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An advanced prediction model for postoperative complications and early implant failure.

ABSTRACT: OBJECTIVES:Risk prediction in implant dentistry presents specific challenges including the dependence of observations from patients with multiple implants and rare outcome events. The aim of this study was to use advanced statistical methods based on penalized regression to assess risk factors in implant dentistry. MATERIAL AND METHODS:We conducted a retrospective study from January 2016 to November 2018 recording postoperative complications including bleeding, hematoma, local infection, and nerve damage, as well as early implant failure. We further assessed patient- and implant-related risk factors including smoking and diabetes, as well as treatment parameters including types of gaps and surgical procedures. Univariable and multivariable generalized estimating equation (GEE) models were estimated to assess predictor effects, and a prediction model was fitted using L1 penalized estimation (lasso). RESULTS:In a total of 1,132 patients (mean age: 50.6 ± 16.5 years, 55.4% female) and 2,413 implants, postoperative complications occurred in 71 patients. Sixteen implants were lost prior to loading. Multivariable GEE models showed a higher risk of any complication for diabetes mellitus (p = .006) and bone augmentation (p = .039). The models further revealed a higher risk of local infection for bone augmentation (p = .003), and a higher risk of hematoma formation for diabetes mellitus (p = .007) and edentulous jaws (p = .024). The lasso model did not select any risk factors into the prediction model. CONCLUSIONS:Using novel methodology well-suited to tackle the specific challenges of risk prediction in implant dentistry, we were able to reliably estimate associations of risk factors with outcomes.

SUBMITTER: Feher B

PROVIDER: S-EPMC7589383 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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An advanced prediction model for postoperative complications and early implant failure.

Feher Balazs B Lettner Stefan S Heinze Georg G Karg Florian F Ulm Christian C Gruber Reinhard R Kuchler Ulrike U

Clinical oral implants research 20200731 10

<h4>Objectives</h4>Risk prediction in implant dentistry presents specific challenges including the dependence of observations from patients with multiple implants and rare outcome events. The aim of this study was to use advanced statistical methods based on penalized regression to assess risk factors in implant dentistry.<h4>Material and methods</h4>We conducted a retrospective study from January 2016 to November 2018 recording postoperative complications including bleeding, hematoma, local inf ...[more]

PMID: 32683718

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Project description:PurposeAlthough elective surgery is generally safe, some procedures remain associated with an increased risk of complications. Improved preoperative risk stratification and earlier recognition of these complications may ameliorate postoperative recovery and improve long-term outcomes. The perioperative longitudinal study of complications and long-term outcomes (PLUTO) cohort aims to establish a comprehensive biorepository that will facilitate research in this field. In this profile paper, we will discuss its design rationale and opportunities for future studies.ParticipantsPatients undergoing elective intermediate to high-risk non-cardiac surgery are eligible for enrolment. For the first seven postoperative days, participants are subjected to daily bedside visits by dedicated observers, who adjudicate clinical events and perform non-invasive physiological measurements (including handheld spirometry and single-channel electroencephalography). Blood samples and microbiome specimens are collected at preselected time points. Primary study outcomes are the postoperative occurrence of nosocomial infections, major adverse cardiac events, pulmonary complications, acute kidney injury and delirium/acute encephalopathy. Secondary outcomes include mortality and quality of life, as well as the long-term occurrence of psychopathology, cognitive dysfunction and chronic pain.Findings to dateEnrolment of the first participant occurred early 2020. During the inception phase of the project (first 2 years), 431 patients were eligible of whom 297 patients consented to participate (69%). Observed event rate was 42% overall, with the most frequent complication being infection.Future plansThe main purpose of the PLUTO biorepository is to provide a framework for research in the field of perioperative medicine and anaesthesiology, by storing high-quality clinical data and biomaterials for future studies. In addition, PLUTO aims to establish a logistical platform for conducting embedded clinical trials.Trial registration numberNCT05331118.

Project description:IntroductionYentl syndrome describing sex-related disparities has been extensively studied in medical conditions but not after surgery. This retrospective cohort study assessed the association of sex, frailty, presenting with preoperative acute serious conditions (PASC), and the expanded Operative Stress Score (OSS) with postoperative complications, mortality, and failure-to-rescue.MethodsThe National Surgical Quality Improvement Program from 2015 to 2019 evaluating 30-d complications, mortality, and failure-to-rescue.ResultsOf 4,860,308 cases (43% were male; mean [standard deviation] age of 56 [17] y), 6.0 and 0.8% were frail and very frail, respectively. Frailty score distribution was higher in men versus women (P < 0.001). Most cases were low-stress OSS2 (44.9%) or moderate-stress OSS3 (44.5%) surgeries. While unadjusted 30-d mortality rates were higher (P < 0.001) in males (1.1%) versus females (0.8%), males had lower odds of mortality (adjusted odds ratio (aOR) = 0.92, 95% confidence interval [CI] = 0.90-0.94, P < 0.001) after adjusting for frailty, OSS, case status, PASC, and Clavien-Dindo IV (CDIV) complications. Males have higher odds of PASC (aOR = 1.33, CI = 1.31-1.35, P < 0.001) and CDIV complications (aOR = 1.13, CI = 1.12-1.15, P < 0.001). Male-PASC (aOR = 0.76, CI = 0.72-0.80, P < 0.001) and male-CDIV (aOR = 0.87, CI = 0.83-0.91, P < 0.001) interaction terms demonstrated that the increased odds of mortality associated with PASC or CDIV complications/failure-to-rescue were lower in males versus females.ConclusionsOur study provides a comprehensive analysis of sex-related surgical outcomes across a wide range of procedures and health care systems. Females presenting with PASC or experiencing CDIV complications had higher odds of mortality/failure to rescue suggesting sex-related care differences. Yentl syndrome may be present in surgical patients; possibly related to differences in presenting symptoms, patient care preferences, or less aggressive care in female patients and deserves further study.

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An advanced prediction model for postoperative complications and early implant failure.

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An advanced prediction model for postoperative complications and early implant failure.

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