New Thermoelectric Materials Based on Solid Solutions of Compounds Tl2Тe–PbTe–Bi2Тe3 System

Проведено дослідження характеру фізико-хімічної взаємодії на квазібінарних перерізах системи Tl2Тe−PbTe–Bi2Тe3, підібрано раціональні склади, технологічні умови й одержано зразки тернарних телуридів і твердих розчинів на їх основі, для яких вивчено фізико-хімічні та термоелектричні властивості. The physico-chemical interaction on the quasibinary sections of Tl2Тe–PbTe–Bi2Тe3 system have been investigated, the materials of ternary telluride’s and solid solutions on which based were growth, some physico-chemical and thermoelectric properties were establishe

Біомаркери в діагностиці хвороб пародонта

The chronic course of periodontitis and gingivitis affects up to 80 % of the adult population, making them one of the most common diseases of mankind. The disease is initiated by the accumulation of bacteria along the gingival margin and in the space between the gingival tissue and the teeth. The absence of an acute pain clinic for periodontal diseases is one of the main reasons for the low level of patients seeking dental care. Diagnosis of periodontal disease, as a rule, is carried out by a dentist, it includes a visual examination of the gum tissue and a number of other protocol procedures, including additional diagnostic methods – a clinical assessment of the roentgenogram. At the same time, conventional clinical and radiographic methods for periodontal diagnostics are capable of only a retrospective diagnosis, they cannot detect or predict the activity of periodontitis. For these reasons, in recent years, potential biomarkers for the diagnosis of periodontal tissue diseases have been actively investigated. The source of biomarkers, in the first place, are considered gingival fluid and saliva, such as those that are in direct contact with the affected tissues. Given the foregoing, it seems appropriate to review the literature on biomarkers of gingival fluid and saliva used to diagnose periodontal diseases and the possibility of developing easy-to-use test methods for their early diagnosis. The aim of the study – to evaluate the prospects of using biomarkers in dental practice, in particular in the diagnosis of parathon tissue pathology, including peri-implant pathology, based on the analysis of literature data. Materials and Methods. The study used biblical and analytical methods. Results and Discussion. The sources of scientific and medical information on the application of biomarkers in the diagnosis of periodontal diseases are analyzed and processed. Conclusions. Despite the fact that the diagnostic value of oral fluids is recognized and there is a significant number of potential biomarkers, the studies conducted to date have proved inadequate to provide clinically reliable and useful information for practitioners in terms of more accurate diagnosis and treatment planning.Хроническое течение пародонтита и гингивита поражает до 80 % взрослого населения, ставши одной из самых распространенных болезней человечества. Заболевания инициируется накоплением бактерий вдоль десневого края и в пространстве между десневыми тканями и зубами. Отсутствие клиники острой боли при заболеваниях пародонта является одной из основных причин низкого уровня обращений пациентов за стоматологической помощью. Диагностику заболеваний пародонта, как правило, проводит врач-стоматолог. Она включает визуальный осмотр тканей десен и ряд других протокольных процедур, в том числе дополнительных методов диагностики – клиническую оценку рентенограммы. В то же время, обычные клинические и рентгенографические методы диагностики пародонта способны лишь к ретроспективному диагнозу, они не могут обнаружить или предсказать активность пародонтита. Поэтому в последние годы активно исследуются потенциальные биомаркеры для диагностики болезней тканей пародонта. Источником биомаркеров в первую очередь является десневая жидкость и слюна, как такие, которые непосредственно контактируют с пораженными тканями. Учитывая сказанное, целесообразно проанализировать литературные данные по биомаркерам десневой жидкости и слюны, которые используют для диагностики болезней пародонта и возможности разработать простые в применении тест-методы для ранней диагностики. Цель исследования – проанализировать литературные данные по оценке перспективы применения биомаркеров в стоматологической практике, в частности в диагностике патологии тканей пародонта вместе с периимплантной патологией. Материалы и методы. В исследовании применены библиосематический и аналитический методы. Результаты исследований и их обсуждение. В статье проанализированы и обработаны источники научно-медицинской информации, касающиеся применения биомаркеров в диагностике болезней пародонта. Выводы. Несмотря на то, что в диагностике ротовой жидкости имеется значительное количество потенциальных биомаркеров, проведенные на сегодняшний день исследования оказались недостаточными для предоставления клинически достоверной и полезной информации для практиков с точки зрения более точной диагностики и планирования лечения.Хронічний перебіг пародонтиту та гінгівіту вражає до 80 % дорослого населення, стаючи одним із найпоширеніших серед хвороб людства. Захворювання ініціюється накопиченням бактерій вздовж ясенного краю і в просторі між ясенними тканинами та зубами. Відсутність клініки гострого болю при захворюваннях пародонта є однією з основних причин низького рівня звернень пацієнтів за стоматологічною допомогою. Діагностику захворювань пародонта, як правило, проводить лікар-стоматолог. Вона включає візуальний огляд тканин ясен та ряд інших протокольних процедур, у тому числі додоткових методів діагностики – клінічну оцінку рентенограми. Водночас, звичайні клінічні та рентгенографічні методи діагностики пародонта здатні лише до ретроспективного діагнозу, вони не можуть виявити або передбачити активність пародонтиту. Тому в останні роки активно досліджують потенційні біомаркери для діагностування хвороб тканин пародонта. Джерелом біомаркерів перш за все є ясенна рідина та слина, як такі, що безпосередньо контактують з ураженими тканинами. Враховуючи сказане, доцільно проаналізувати літературні дані щодо біомаркерів ясенної рідини та слини, які використовують для діагностики хвороб пародонта та можливості розробити прості у застосуванні тест-методи для ранньої діагностики. Мета дослідження – проаналізувати літературні дані щодо оцінки перспективи застосування біомаркерів у стоматологічній практиці, зокрема в діагностиці патології тканин парадонта разом із періімплантною патологією. Матеріали і методи. У дослідженні застосовано бібліосематичний та аналітичний методи. Результати досліджень та їх обговорення. У статті проаналізовано та опрацьовано джерела науково-медичної інформації, що стосуються застосування біомаркерів у діагностиці хвороб пародонта. Висновки. Незважаючи на те, що в діагностиці рогової рідини наявна значна кількість потенційних біомаркерів, проведені на сьогодні дослідження виявилися недостатніми щодо надання клінічно достовірної та корисної інформації для практиків з точки зору більш точної діагностики та планування лікування

