Prediction of loss to follow-up in long-term supportive periodontal therapy in patients with chronic periodontitis

Abstract Background Clinical evidence indicates that there are various risk factors of tooth loss. However, the degree of this risk among other risk factors remains unclear. In this retrospective cohort study, the authors evaluated the hazard ratios of several risk factors for tooth loss. Methods Included patients had all been treated for dental disorders, were in the supportive phase of periodontal therapy by dental hygienists, and visited a Japanese dental office continually during a 10-year period. Periodontal parameters, tooth condition, and general status of all teeth (excluding third molars) at the initial visit and at least 10 years later were evaluated by using multiple classification analysis. Results The authors evaluated a total of 7584 teeth in 297 patients (average age: 45.3, mean follow-up time: 13.9 years) Non-vital pulp was the most significant predictor of tooth loss according to Cox hazards regression analysis (hazard ratio: 3.31). The 10-year survival rate was approximately 90% for teeth with non-vital pulp and 99% for teeth with vital pulp. Fracture was the most common reason for tooth loss. Conclusions Non-vital pulp had the most significant association with tooth loss among the parameters. Therefore, it is very important to minimize dental pulp extirpation.

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How to Find Patients Who are 'Lost to Follow-up'

Bulletin of The Royal College of Surgeons of England ◽

10.1308/147363510x487795 ◽

2010 ◽

Vol 92 (3) ◽

pp. 98-101 ◽

Cited By ~ 5

Author(s):

LC Biant ◽

VK Eswaramoorthy ◽

RE Field

Keyword(s):

Surgical Interventions ◽

Loss To Follow Up ◽

Medical Interventions ◽

Follow Up Studies ◽

Long Term Follow Up ◽

Lost To Follow Up

Long-term surveillance of patients is necessary to ascertain the outcome of medical interventions. The rate of 'loss to follow-up' is the largest controllable variable in long-term follow-up studies. Such surveillance programmes are of particular importance to surgical interventions as differences between techniques or implants may take years to become apparent.

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Digital adherence technologies for the management of tuberculosis therapy: mapping the landscape and research priorities

BMJ Global Health ◽

10.1136/bmjgh-2018-001018 ◽

2018 ◽

Vol 3 (5) ◽

pp. e001018 ◽

Cited By ~ 51

Author(s):

Ramnath Subbaraman ◽

Laura de Mondesert ◽

Angella Musiimenta ◽

Madhukar Pai ◽

Kenneth H Mayer ◽

...

Keyword(s):

Treatment Outcomes ◽

Healthcare Providers ◽

Research Priorities ◽

Directly Observed Therapy ◽

Loss To Follow Up ◽

Individualised Care ◽

Health System Efficiency ◽

Tuberculosis Therapy

Poor medication adherence may increase rates of loss to follow-up, disease relapse and drug resistance for individuals with active tuberculosis (TB). While TB programmes have historically used directly observed therapy (DOT) to address adherence, concerns have been raised about the patient burden, ethical limitations, effectiveness in improving treatment outcomes and long-term feasibility of DOT for health systems. Digital adherence technologies (DATs)—which include feature phone–based and smartphone-based technologies, digital pillboxes and ingestible sensors—may facilitate more patient-centric approaches for monitoring adherence, though available data are limited. Depending on the specific technology, DATs may help to remind patients to take their medications, facilitate digital observation of pill-taking, compile dosing histories and triage patients based on their level of adherence, which can facilitate provision of individualised care by TB programmes to patients with varied levels of risk. Research is needed to understand whether DATs are acceptable to patients and healthcare providers, accurate for measuring adherence, effective in improving treatment outcomes and impactful in improving health system efficiency. In this article, we describe the landscape of DATs that are being used in research or clinical practice by TB programmes and highlight priorities for research.

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