Dataset Information

Performance of age-adjusted D-dimer values for predicting DVT before the knee and hip arthroplasty.

ABSTRACT:

Purpose

To compare the specificity and sensitivity of preoperative D-dimer and age-adjusted D-dimer value for predicting the incidence of the DVT preoperatively in total joint arthroplasty (TJA) patients.

Methods

We enrolled 406 patients finally above 50?years old. Everyone had done ultrasonography bedside, and D-dimer concentrations were collected before surgery. The D-dimer and age-adjusted D-dimer cut-off was calculated by multiple logistic regression and receiver operating curve (ROC) analyses.

Results

A total of 39 patients had found asymptomatic deep vein thrombosis (DVT) by ultrasonography. The age (odds ratio [OR] 1.067; p = 0.003) and D-dimer (OR 1.331; p = 0.025) were related to the existence of DVT. For conventional D-dimer and age-adjusted D-dimer value, the area under the curves (AUCs) were 0.685 (0.499-0.696) and 0.795 (0.611-0.881), respectively.

Conclusion

Compared to traditional D-dimer, age-adjusted D-dimer showed better performance in screening DVT, which was useful clinically.

SUBMITTER: Wu JX

PROVIDER: S-EPMC7831181 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Performance of age-adjusted D-dimer values for predicting DVT before the knee and hip arthroplasty.

Wu Jian Xiang JX Qing Jiang Hui JH Yao Yao Y Chen Dong Yang DY Jiang Qing Q

Journal of orthopaedic surgery and research 20210125 1

<h4>Purpose</h4>To compare the specificity and sensitivity of preoperative D-dimer and age-adjusted D-dimer value for predicting the incidence of the DVT preoperatively in total joint arthroplasty (TJA) patients.<h4>Methods</h4>We enrolled 406 patients finally above 50 years old. Everyone had done ultrasonography bedside, and D-dimer concentrations were collected before surgery. The D-dimer and age-adjusted D-dimer cut-off was calculated by multiple logistic regression and receiver operating cur ...[more]

PMID: 33494760

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Project description:BackgroundTotal joint replacements are high-volume and high-cost procedures that should be monitored for cost and quality control. Models that can identify patients at high risk of readmission might help reduce costs by suggesting who should be enrolled in preventive care programs. Previous models for risk prediction have relied on structured data of patients rather than clinical notes in electronic health records (EHRs). The former approach requires manual feature extraction by domain experts, which may limit the applicability of these models.ObjectiveThis study aims to develop and evaluate a machine learning model for predicting the risk of 30-day readmission following knee and hip arthroplasty procedures. The input data for these models come from raw EHRs. We empirically demonstrate that unstructured free-text notes contain a reasonably predictive signal for this task.MethodsWe performed a retrospective analysis of data from 7174 patients at Partners Healthcare collected between 2006 and 2016. These data were split into train, validation, and test sets. These data sets were used to build, validate, and test models to predict unplanned readmission within 30 days of hospital discharge. The proposed models made predictions on the basis of clinical notes, obviating the need for performing manual feature extraction by domain and machine learning experts. The notes that served as model inputs were written by physicians, nurses, pathologists, and others who diagnose and treat patients and may have their own predictions, even if these are not recorded.ResultsThe proposed models output readmission risk scores (propensities) for each patient. The best models (as selected on a development set) yielded an area under the receiver operating characteristic curve of 0.846 (95% CI 82.75-87.11) for hip and 0.822 (95% CI 80.94-86.22) for knee surgery, indicating reasonable discriminative ability.ConclusionsMachine learning models can predict which patients are at a high risk of readmission within 30 days following hip and knee arthroplasty procedures on the basis of notes in EHRs with reasonable discriminative power. Following further validation and empirical demonstration that the models realize predictive performance above that which clinical judgment may provide, such models may be used to build an automated decision support tool to help caretakers identify at-risk patients.

Project description:BackgroundProphylactic antibiotics have significantly led to a reduction in the risk of post-operative surgical site infections (SSI) in orthopaedic surgery. The aim of using antibiotics for this purpose is to achieve serum and tissue drug levels that exceed, for the duration of the operation, the minimum inhibitory concentration of the likely organisms that are encountered. Prophylactic antibiotics reduce the rate of SSIs in lower limb arthroplasty from between 4% and 8% to between 1% and 3%. Controversy, however, still surrounds the optimal frequency and dosing of antibiotic administration.AimTo evaluate the impact of introduction of a weight-adjusted antibiotic prophylaxis regime, combined with a reduction in the duration of administration of post-operative antibiotics on SSI incidence during the 2 years following primary elective total hip and knee arthroplasty.MethodsFollowing ethical approval, patients undergoing primary total hip arthroplasty (THA)/total knee arthroplasty (TKA) with the old regime (OR) of a preoperative dose [cefazolin 2 g intravenously (IV)], and two subsequent doses (2 h and 8 h), were compared to those after a change to a new regime (NR) of a weight-adjusted preoperative dose (cefazolin 2 g IV for patients < 120 kg; cefazolin 3g IV for patients > 120 kg) and a post-operative dose at 2 h. The primary outcome in both groups was SSI rates during the 2 years post-operatively.ResultsA total of n = 1273 operations (THA n = 534, TKA n = 739) were performed in n = 1264 patients. There was no statistically significant difference in the rate of deep (OR 0.74% (5/675) vs NR 0.50% (3/598); fishers exact test P = 0.72), nor superficial SSIs (OR 2.07% (14/675) vs NR 1.50% (9/598); chi-squared test P = 0.44) at 2 years post-operatively. With propensity score weighting and an interrupted time series analysis, there was also no difference in SSI rates between both groups [RR 0.88 (95%CI 0.61 to 1.30) P = 0.46].ConclusionA weight-adjusted regime, with a reduction in number of post-operative doses had no adverse impact on SSI incidence in this population.

Dataset Information

Performance of age-adjusted D-dimer values for predicting DVT before the knee and hip arthroplasty.

Purpose

Methods

Results

Conclusion

Publications

Performance of age-adjusted D-dimer values for predicting DVT before the knee and hip arthroplasty.

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