ArticleClinical interventions in aging2022
Establishment and Validation of a Nomogram to Predict Hospital-Acquired Infection in Elderly Patients After Cardiac Surgery.
Article in Clinical interventions in aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 18 citations in OpenAlex.
- Clinical risk factors for postoperative infection in adult cardiac surgery with cardiopulmonary bypass: a retrospective study.Infection prevention in practice · 2025Article
- Analysis of the current situation and risk factors of nosocomial infections in oral cancer patients after surgery.World journal of surgical oncology · 2025Article
- Risk Factors and Nomogram Prediction Model for Healthcare-Associated Infections (HAIs) in COVID-19 Patients.Infection and drug resistance · 2024Article
- Application of exponential smoothing method and SARIMA model in predicting the number of admissions in a third-class hospital in Zhejiang Province.BMC public health · 2023Article
- Rates and Determinants of Hospital-Acquired Infection among ICU Patients Undergoing Cardiac Surgery in Developing Countries: Results from EMERGENCY'NGO's Hospital in Sudan.Antibiotics (Basel, Switzerland) · 2022Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
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Abstract
backgroundHospital-acquired infection (HAI) after cardiac surgery is a common clinical concern associated with adverse prognosis and mortality. The objective of this study is to determine the prevalence of HAI and its associated risk factors in elderly patients following cardiac surgery and to build a nomogram as a predictive model.
methodsWe developed and internally validated a predictive model from a retrospective cohort of 6405 patients aged ≥70 years, who were admitted to our hospital and underwent cardiac surgery. The primary outcome was HAI. Multivariable logistic regression analysis was used to identify independent factors significantly associated with HAI. The performance of the established nomogram was assessed by calibration, discrimination, and clinical utility. Internal validation was achieved by bootstrap sampling with 1000 repetitions to reduce the overfit bias.
resultsIndependent factors derived from the multivariable analysis to predict HAI were smoking, myocardial infarction, cardiopulmonary bypass use, intraoperative erythrocytes transfusion, extended preoperative hospitalization days and prolonged duration of mechanical ventilation postoperatively. The derivation model showed good discrimination, with a C-index of 0.706 [95% confidence interval 0.671-0.740], and good calibration [Hosmer-Lemeshow test
conclusionsWe developed a predictive nomogram for postoperative HAIs based on routinely available data. This predictive tool may enable clinicians to achieve better perioperative management for elderly patients undergoing cardiac surgery but still requires further external validation.
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