Age-Adjusted D-Dimer in the Prediction of Pulmonary Embolism: Systematic Review and Meta-analysis

Iwuji, Kenneth; Almekdash, Mhd Hasan; Nugent, Kenneth; Islam, Ebtesam; Hyde, Briget; Kopel, Jonathan; Opiegbe, Adaugo; Appiah, Duke

doi:10.1177/21501327211054996

Cited by 15 publications

(7 citation statements)

References 34 publications

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“…In addition, previous studies have shown that the plasma D-dimer level of patients with lung cancer is generally high, which is greatly affected by age, and the difference in lung cancer stage and pathological type may change the optimal critical value for the diagnosis of PE with plasma D-dimer. 44,45 Subgroup analysis based on lung cancer stage and pathological type needs to be further explored in future studies.…”

Section: Discussionmentioning

confidence: 99%

A systematic review of risk prediction model of venous thromboembolism for patients with lung cancer

Wang,

Li,

Zhou

et al. 2024

Thoracic Cancer

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BackgroundVenous thromboembolism (VTE) increases the risk of death or adverse outcomes in patients with lung cancer. Therefore, early identification and treatment of high‐risk groups of VTE have been the research focus. In this systematic review, the risk assessment tools of VTE in patients with lung cancer were systematically analyzed and evaluated to provide a reference for VTE management.MethodsRelevant studies were retrieved from major English databases (The Cochrane Library, Embase, Web of Science, PubMed, Scopus, Medline) and Chinese databases (China National Knowledge Infrastructure [CNKI] and WanFang Data) until July 2023 and extracted by two researchers. This systematic review was registered at PROSPERO (no. CRD42023409748).ResultsFinally, two prospective cohort studies and four retrospective cohort studies were included from 2019. There was a high risk of bias in all included studies according to the Prediction Model Risk of Bias Assessment tool (PROBAST). In the included studies, Cox and logistic regression were used to construct models. The area under the receiver operating characteristic curve (AUC) of the model ranged from 0.670 to 0.904, and the number of predictors ranged from 4 to 11. The D‐dimer index was included in five studies, but significant differences existed in optimal cutoff values from 0.0005 mg/L to 2.06 mg/L. Then, three studies validated the model externally, two studies only validated the model internally, and only one study validated the model using a combination of internal and external validation.ConclusionVTE risk prediction models for patients with lung cancer have received attention for no more than 5 years. The included model shows a good predictive effect and may help identify the risk population of VTE at an early stage. In the future, it is necessary to improve data modeling and statistical analysis methods, develop predictive models with good performance and low risk of bias, and focus on external validation and recalibration of models.

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Section: Discussionmentioning

confidence: 99%

A systematic review of risk prediction model of venous thromboembolism for patients with lung cancer

Wang,

Li,

Zhou

et al. 2024

Thoracic Cancer

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“…So, in elderly patients, the D-dimer level should be adjusted by age. Currently, many studies have already reported the age-adjusted D-dimer cutoff values in elderly patients ( 43 – 45 ). However, there has been no such a concrete and unified calculation formula about the age-adjusted D-dimer.…”

Section: Discussionmentioning

confidence: 99%

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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“…But, compared to age adjusted D-dimer, conventional D-dimer use is associated with higher false positive results. 6 The formula to calculate age-adjusted D-dimer is Age (if over 50 years) x 10 = cutoff value in ng/mL (fibrinogen equivalent units).…”

Section: Triage For Imaging/diagnosismentioning

confidence: 99%

Acute pulmonary embolism: Diagnosis and management

Khandait,

Harkut,

Khandait

et al. 2023

Indian Heart Journal

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Age-Adjusted D-Dimer in the Prediction of Pulmonary Embolism: Systematic Review and Meta-analysis

Cited by 15 publications

References 34 publications

A systematic review of risk prediction model of venous thromboembolism for patients with lung cancer

A systematic review of risk prediction model of venous thromboembolism for patients with lung cancer

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

Acute pulmonary embolism: Diagnosis and management

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