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Construction of a prediction model for community-acquired pneumonia in the elderly population and analysis of prevention and treatment strategies
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Yang-zhong WANG1, Xue-bin TANG2, Dao-yong LIU3
Modern Preventive Medicine | 2026, 53(12) : 2220 - 2225
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Modern Preventive Medicine | 2026, 53(12): 2220-2225
• Primary Health Service •
Construction of a prediction model for community-acquired pneumonia in the elderly population and analysis of prevention and treatment strategies
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Yang-zhong WANG1, Xue-bin TANG2, Dao-yong LIU3
Affiliations
  • School of Medicine, Chongqing University, Department of Respiratory and Critical Care Medicine, Fuling Hospital Affiliated to Chongqing University, Chongqing 408000, China
Published: 2026-06-25 doi: 10.20043/j.cnki.MPM.202601295
Outline
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Objective

To investigate the distribution of pathogenic bacteria in community-acquired pneumonia among the elderly population, to construct a risk assessment model for high-risk groups of community-acquired pneumonia, and to provide a basis for clinical prevention and control of pneumonia.

Methods

A total of 163 elderly patients with community-acquired pneumonia who were hospitalized in Chongqing Fuling Hospital, School of Medicine, from January 2020 to January 2025 were included as the pneumonia group, and another 180 elderly people with normal physical examinations during the same period were selected as the control group. By comparing the baseline data of the two groups of patients, logistic multivariate analysis was used to identify the independent risk factors for the occurrence of community-acquired pneumonia in the elderly. Based on the results of the factor analysis, a nomogram prediction model was constructed. The model’s efficacy was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and Hosmer-Lemeshow goodness-of-fit test.

Results

A total of 172 pathogenic bacteria were isolated from 163 patients with community-acquired pneumonia, with Candida albicans (41.10%) and Klebsiella pneumoniae (31.29%) accounting for the highest proportion. The results of the logistic analysis showed that smoking history (OR=1.971, 95%CI: 1.396 - 2.783), cerebrovascular disease (OR=1.300, 95%CI: 1.013 - 1.668), anemia (OR=1.281, 95%CI: 1.014 - 1.618), liver and kidney dysfunction (OR=2.037, 95%CI: 1.008 - 4.118), septic shock (OR=2.299, 95%CI: 1.074 - 4.922), consciousness disorder (OR=1.635, 95%CI:1.074 - 2.488), animal breeding (OR=1.901, 95%CI: 1.364 - 2.648), and dust exposure (OR=1.478, 95%CI: 1.048 - 2.085) were all independent risk factors for community-acquired pneumonia in the elderly(P<0.05). The ROC curve of the nomogram showed that the AUC=0.710 (95%CI: 0.661 - 0.759), the sensitivity was 0.702, and the specificity was 0.813. The Hosmer-Lemeshow test result showed:P=0.36 (P > 0.05).

Conclusion

Smoking history, cerebrovascular disease, anemia, liver and kidney dysfunction, etc. are all independent risk factors for community-acquired pneumonia in the elderly. Early prevention and control of these risk factors should be strengthened to reduce the risk of pneumonia occurrence.

Community-acquired pneumonia  /  Elderly  /  Prediction  /  Risk factors  /  Early intervention
王杨中, 汤雪斌, 刘道勇. 老年人群社区获得性肺炎的病原菌分布及发生风险评估模型的构建. 现代预防医学, 2026 , 53 (12) : 2220 -2225 . DOI: 10.20043/j.cnki.MPM.202601295
Yang-zhong WANG, Xue-bin TANG, Dao-yong LIU. Construction of a prediction model for community-acquired pneumonia in the elderly population and analysis of prevention and treatment strategies[J]. Modern Preventive Medicine, 2026 , 53 (12) : 2220 -2225 . DOI: 10.20043/j.cnki.MPM.202601295
Year 2026 volume 53 Issue 12
194
72
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doi: 10.20043/j.cnki.MPM.202601295
  • Receive Date:2026-01-19
  • Online Date:2026-09-28
  • Published:2026-06-25
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  • Received:2026-01-19
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    School of Medicine, Chongqing University, Department of Respiratory and Critical Care Medicine, Fuling Hospital Affiliated to Chongqing University, Chongqing 408000, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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