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Background: Machine-learning models may improve prediction of length of stay (LOS) and morbidity after surgery. However, few studies include fast-track programs, and most rely on administrative coding with limited follow-up and information on perioperative care. This study investigates potential benefits of a machine-learning model for prediction of postoperative morbidity in fast-track total hip (THA) and knee arthroplasty (TKA). Methods: Cohort study in consecutive unselected primary THA/TKA between 2014–2017 from seven Danish centers with established fast-track protocols. Preoperative comorbidity and prescribed medication were recorded prospectively and information on length of stay and readmissions was obtained through the Danish National Patient Registry and medical records. We used a machine-learning model (Boosted Decision Trees) based on boosted decision trees with 33 preoperative variables for predicting "medical" morbidity leading to LOS > 4 days or 90-days readmissions and compared to a logistical regression model based on the same variables. We also evaluated two parsimonious models, using the ten most important variables in the full machine-learning and logistic regression models. Data collected between 2014–2016 (n:18,013) was used for model training and data from 2017 (n:3913) was used for testing. Model performances were analyzed using precision, area under receiver operating (AUROC) and precision recall curves (AUPRC), as well as the Mathews Correlation Coefficient. Variable importance was analyzed using Shapley Additive Explanations values. Results: Using a threshold of 20% "risk-patients" (n:782), precision, AUROC and AUPRC were 13.6%, 76.3% and 15.5% vs. 12.4%, 74.7% and 15.6% for the machine-learning and logistic regression model, respectively. The parsimonious machine-learning model performed better than the full logistic regression model. Of the top ten variables, eight were shared between the machine-learning and logistic regression models, but with a considerable age-related variation in importance of specific types of medication. Conclusion: A machine-learning model using preoperative characteristics and prescriptions slightly improved identification of patients in high-risk of "medical" complications after fast-track THA and TKA compared to a logistic regression model. Such algorithms could help find a manageable population of patients who may benefit most from intensified perioperative care. [ABSTRACT FROM AUTHOR]

Introduction: Gastrointestinal complications after total hip (THA) and knee arthroplasty (TKA) have been reported to be between 0.3 and 2.6% with bleeding and C. difficile infection in 0–1%, and 0.1–1.7%, respectively. The use of enhanced recovery or "fast-track" protocols have focused on optimizing all aspects of perioperative care resulting in reduced length of hospital stay (LOS) and potentially also gastrointestinal complications. This study is a detailed analysis on the occurrence of postoperative gastrointestinal complications resulting in increased hospital stay or readmissions in a large consecutive cohort of fast-track THA and TKA with complete 90 days follow-up. Materials and methods: This is an observational study on a consecutive cohort of primary unilateral THAs and TKAs performed between January 2010 and August 2017 in nine Danish high-volume fast-track centers. Discharge summaries and relevant patient records were reviewed in patients with readmissions within 90 days or LOS > 4 days caused by gastrointestinal complications. Results: The cohort included 36,932 patients with 58.3% females and 54.1% THAs. Mean age and BMI were 68 years and 28. Median postoperative LOS was 2 days. Only n: 276 (0.75 %) had a LOS > 4 days or a readmission within 90 days due to a gastrointestinal complication (CI 0.67%–0.84%). Of these, only 34 (0.09%) were graded as severe ileus or gastrointestinal bleeding. Conclusions: The risk of GI-complications within the first 90 postoperative days after fast-track THA and TKA was low (0.75%). [ABSTRACT FROM AUTHOR]

