (1) ◽  
pp. 65-75
Author(s):  
Raluca-Elena Tripon ◽  
Victor Cristea ◽  
Mihaela-Sorina Lupse

Abstract Introduction: Community-acquired pneumonia (CAP) is the primary cause of severe sepsis. Severity assessment scores have been created, in order to help physicians decide the proper management of CAP. The purpose of this study was to examine the correlations between different CAP severity scores, including qSOFA, several biomarkers and their predictive value in the 30 day follow-up period, regarding adverse outcome. Materials and methods: One hundred and thirty nine adult patients with CAP, admitted in the Teaching Hospital of Infectious Diseases, Cluj-Napoca, Romania from December 2015 to February 2017, were enrolled in this study. Pneumonia Severity Index (PSI), CURB-65, SMART-COP and the qSOFA scores were calculated at admittance. Also, C-reactive protein (CRP), procalcitonin (PCT) and albumin levels were used to determine severity. Results: The mean PSI of all patients was 93.30±41.135 points, for CURB-65 it was 1.91±0.928 points, for SMART-COP it was 1.69±1.937 points. The mean qSOFA was 1.06±0.522 points, 21 (14.9%) were at high risk of in-hospital mortality. In the group of patients with qSOFA of ≥2, all pneumonia severity scores and all biomarkers tested were higher than those with scores <2. We found significant correlations between biomarkers and severity scores, but none regarding adverse outcome. Conclusion: The qSOFA score is easier to use and it is able to accurately evaluate the severity of CAP, similar to other scores. Biomarkers are useful in determining the severity of the CAP. Several studies are needed to assess the prediction of these biomarkers and severity scores in pneumonia regarding adverse outcome.


2013 ◽  
Vol 43 (2) ◽  
pp. 97-100 ◽  
Author(s):  
Jonathan Brett ◽  
Vincent Lam ◽  
Melissa T Baysari ◽  
Tamara Milder ◽  
Louise Killen ◽  
...  

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