Ventilation and outcomes following robotic-assisted abdominal surgery: an international, multicentre observational study

Background: International data on the epidemiology, ventilation practice, and outcomes in patients undergoing abdominal robotic-assisted surgery (RAS) are lacking. The aim of the study was to assess the incidence of postoperative pulmonary complications (PPCs), and to describe ventilator management after abdominal RAS. Methods: This was an international, multicentre, prospective study in 34 centres in nine countries. Patients ≥18 yr of age undergoing abdominal RAS were enrolled between April 2017 and March 2019. The Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) score was used to stratify for higher risk of PPCs (≥26). The primary outcome was the incidence of PPCs. Secondary endpoints included the preoperative risk for PPCs and ventilator management. Results: Of 1167 subjects screened, 905 abdominal RAS patients were included. Overall, 590 (65.2%) patients were at increased risk for PPCs. Meanwhile, 172 (19%) patients sustained PPCs, which occurred more frequently in 132 (22.4%) patients at increased risk, compared with 40 (12.7%) patients at lower risk of PPCs (absolute risk difference: 12.2% [95% confidence intervals (CI), 6.8–17.6%]; P<0.001). Plateau and driving pressures were higher in patients at increased risk, compared with patients at low risk of PPCs, but no ventilatory variables were independently associated with increased occurrence of PPCs. Development of PPCs was associated with a longer hospital stay. Conclusions: One in five patients developed one or more PPCs (chiefly unplanned oxygen requirement), which was associated with a longer hospital stay. No ventilatory variables were independently associated with PPCs. Clinical trial registration: NCT02989415

Reliability of Identifying Diagnostic Error and Delay in Critically Ill Patients

Learning Objectives: Autopsy studies have attributed 10-20% of deaths to diagnostic error. Diagnostic error and delay contribute to avoidable illness. The process of reporting errors and near misses, however, remains under developed and lacks a standardized measurement tool. The aim of this study was to develop a reliable, reproducible standard operating procedure (SOP) for data abstraction, using available information in the electronic medical record that identifies diagnostic errors and delays in adult nontrauma patients at risk for critical illness. Methods: This was a retrospective observational study at Mayo Clinic Rochester reviewing a convenience sample of adult nontrauma patients admitted to the hospital in the year 2012 who had a rapid response team (RRT) call during their hospitalization. A standard operating procedure was developed to review electronic medical records using a taxonomy based assessment of diagnostic error and delay that identified areas of where in the diagnostic process the error or delay occurred and what that error or delay was. Diagnostic errors were further classified using a modified Goldman classification. Two critical care fellows independently reviewed all patients in the sample. Senior Critical Care clinicians further arbitrated disagreement among the reviewers. Inter-rater reliability was assessed with kappa agreement statistics. Results: A total of 1300 patients had a RRT call in 2012 of which our convenience sample was 130 patients (10%). Following independent review by critical fellows and arbitration of the disagreements, diagnostic error was identified in 10% and diagnostic delay in 17%. When assessing diagnostic error or delay, Kappa Coefficient was 0.57 (95 % CI 0.40-0.74) and observed agreement was 87% (95% CI 0.80-0.91) between the reviewers. The calculated Kappa Coefficient for diagnostic error was 0.48 (95% CI, 0.22-0.74) and observed agreement 91.5% (95% CI 0.84-0.95). For diagnostic delay, the calculated Kappa Coefficient was 0.61 (95% CI, 0.43-0.78) and observed agreement 88.5 % (95% CI 0.81-0.92). Conclusions: In this study, we have developed a standard operating procedure that identifies with moderate reliability, diagnostic error and delay in adult non-trauma critically ill patients