Background: Peripheral nerve blocks (PNB) have recently been recommended in total hip (THA) and knee (TKA) arthroplasty as they may reduce pain, morphine consumption, length of stay (LOS) and complications. However, whether PNBs are associated with early discharge within an enhanced recovery protocol including multimodal analgesia is uncertain. Methods: An observational multicenter study from January to August 2017 in six Danish Arthroplasty Centers with established fast‐track protocols. Prospective recording of preoperative characteristics and information on PNB, LOS and readmissions through the Danish National Patient Registry and medical records. Multiple logistic regression was used to investigate associations between PNB and a LOS >1 day, LOS >4 days, and 30‐days readmissions. We also reported on mobilization, pain, opioid and fall‐related complications leading to LOS >4 days or readmissions. Results: A total of 2027 (58.6%) THA and 1432 (41.4%) TKAs with a median LOS of 1 day (IQR 1–2) and 5.3% (CI:4.6–6.1) 30‐days readmission rate were identified. PNB was used in 40.7% (CI:38.2–43.3) of TKA and 2.7% (CI:2.0–3.5) of THA, but with considerable interdepartmental variation (0.0–89.0% for TKA). There was no association between PNB and LOS >1 day (OR:1.19 CI:0.82–1.72; p =.354), LOS >4 days (OR:1.4 CI:0.68–2.89; p =.359) or 30‐days readmissions (OR:1.02 CI:0.63–1.65; p =.935) in TKA. Logistic regression in THA was not possible due to limited use of PNB. In TKA there were 12 (2.1% CI:1.2–3.6) with and 1 (0.1% CI:0.02–0.7) without a PNB, who had mobilization, pain or opioid‐related complications, and 5 (0.9% CI:0.4–2.0) versus 4 (0.5% CI:0.2–1.2) who fell. Correspondingly, 2 (3.7% CI:1.0–12.6) and 11 (0.6% CI:0.3–1.0) of THA patients had these complications, while 0 (0.0% CI:0.0–6.6) and 17 (0.8% CI:0.5–1.3) fell. Conclusion: Routine use of peripheral nerve blocks was not associated with early discharge or 30‐days readmissions in fast‐track THA and TKA. Future studies should focus on benefits of PNB in high‐risk patients. [ABSTRACT FROM AUTHOR]

Background and purpose -- Prediction of postoperative outcomes and length of hospital stay (LOS) of patients is vital for allocation of healthcare resources. We investigated the performance of prediction models based on machinelearning algorithms compared with a previous risk stratification model using traditional multiple logistic regression, for predicting the risk of a LOS of > 2 days after fast-track total hip and knee replacement. Patients and methods -- 3 different machine learning classifiers were trained on data from the Lundbeck Centre for Fast-track Hip and Knee Replacement Database (LCDB) collected from 9,512 patients between 2016 and 2017. The chosen classifiers were a random forest classifier (RF), a support vector machine classifier with a polynomial kernel (SVM), and a multinomial Naïve-Bayes classifier (NB). Results -- Comparing performance measures of the classifiers with the traditional model revealed that all the models had a similar performance in terms of F1 score, accuracy, sensitivity, specificity, area under the receiver operating curve (AUC), and area under the precision-recall curve (AUPRC). A feature importance analysis of the RF classi- fier found hospital, age, use of walking aid, living alone, and joint operated on to be the most relevant input features. None of the classifiers reached a clinically relevant performance with the input data from the LCDB. Interpretation -- Despite the promising prospects of machine-learning practices for disease and risk prediction, none of the machine learning models tested outperformed the traditional multiple regression model in predicting which patients in this cohort had a LOS > 2 days. [ABSTRACT FROM AUTHOR]

Background and purpose — Enhanced recovery programs have reduced length of stay (LOS) after hip and knee arthroplasty (THA/TKA). Although risk factors disposing to prolonged LOS are well documented, there is limited information on the role of weekday of surgery. This study analyzed the role of weekday of surgery and other potential risk factors for LOS > 2 days. Patients and methods — We included 10,576 unselected consecutive procedures between January 2016 and August 2017 within a multicenter fast-track THA/TKA collaboration with prospective collection of preoperative characteristics. We used multiple regression analysis of potential risk factors for LOS > 2 days followed by construction of a simple risk score from 0 to 15 points based on the calculated odds ratios. Results — Mean LOS was 1.9 (SD 1.8) days, with 80% of patients having surgery from Monday to Wednesday. Of these, 17% (95% CI 16–18) had a LOS > 2 days vs. 19% (CI 17–21) in those operated on Thursday and Friday. Patients were scheduled evenly throughout the week regardless of risk of LOS > 2 days and despite the fact that 38% (CI 35–40) of patients with ≥ 6 points (16% of the total population) had a LOS > 2 days compared with 14% (CI 13–14) in those with < 6 points. In these "high-risk" patients, the fraction with LOS > 2 days increased when having surgery on Thursdays or Fridays (43% CI 38–49) compared with Monday to Wednesday (37% CI 34–39). Interpretation — A detailed preoperative risk assessment may be helpful to plan the weekday of surgery in order to decrease LOS and weekend hospitalization. [ABSTRACT FROM AUTHOR]

