Prevention and treatment of peri-implant diseases—The EFP S3 level clinical practice guideline

Background: The recently published Clinical Practice Guidelines (CPGs) for the treatment of stages I–IV periodontitis provided evidence-based recommendations for treating periodontitis patients, defined according to the 2018 classification. Peri-implant diseases were also re-defined in the 2018 classification. It is well established that both peri-implant mucositis and peri-implantitis are highly prevalent. In addition, peri-implantitis is particularly challenging to manage and is accompanied by significant morbidity. Aim: To develop an S3 level CPG for the prevention and treatment of peri-implant diseases, focusing on the implementation of interdisciplinary approaches required to prevent the development of peri-implant diseases or their recurrence, and to treat/rehabilitate patients with dental implants following the development of peri-implant diseases. Materials and Methods: This S3 level CPG was developed by the European Federation of Periodontology, following methodological guidance from the Association of Scientific Medical Societies in Germany and the Grading of Recommendations Assessment, Development and Evaluation process. A rigorous and transparent process included synthesis of relevant research in 13 specifically commissioned systematic reviews, evaluation of the quality and strength of evidence, formulation of specific recommendations, and a structured consensus process involving leading experts and a broad base of stakeholders. Results: The S3 level CPG for the prevention and treatment of peri-implant diseases culminated in the recommendation for implementation of various different interventions before, during and after implant placement/loading. Prevention of peri-implant diseases should commence when dental implants are planned, surgically placed and prosthetically loaded. Once the implants are loaded and in function, a supportive peri-implant care programme should be structured, including periodical assessment of peri-implant tissue health. If peri-implant mucositis or peri-implantitis are detected, appropriate treatments for their management must be rendered. Conclusion: The present S3 level CPG informs clinical practice, health systems, policymakers and, indirectly, the public on the available and most effective modalities to maintain healthy peri-implant tissues, and to manage peri-implant diseases, according to the available evidence at the time of publication

Wearable based monitoring and self-supervised contrastive learning detect clinical complications during treatment of Hematologic malignancies

Abstract Serious clinical complications (SCC; CTCAE grade ≥ 3) occur frequently in patients treated for hematological malignancies. Early diagnosis and treatment of SCC are essential to improve outcomes. Here we report a deep learning model-derived SCC-Score to detect and predict SCC from time-series data recorded continuously by a medical wearable. In this single-arm, single-center, observational cohort study, vital signs and physical activity were recorded with a wearable for 31,234 h in 79 patients (54 Inpatient Cohort (IC)/25 Outpatient Cohort (OC)). Hours with normal physical functioning without evidence of SCC (regular hours) were presented to a deep neural network that was trained by a self-supervised contrastive learning objective to extract features from the time series that are typical in regular periods. The model was used to calculate a SCC-Score that measures the dissimilarity to regular features. Detection and prediction performance of the SCC-Score was compared to clinical documentation of SCC (AUROC ± SD). In total 124 clinically documented SCC occurred in the IC, 16 in the OC. Detection of SCC was achieved in the IC with a sensitivity of 79.7% and specificity of 87.9%, with AUROC of 0.91 ± 0.01 (OC sensitivity 77.4%, specificity 81.8%, AUROC 0.87 ± 0.02). Prediction of infectious SCC was possible up to 2 days before clinical diagnosis (AUROC 0.90 at −24 h and 0.88 at −48 h). We provide proof of principle for the detection and prediction of SCC in patients treated for hematological malignancies using wearable data and a deep learning model. As a consequence, remote patient monitoring may enable pre-emptive complication management

Feasibility of Wearable-Based Remote Monitoring in Patients During Intensive Treatment for Aggressive Hematologic Malignancies

PURPOSE Intensive treatment protocols for aggressive hematologic malignancies harbor a high risk of serious clinical complications, such as infections. Current techniques of monitoring vital signs to detect such complications are cumbersome and often fail to diagnose them early. Continuousmonitoring of vital signs and physical activity bymeans of an upper arm medical wearable allowing 24/7 streaming of such parameters may be a promising alternative. METHODS This single-arm, single-center observational trial evaluated symptom-related patient-reported outcomes and feasibility of a wearable-based remote patient monitoring. All wearable data were reviewed retrospectively and were not available to the patient or clinical staff. A total of 79 patients (54 inpatients and 25 outpatients) participated and received standard-of-care treatment for a hematologic malignancy. In addition, the wearable was continuously worn and self-managed by the patient to record multiple parameters such as heart rate, oxygen saturation, and physical activity. RESULTS Fifty-one patients (94.4%) in the inpatient cohort and 16 (64.0%) in the outpatient cohort reported gastrointestinal symptoms (diarrhea, nausea, and emesis), pain, dyspnea, or shivering in at least one visit. With the wearable, vital signs and physical activity were recorded for a total of 1,304.8 days. Recordings accounted for 78.0% (63.0-88.5; median [interquartile range]) of the potential recording time for the inpatient cohort and 84.6% (76.3-90.2) for the outpatient cohort. Adherence to the wearable was comparable in both cohorts, but decreased moderately over time during the trial. CONCLUSION A high adherence to the wearable was observed in patients on intensive treatment protocols for a hematologic malignancy who experience high symptom burden. Remote patient monitoring of vital signs and physical activity was demonstrated to be feasible and of primarily sufficient quality. (C) 2022 by American Society of Clinical Oncolog