Development and validation of a new scoring system for prognostic prediction of community-acquired pneumonia in older adults

Shirata, Masahiro; Ito, Isao; Ishida, Tadashi; Takahashi, Hiromasa; Tanabe, Naoya; Konishi, Satoshi; Oi, Issei; Hamao, Nobuyoshi; Nishioka, Kanae; Matsumoto, Hisako; Yasutomo, Yoshiro; Kadowaki, Seizo; Ohnishi, Hisashi; Tomioka, Haruaki; Nishimura, Takashi; Hasegawa, Yoshinori; Nakagawa, Atsushi; Hirai, Toyohiro

doi:10.1038/s41598-021-03440-3

Cited by 7 publications

(8 citation statements)

References 37 publications

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“…In details, the AUC of the nomogram model was about 0.9 for predicting in-hospital mortality of CAP and observed to be higher than PSI, CURB-65 and qSOFA values (0.85, 0.86, and 0.71, respectively). Among them, the evidence for the application of 4 selected variables (Age, Pulse, NLR, and BUN) in our model has been supported by various studies ( 19 – 23 ). Here, we also reported that the addition of serum albumin (ALB) and D-dimer can improve the predictive ability for mortality of CAP in patients aged ≥ 65 years.…”

Section: Discussionsupporting

confidence: 67%

Section: Discussionsupporting

confidence: 57%

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Exploration of prognostic factors for prediction of mortality in elderly CAP population using a nomogram model

Shi

et al. 2022

Front. Med.

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BackgroundThe incidence and mortality rate of community-acquired pneumonia (CAP) in elderly patients were higher than the younger population. The assessment tools including CURB-65 and qSOFA have been applied in early detection of high-risk patients with CAP. However, several disadvantages exist to limit the efficiency of these tools for accurate assessment in elderly CAP. Therefore, we aimed to explore a more comprehensive tool to predict mortality in elderly CAP population by establishing a nomogram model.MethodsWe retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University. The least absolute shrinkage and selection operator (LASSO) logistic regression combined with multivariate analyses were used to select independent predictive factors and established nomogram models via R software. Calibration plots, decision curve analysis (DCA) and receiver operating characteristic curve (ROC) were generated to assess predictive performance.ResultsLASSO and multiple logistic regression analyses showed the age, pulse, NLR, albumin, BUN, and D-dimer were independent risk predictors. A nomogram model (NB-DAPA model) was established for predicting mortality of CAP in elderly patients. In both training and validation set, the area under the curve (AUC) of the NB-DAPA model showed superiority than CURB-65 and qSOFA. Meanwhile, DCA revealed that the predictive model had significant net benefits for most threshold probabilities.ConclusionOur established NB-DAPA nomogram model is a simple and accurate tool for predicting in-hospital mortality of CAP, adapted for patients aged 65 years and above. The predictive performance of the NB-DAPA model was better than PSI, CURB-65 and qSOFA.

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Section: Discussionsupporting

confidence: 67%

Section: Discussionsupporting

confidence: 57%

Exploration of prognostic factors for prediction of mortality in elderly CAP population using a nomogram model

Shi

et al. 2022

Front. Med.

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“…In one study, Sakakibara et al 35 established a new score model including albumin to predict severe adverse events (including death) in CAP patients, which exhibits a higher AUC value (0.85) compared with the other predictive models. Furthermore, another study by Shirata et al 25 developed another albumin-based system (using cutoff as 3.0 g/dL) to predict mortality in older patients with CAP, showing a higher AUC (0.809) than that of CURB-65. In addition, albumin decreased with aging for several potential reasons such as decline in cognition, poor oral health, and dysphagia 36 , 37 .…”

Section: Discussionmentioning

confidence: 99%

Establishment of risk model for elderly CAP at different age stages: a single-center retrospective observational study