Background: Days alive and out of hospital (DAH) has been proposed as a pragmatic outcome measure of surgical quality. However, there is a lack of procedure specific data or data within an optimised fast-track protocol. Furthermore, information about influence of follow-up duration and types of complications on DAH is limited.Methods: Observational multicentre cohort study of patients undergoing fast-track total hip (THA) and knee arthroplasty (TKA). Prospective information on comorbidity and complete 90 days follow-up was undertaken through the Danish National Patient Register and chart review.Results: For 16 137 procedures, of which 18.6% were high-risk (≥2 preoperative risk factors), the median length of stay was 2 days (inter-quartile range [IQR], 2-3), and 30- and 90-day readmission rates were 5.7% and 8.1%, respectively. Median DAH30 and DAH90 days were 27 (26-28) and 87 (85-88) vs 28 (27-28) and 88 (87-89) (P<0.001) in high-vs low-risk patients, respectively. The fraction with DAH ≤25 at 30 days and DAH ≤85 at 90 days was increased in high-vs low-risk patients: 23.3% vs 6.8% (odds ratio [OR]=4.16; 95% confidence interval [CI], 3.73-4.65) and 26.0% vs 8.6% (OR=3.75; 95% CI, 3.38-4.16). There were relatively fewer 'surgical' complications in high- vs low-risk patients with DAH30 ≤25 (14.6% vs 25.8%) (OR=0.49; 95% CI, 0.37-0.65) and DAH90 ≤85 (16.9% vs 31.89%) (OR=0.43; 95% CI, 0.34-0.56). About 2% of patients had readmissions, but DAH was >25 and >85 at 30 and 90 days after operation, respectively.Conclusion: Median DAH in fast-track THA/TKA patients is 28 at 30 days and 88 at 90 days after surgery. DAH in high-risk patients was only slightly reduced compared with low-risk patients, but they have relatively more 'medical' complications. [ABSTRACT FROM AUTHOR]

Background and purpose — Acute myocardial infarction (MI) is a leading cause of mortality following total hip and knee arthroplasty (THA/TKA). The reported 30-day incidence of MI varies from 0.3% to 0.9%. However, most data derive from administration and insurance databases or large RCTs with potential confounding factors. We studied the incidence of and potential modifiable risk factors for postoperative MI in a large, multicenter optimized "fast-track" THA/TKA setting. Patients and methods — A prospective cohort study was conducted on consecutive unselected elective primary unilateral THA and TKA, using prospective information on comorbidities and complete 90-day follow-up from the Danish National Patient Registry. Evaluation of discharge summaries and medical records was undertaken in cases of suspected MI. Logistic regression analyses were carried out for identification of preoperative risk factors. Results — Of 24,862 procedures with a median length of stay 2 (IQR 2-3) days, 30- and 90-day incidence of MI was 31 (0.12%) and 48 (0.19%). Preoperative risk factors for MI ≤30 days were age >85 years (OR 7.4, 95% CI 2.3-24), insulin-dependent diabetes mellitus (IDDM) (3.6, CI 1.1-12), cardiovascular disease (2.4, CI 1.1-5.0) and hypercholesterolemia (2.3, CI 1.1-5.1). Of 31 patients with MI ≤30 days 9 were treated with vasopressors for intraoperative hypotension and 27 had postoperative anemia. Interpretation — Fast-track THA and TKA had a low 30-day MI incidence. Focus on patients with age >85, IDDM, cardiovascular disease, and hypercholesterolemia may further reduce the 30-day incidence of MI. The role of postoperative anemia and intraoperative hypotension are other areas for further improvement [ABSTRACT FROM AUTHOR]