Alpha-1-antitrypsin-deficiency is associated with lower cardiovascular risk: an approach based on federated learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory multisystemic disease caused by environmental exposures and/or genetic factors. Inherited alpha-1-antitrypsin deficiency (AATD) is one of the best recognized genetic factors increasing the risk for an early onset COPD with emphysema. The aim of this study was to gain a better understanding of the associations between comorbidities and specific biomarkers in COPD patients with and without AATD to enable future investigations aimed, for example, at identifying risk factors or improving care. METHODS: We focused on cardiovascular comorbidities, blood high sensitivity troponin (hs-troponin) and lipid profiles in COPD patients with and without AATD. We used clinical data from six German University Medical Centres of the MIRACUM (Medical Informatics Initiative in Research and Medicine) consortium. The codes for the international classification of diseases (ICD) were used for COPD as a main diagnosis and for comorbidities and blood laboratory data were obtained. Data analyses were based on the DataSHIELD framework. RESULTS: Out of 112,852 visits complete information was available for 43,057 COPD patients. According to our findings, 746 patients with AATD (1.73%) showed significantly lower total blood cholesterol levels and less cardiovascular comorbidities than non-AATD COPD patients. Moreover, after adjusting for the confounder factors, such as age, gender, and nicotine abuse, we confirmed that hs-troponin is a suitable predictor of overall mortality in COPD patients. The comorbidities associated with AATD in the current study differ from other studies, which may reflect geographic and population-based differences as well as the heterogeneous characteristics of AATD. CONCLUSION: The concept of MIRACUM is suitable for the analysis of a large healthcare database. This study provided evidence that COPD patients with AATD have a lower cardiovascular risk and revealed that hs-troponin is a predictor for hospital mortality in individuals with COPD.

Early ACL reconstruction shows an improved recovery of isokinetic thigh muscle strength compared to delayed or chronic cases.

INTRODUCTION: The recovery of periarticular strength is a major criterion in return-to-play testing. The rationale of the study was to assess the impact of the delay of surgery (∆ between injury and surgery) on knee extensor and knee flexor strength of anterior cruciate ligament (ACL)-deficient patients six months after reconstruction. MATERIALS AND METHODS: In a retrospective cohort study, all patients with ACL ruptures between 03/2015 and 12/2019 were analyzed. Inclusion criteria were isolated ACL rupture without any associated lesions undergoing a reconstruction using ipsilateral hamstring tendon autograft and adherence to isokinetic strength testing before and at 5-7 months postoperatively. These patients were then clustered into three groups: EARLY reconstruction (∆ < 42 days), DELAYED reconstruction (∆42-180d), and CHRONIC (∆ > 180d). Knee extensor and flexor strength of the ipsi- and contralateral leg were analyzed by concentric isokinetic measurement (60°/s). Primary outcomes were the maximal knee extension and flexion torque, hamstrings-to-quadriceps ratio (H/Q) ratio), and the corresponding limb symmetry indices. RESULTS: n = 444 patients met the inclusion criteria. From EARLY to DELAYED to CHRONIC, a progressive reduction in postoperative strength performance was observed in knee extension (1.65 ± 0.45 to 1.62 ± 0.52 to 1.51 ± 0.5 Nm/kg resp.) and flexion (1.22 ± 0.29 to 1.18 ± 0.3 to 1.13 ± 0.31 Nm/kg resp.) strength on the ACL reconstructed leg. This general loss in periarticular strength was already apparent in the preoperative performance even on the healthy side. When controlling for the preoperative performance using ANCOVA analysis, EARLY performed significantly better than DELAYED (extension p = 0.001, flexion p = .02) and CHRONIC (extension p = 0.005, flexion p < 0.001). Also, there were significantly higher values for H/Q ratio in the injured leg across all groups where the H/Q ratio increased from EARLY to CHRONIC and from pre- to postoperative values. CONCLUSIONS: With respect to the force generating capacity when returning-to-play, it is advantageous to seek for an early ACL reconstruction within the first 12 weeks after the injury. The increasing loss of thigh muscle strength observed in delayed or chronic cases affects the injured and also the non-injured leg. LEVEL OF EVIDENCE: III, retrospective cohort study.

Predicting the Recovery of Isokinetic Knee Strength 6 Months After Anterior Cruciate Ligament Reconstruction.

Background: The limb symmetry index (LSI) is a metric of strength restoration. It is key to successfully return to sports after anterior cruciate ligament (ACL) reconstruction. The threshold for return to sports is generally considered an LSI of ≥85%. Purpose: To develop a statistical model for predicting the recovery of knee extension and flexion strength (with LSI ≥85%) at 6 months after ACL reconstruction. Study Design: Case-control study; Level of evidence: 3. Methods: Patients who underwent arthroscopic ACL reconstruction between November 2015 and December 2020 were included. The patients were classified into 2 groups: "pass" if the LSI at 6 months postoperatively was ≥85% and "fail" if the LSI was <85%. Factors in 25 categories with 74 levels, including patient characteristics, periarticular procedures, intra-articular lesions and treatment, and perioperative management, were collected. A multivariable logistic regression combined with backward variable elimination was used to determine the predictive parameters for recovery of knee extension and flexion strength. Results: A total of 948 patients were included. Graft site, preoperative isokinetic strength, treatment of meniscal injury, and injured side (left vs right) were identified as general predictors for both knee extension and flexion strength. For knee extension strength, age at injury and partial weightbearing duration were identified as additional predictors. For knee flexion strength, type of meniscal injury, surgeon volume, cartilage procedures, and periarticular procedures were identified as additional predictors. The Nagelkerke R 2 of the final model was 0.178, and the c-statistic was 0.716 (95% CI, 0.676-0.754). The Hosmer-Lemeshow test indicated good calibration (P = .879). Conclusion: Several factors including preoperative isokinetic strength, treatment of meniscal injuries, left vs. right side and graft site were found to predict recovery of ≥85% LSI in knee extension and flexion strength. Despite the numerous factors that were analyzed, the predictive power was moderate (c-statistic = 0.716), indicating there were other nonincluded factors that significantly influence strength performance at 6 months postoperatively.

dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD.

OBJECTIVE: Achieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions could be a potential challenge for achieving this added power. Hence we implemented a federated meta-analysis approach of survival models in DataSHIELD, where only anonymous aggregated data are shared across institutions, while simultaneously allowing for exploratory, interactive modelling. In this case, meta-analysis techniques to combine analysis results from each site are a solution, but an analytic workflow involving local analysis undertaken at individual studies hinders exploration. Thus, the aim is to provide a framework for performing meta-analysis of Cox regression models across institutions without manual analysis steps for the data providers. RESULTS: We introduce a package (dsSurvival) which allows privacy preserving meta-analysis of survival models, including the calculation of hazard ratios. Our tool can be of great use in biomedical research where there is a need for building survival models and there are privacy concerns about sharing data.