Lv,

Pan,

Shi

et al. 2023

Sci Rep

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Community-acquired pneumonia (CAP) is one of the main reasons of mortality and morbidity in elderly population, causing substantial clinical and economic impacts. However, clinically available score systems have been shown to demonstrate poor prediction of mortality for patients aged over 65. Especially, no existing clinical model can predict morbidity and mortality for CAP patients among different age stages. Here, we aimed to understand the impact of age variable on the establishment of assessment model and explored prognostic factors and new biomarkers in predicting mortality. We retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University. We used univariate and multiple logistic regression analyses to study the prognostic factors of mortality in each age-based subgroup. The prediction accuracy of the prognostic factors was determined by the Receiver Operating Characteristic curves and the area under the curves. Combination models were established using several logistic regressions to save the predicted probabilities. Four factors with independently prognostic significance were shared among all the groups, namely Albumin, BUN, NLR and Pulse, using univariate analysis and multiple logistic regression analysis. Then we built a model with these 4 variables (as ABNP model) to predict the in-hospital mortality in all three groups. The AUC value of the ABNP model were 0.888 (95% CI 0.854–0.917, p < 0.000), 0.912 (95% CI 0.880–0.938, p < 0.000) and 0.872 (95% CI 0.833–0.905, p < 0.000) in group 1, 2 and 3, respectively. We established a predictive model for mortality based on an age variable -specific study of elderly patients with CAP, with higher AUC value than PSI, CURB-65 and qSOFA in predicting mortality in different age groups (66–75/ 76–85/ over 85 years).

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“…Since Japan has one of the world’s highest life expectancies, it is likely that CURB-65 would not perform as well if applied to a Japanese cohort. Interestingly, CURB-65 also performs poorly when applied to Colombian patients (AUCs of 0.629-0.669 when tested against 3 cohorts) 20 . Hincapie suggested that this may be due to the factors underpinning a significant difference in community-acquired pneumonia-associated mortality (9.5% 17 versus 17-32% 20 ).…”

Section: Discussionmentioning

confidence: 99%

“…Interestingly, CURB-65 also performs poorly when applied to Colombian patients (AUCs of 0.629-0.669 when tested against 3 cohorts) 20 . Hincapie suggested that this may be due to the factors underpinning a significant difference in community-acquired pneumonia-associated mortality (9.5% 17 versus 17-32% 20 ). Although it has been suspected that this is the case, we note that biomarkers and prognostic scores developed in large multi-center trials in predominantly developed countries continue to be used in other countries and be incorporated into national guidelines without prior validation.…”

Section: Discussionmentioning

confidence: 99%

Mapping of biomarker efficacy in SARS-CoV-2: tracking the impact of viral mutations and vaccinations

Shuvo

Schwiening

Soares

et al. 2022

Preprint

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Objectives: Sophisticated scores have been proposed for prognostication of mortality due to SARS-CoV-2 but perform inconsistently. We conducted these meta-analyses to uncover why and to pragmatically seek a single dependable biomarker for mortality. Design: We searched the PubMed database for the keywords SARS-CoV-2 with biomarker name and mortality. All studies published from 01st December 2019 to 30th June 2021 were surveyed. To aggregate the data, the meta library in R was used to report overall mean values and 95% confidence intervals. We fitted a random effects model to obtain pooled AUCs and associated 95% confidence intervals for the European/North American, Asian, and overall datasets. Setting and Participants: Data was collected from 131 studies on SARS-CoV-2 PCR-positive general hospital adult admissions (n=76,169 patients in total). Main Outcome Measures: We planned a comparison of pooled area under curves (AUCs) from Receiver Operator Characteristic curves plotted for admission D-dimer, CRP, urea, troponin and interleukin-6 levels. Main Results: Biomarker effectiveness varies significantly in different regions of the world. Admission CRP levels are a good prognostic marker for mortality due to SARS-CoV-2 in Asian countries, with a pooled area under curve (AUC) of 0.83 (95% CI 0.80-0.85), but only an average predictor of mortality in Europe/North America, with a pooled AUC of 0.67 (95% CI 0.63-0.71, P<0.0001). We observed the same pattern for D-dimer and IL-6. This variability explains why the proposed prognostic scores did not perform evenly. Notably, urea and troponin had pooled AUCs ≥ 0.78 regardless of location, implying that end-organ damage at presentation is a key prognostic factor. These differences might be due to age, genetic backgrounds, or different modes of death (younger patients in Asia dying of cytokine storm while older patients die of multi-organ failure). Conclusions: Biomarker effectiveness for prognosticating SARS-CoV-2 mortality varies significantly by geographical location. We propose that biomarkers and by extension prognostic scores need to be tailored for specific populations. This also implies that validation of commonly used prognostic scores for other conditions should occur before they are used in different populations.

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Development and validation of a new scoring system for prognostic prediction of community-acquired pneumonia in older adults

Cited by 7 publications

References 37 publications

Exploration of prognostic factors for prediction of mortality in elderly CAP population using a nomogram model

Exploration of prognostic factors for prediction of mortality in elderly CAP population using a nomogram model

Establishment of risk model for elderly CAP at different age stages: a single-center retrospective observational study

Mapping of biomarker efficacy in SARS-CoV-2: tracking the impact of viral mutations and vaccinations

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