Nomogram for predicting in‐hospital mortality of nonagenarians with community‐acquired pneumonia

Abstract

Aim Nonagenarians with community‐acquired pneumonia (CAP) have a high mortality rate; however, appropriate tools for reliable severity assessment in this population are lacking. The current study aimed to evaluate the risk factors and establish a nomogram to predict in‐hospital mortality of nonagenarians with CAP. Methods In total, 304 patients aged ≥90 years who were admitted with CAP to Jiangsu Provincial People's Hospital and Jiangsu Provincial Hospital of Chinese Medicine between 2014 and 2020 were retrospectively analyzed. Clinical information, laboratory imaging results and pathogen detection were retrieved. Significant variables independently associated with CAP were identified by a logistic regression model, and a nomogram prediction model was constructed. The nomogram was compared with the widely used assessments: CURB‐65, PSI and National Early Warning Score (NEWS) scores. Results Univariate and multivariate logistic regression analyses identified gender, blood urea nitrogen, C‐reactive protein‐to‐albumin ratio, Charlson Comorbidity Index and systemic immune inflammation index as independent factors that affect the prognosis. We created a nomogram for CAP based on these risk factors. The nomogram had a bootstrapped concordance index of 0.796 and was well‐calibrated in the decision analysis curve range of 0.1–0.98. The area under the curve was 0.796 (95% CI: 0.74–0.85), significantly higher than for CURB‐65, PSI and NEWS scores (P < 0.05). Conclusions Our nomogram model can predict the outcome of hospitalized nonagenarians with CAP and guide clinicians to provide better treatment, leading to improved prognosis and reduced mortality. Geriatr Gerontol Int 2022; 22: 635–641.

Utility of pneumonia severity assessment tools for mortality prediction in healthcare-associated pneumonia: a systematic review and meta-analysis

“…Further investigation is needed, but age and comorbidities may be overvalued in predicting pneumonia severity in elderly patients such as HCAP 39 . Furthermore, the influence of the general condition, such as “bedridden state” and “low serum albumin” as well as inflammatory biomarkers, such as “CRP level” and “neutrophil-to-lymphocyte ratio” has been shown for predicting mortality in elderly patients with pneumonia 47 , 48 . Therefore, these explain the low AUC value despite a large number of items, as the prognosis might be more strongly influenced by the ordinal general condition than the presence of comorbid diseases in these patients 43 .…”

Risk factors and nomogram-based prediction of the risk of limb weakness in herpes zoster

“…Nomogram is widely used in both oncologic and non-oncologic diseases ( Huang et al, 2022 ; Zan et al, 2022 ; Zhang et al, 2022 ). Nomograms can create a simple graphical representation of a statistical predictive model that generates a numerical probability of a clinical event ( Iasonos et al, 2008 ).…”