Reliability of identifying diagnostic error and delay in critically ill patients

Learning Objectives: Autopsy studies have attributed 10-20% of deaths to diagnostic error. Diagnostic error and delay contribute to avoidable illness. The process of reporting errors and near misses, however, remains under developed and lacks a standardized measurement tool. The aim of this study was to develop a reliable, reproducible standard operating procedure (SOP) for data abstraction, using available information in the electronic medical record that identifies diagnostic errors and delays in adult nontrauma patients at risk for critical illness. Methods: This was a retrospective observational study at Mayo Clinic Rochester reviewing a convenience sample of adult nontrauma patients admitted to the hospital in the year 2012 who had a rapid response team (RRT) call during their hospitalization. A standard operating procedure was developed to review electronic medical records using a taxonomy based assessment of diagnostic error and delay that identified areas of where in the diagnostic process the error or delay occurred and what that error or delay was. Diagnostic errors were further classified using a modified Goldman classification. Two critical care fellows independently reviewed all patients in the sample. Senior Critical Care clinicians further arbitrated disagreement among the reviewers. Inter-rater reliability was assessed with kappa agreement statistics. Results: A total of 1300 patients had a RRT call in 2012 of which our convenience sample was 130 patients (10%). Following independent review by critical fellows and arbitration of the disagreements, diagnostic error was identified in 10% and diagnostic delay in 17%. When assessing diagnostic error or delay, Kappa Coefficient was 0.57 (95 % CI 0.40-0.74) and observed agreement was 87% (95% CI 0.80-0.91) between the reviewers. The calculated Kappa Coefficient for diagnostic error was 0.48 (95% CI, 0.22-0.74) and observed agreement 91.5% (95% CI 0.84-0.95). For diagnostic delay, the calculated Kappa Coefficient was 0.61 (95% CI, 0.43-0.78) and observed agreement 88.5 % (95% CI 0.81-0.92). Conclusions: In this study, we have developed a standard operating procedure that identifies with moderate reliability, diagnostic error and delay in adult non-trauma critically ill patients

Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness

Objective: To reliably improve diagnostic fidelity and identify delays using a standardized approach applied to the electronic medical records of patients with emerging critical illness. Patients and Methods: This retrospective observational study at Mayo Clinic, Rochester, Minnesota, conducted June 1, 2016, to June 30, 2017, used a standard operating procedure applied to electronic medical records to identify variations in diagnostic fidelity and/or delay in adult patients with a rapid response team evaluation, at risk for critical illness. Multivariate logistic regression analysis identified predictors and compared outcomes for those with and without varying diagnostic fidelity and/or delay. Results: The sample included 130 patients. Median age was 65 years (interquartile range, 56-76 years), and 47.0% (52 of 130) were women. Clinically significant diagnostic error or delay was agreed in 23 (17.7%) patients (κ=0.57; 95% CI, 0.40-0.74). Median age was 65.4 years (interquartile range, 60.3-74.8) and 9 of the 23 (30.1%) were female. Of those with diagnostic error or delay, 60.9% (14 of 23) died in the hospital compared with 19.6% (21 of 107) without; P\u3c.001. Diagnostic error or delay was associated with higher Charlson comorbidity index score, cardiac arrest triage score, and do not intubate/do not resuscitate status. Adjusting for age, do not intubate/do not resuscitate status, and Charlson comorbidity index score, diagnostic error or delay was associated with increased mortality; odds ratio, 5.7; 95% CI, 2.0-17.8. Conclusion: Diagnostic errors or delays can be reliably identified and are associated with higher comorbidity burden and increased mortality

Predictors and Outcome of Diagnostic Error in Patients at Risk for Critical Illness

Introduction: Diagnostic error and delay are recognized factors that contribute to avoidable illness. The goal of this study was to validate a previously developed standard operating procedure (SOP) used to identify diagnostic error and delay, identify predictors and assess outcomes in adult patients at risk for critical illness. Methods: This was a retrospective observational study at Mayo Clinic Rochester reviewing a convenience sample of adult patients admitted to the hospital in the year 2012 who had a rapid response team (RRT) call during their hospitalization. A previously developed standard operating procedure reliably identified diagnostic error or delay in a convenience sample. In this study we validated our findings by identifying predictors and assessing outcomes of mortality and hospital length of stay in those with and without diagnostic error or delay through multivariate logistic regression analysis. Results: Our convenience sample included 130 patients that were selected for detailed review. Diagnostic error or delay was present in 23 patients. Hospital mortality for this group was 60%, compared to 19% in the group without diagnostic error or delay (p\u3c0.001). Diagnostic error or delay was associated with a higher comorbidity burden, with a Charlson comorbidity index of 5 (IQR 2-7) vs 2 (IQR 0-5), p=0.018. When adjusted for baseline differences, diagnostic error or delay was associated with a markedly increased chance of dying, OR 5.7 (95 % CI 1.98 - 17.82). Conclusion: Diagnostic error and delay occurs more often in patients with chronic comorbidities. Furthermore, diagnostic error and delay is independently associated with increased mortality