A nomogram for predicting post‐operative wound complications after open reduction and internal fixation for calcaneal fractures

Hu, Wei; Huang, Chengbin; Zhang, Yingying; Wang, Xingyu; Jiang, Yanshu

doi:10.1111/iwj.13822

Cited by 5 publications

(3 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nomograms, which are intuitive and visualized risk prediction models, have been widely used in recent years to predict cancer and surgical prognosis 12 – 14 , can rapidly and accurately identify high-risk groups and can improve the diagnostic efficacy. In the latest research, a nomogram was used to predict the occurrence of refractory Mycoplasma pneumoniae pneumonia (RMPP) in children and bronchial mucus plugs in children with MPP, and both showed good predictive performance 15 , 16 .…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting Mycoplasma pneumoniae pneumonia in adults

Ren

Wang

Liang

et al. 2022

Sci Rep

View full text Add to dashboard Cite

The study aimed to explore predictors of Mycoplasma pneumoniae pneumonia (MPP) in adults and develop a nomogram predictive model in order to identify high-risk patients early. We retrospectively analysed the clinical data of a total of 337 adult patients with community-acquired pneumonia (CAP) and divided them into MPP and non-MPP groups according to whether they were infected with MP. Univariate and multivariate logistic regression analyses were used to screen independent predictors of MPP in adults and to developed a nomogram model. Receiver operating characteristic (ROC) curve, calibration curve, concordance index (C-index), and decision curve analysis (DCA) were used for the validation of the evaluation model. Finally, the nomogram was further evaluated by internal verification. Age, body temperature, dry cough, dizziness, CRP and tree-in-bud sign were independent predictors of MPP in adults (P < 0.05). The nomogram showed high accuracy with C-index of 0.836 and well-fitted calibration curves in both the training and validation sets. The area under the receiver operating curve (AUROC) was 0.829 (95% CI 0.774–0.883) for the training set and 0.847 (95% CI 0.768–0.925) for the validation set. This nomogram prediction model can accurately predict the risk of MPP occurrence in adults, which helps clinicians identify high-risk patients at an early stage and make drug selection and clinical decisions.

show abstract

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting Mycoplasma pneumoniae pneumonia in adults

Ren

Wang

Liang

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…To date, numerous studies have investigated the characteristics and patterns of LNM in EGC patients globally; however, there is still no accurate prediction model. Many scholars now view nomograms as efficient instruments for predicting tumor progression and guiding clinical decision-making[ 5 - 10 ]. Prediction models are commonly employed for diagnosis and prognosis evaluation[ 11 , 12 ] and to determine tumor stage, predict recurrence and metastasis risk, estimate patient survival rates[ 11 ], and evaluate therapeutic efficacy[ 12 - 17 ].…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer

He,

Cao,

et al. 2024

World J Gastrointest Oncol

View full text Add to dashboard Cite

BACKGROUND Lymph node metastasis (LNM) significantly impacts the treatment and prognosis of early gastric cancer (EGC). Consequently, the precise prediction of LNM risk in EGC patients is essential to guide the selection of appropriate surgical approaches in clinical settings. AIM To develop a novel nomogram risk model for predicting LNM in EGC patients, utilizing preoperative clinicopathological data. METHODS Univariate and multivariate logistic regression analyses were performed to examine the correlation between clinicopathological factors and LNM in EGC patients. Additionally, univariate Kaplan-Meier and multivariate Cox regression analyses were used to assess the influence of clinical factors on EGC prognosis. A predictive model in the form of a nomogram was developed, and its discrimination ability and calibration were also assessed. RESULTS The incidence of LNM in the study cohort was 19.6%. Multivariate logistic regression identified tumor size, location, degree of differentiation, and pathological type as independent risk factors for LNM in EGC patients. Both tumor pathological type and LNM independently affected the prognosis of EGC. The model’s performance was reflected by an area under the curve of 0.750 [95% confidence interval (CI): 0.701-0.789] for the training group and 0.763 (95%CI: 0.687-0.838) for the validation group. CONCLUSION A clinical prediction model was constructed (using tumor size, low differentiation, location in the middle-lower region, and signet ring cell carcinoma), with its score being a significant prognosis indicator.

show abstract

“…To date, there have been many studies globally on the characteristics and regularity of LNM in EGC, but there is still no accurate prediction model. An increasing number of scholars believe that nomograms are effective tools for predicting tumour progression and aiding clinical decision-making [5][6][7][8][9][10] Prediction models are widely used to predict diagnosis and evaluate prognosis [11,12] , tumour stage, recurrence, metastasis, patient survival, and therapeutic e cacy [13][14][15][16][17][18] , There have been numerous studies worldwide on nomograms for the prediction of LNM in EGC [19][20][21] . Cui [22] et al established a nomogram for predicting LNM in EGC, which included patient sex, tumour morphology, vascular invasion, lymphangiosarcoma thrombosis, tumour length, tumour invasion depth, and tumour differentiation degree.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of nomogram for predicting lymph node metastasis in early gastric cancer

Cao

et al. 2023

Preprint

View full text Add to dashboard Cite

Purpose: To establish and verify a prediction model for lymph node metastasis (LNM) in early gastric cancer (EGC) and provide a reference for the selection of appropriate treatment for EGC patients. Methods: The clinicopathological data of 1584 patients with EGC admitted to Zhejiang Cancer Hospital from January 2010 to April 2019 were retrospectively analysed. Univariate and multivariate logistic regression analyses were used to explore the correlation between various clinicopathological factors and LNM in patients with EGC. Univariate K‒M and multivariate Cox regression analyses were used to explore the influence of multiple clinical factors on the prognosis of patients with EGC. The discrimination and calibration of the established prediction model, which is presented in the form of a nomogram, were also evaluated. Results: The incidence of LNM was 19.6%. Multivariate logistic regression analysis showed that tumour size, location, differentiation degree and pathological type were independent risk factors for LNM in EGC. Tumour pathological type and LNM were independent factors affecting the prognosis of patients with EGC. The area under the curve in the training and verification group was 0.750 (95% CI: 0.701 ~ 0.789) and 0.763 (95% CI: 0.687 ~ 0.838), respectively. The calibration curve showed good agreement between the predicted and actual probability, and decision curve analysis indicated strong clinical practicability. Conclusion: Tumour diameter ≥ 2 cm, poor differentiation degree, middle-lower tumour location and signet ring cell carcinoma were identified as independent risk factors for LNM in EGC. Among them, tumour pathological type and LNM were independent risk factors for prognosis in EGC. This clinical model for predicting LNM in EGC was used to construct a nomogram, which has high diagnostic value and can serve as a reference in clinical treatment selection.

show abstract

A nomogram for predicting post‐operative wound complications after open reduction and internal fixation for calcaneal fractures

Cited by 5 publications

References 53 publications

Development and validation of a nomogram for predicting Mycoplasma pneumoniae pneumonia in adults

Development and validation of a nomogram for predicting Mycoplasma pneumoniae pneumonia in adults

Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer

Development and validation of nomogram for predicting lymph node metastasis in early gastric cancer

Contact Info

Product

Resources

About