Ability of preoperative falls to predict postsurgical outcomes in non-selected patients undergoing elective surgery at an academic medical centre: Protocol for a prospective cohort study

INTRODUCTION: Falls are increasingly recognised for their ability to herald impending health decline. Despite the likely susceptibility of postsurgical patients to falls, a detailed description of postoperative falls in an unselected surgical population has never been performed. One study suggests that preoperative falls may forecast postoperative complications. However, a larger study with non-selected surgical patients and patient-centred outcomes is needed to provide the generalisability and justification necessary to implement preoperative falls assessment into routine clinical practice. The aims of this study are therefore twofold. First, we aim to describe the main features of postoperative falls in a population of unselected surgical patients. Second, we aim to test the hypothesis that a history of falls in the 6 months prior to surgery predicts postoperative falls, poor quality of life, functional dependence, complications and readmission. METHODS AND ANALYSIS: To achieve these goals, we study adult patients who underwent elective surgery at our academic medical centre and were recruited to participate in a prospective, survey-based cohort study called Systematic Assessment and Targeted Improvement of Services Following Yearlong Surgical Outcomes Surveys (SATISFY-SOS) (NCT02032030). Patients who reported falling in the 6 months prior to surgery will be considered ‘exposed.’ The primary outcome of interest is postoperative falls within 30 days of surgery. Secondary outcomes include postoperative functional dependence, quality of life (both physical and mental), in-hospital complications and readmission. Regression models will permit controlling for important confounders. ETHICS AND DISSEMINATION: The home institution's Institutional Review Board approved this study (IRB ID number 201505035). The authors will publish the findings, regardless of the results

Preoperative falls predict postoperative falls, functional decline, and surgical complications

AbstractBackgroundFalls are common and linked to morbidity. Our objectives were to characterize postoperative falls, and determine whether preoperative falls independently predicted postoperative falls (primary outcome), functional dependence, quality of life, complications, and readmission.MethodsThis prospective cohort study included 7982 unselected patients undergoing elective surgery. Data were collected from the medical record, a baseline survey, and follow-up surveys approximately 30days and one year after surgery.ResultsFall rates (per 100 person-years) peaked at 175 (hospitalization), declined to 140 (30-day survey), and then to 97 (one-year survey). After controlling for confounders, a history of one, two, and ≥three preoperative falls predicted postoperative falls at 30days (adjusted odds ratios [aOR] 2.3, 3.6, 5.5) and one year (aOR 2.3, 3.4, 6.9). One, two, and ≥three falls predicted functional decline at 30days (aOR 1.2, 2.4, 2.4) and one year (aOR 1.3, 1.5, 3.2), along with in-hospital complications (aOR 1.2, 1.3, 2.0). Fall history predicted adverse outcomes better than commonly-used metrics, but did not predict quality of life deterioration or readmission.ConclusionsFalls are common after surgery, and preoperative falls herald postoperative falls and other adverse outcomes. A history of preoperative falls should be routinely ascertained

Associations of baseline use of biologic or targeted synthetic DMARDs with COVID-19 severity in rheumatoid arthritis : Results from the COVID-19 Global Rheumatology Alliance physician registry

Funding Information: Competing interests JAS is supported by the National Institute of Arthritis and Funding Information: Musculoskeletal and Skin Diseases (grant numbers K23 AR069688, R03 AR075886, L30 AR066953, P30 AR070253 and P30 AR072577), the Rheumatology Research Foundation (K Supplement Award and R Bridge Award), the Brigham Research Institute, and the R Bruce and Joan M Mickey Research Scholar Fund. JAS has received research support from Amgen and Bristol-Myers Squibb and performed consultancy for Bristol-Myers Squibb, Gilead, Inova, Janssen and Optum, unrelated to this work. ZSW reports grant support from Bristol-Myers Squibb and Principia/ Sanofi and performed consultancy for Viela Bio and MedPace, outside the submitted work. His work is supported by grants from the National Institutes of Health. MG is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K01 AR070585 and K24 AR074534; JY). KLH reports she has received speaker’s fees from AbbVie and grant income from BMS, UCB and Pfizer, all unrelated to this study. KLH is also supported by the NIHR Manchester Biomedical Research Centre. LC has not received fees or personal grants from any laboratory, but her institute works by contract for laboratories such as, among other institutions, AbbVie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, Novartis Farmaceutica, Pfizer, Roche Farma, Sanofi Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal and UCB Pharma. LG reports research grants from Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz and Sanofi; consulting fees from AbbVie, Amgen, BMS, Biogen, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi Aventis and UCB, all unrelated to this study. EFM reports that LPCDR received support for specific activities: grants from AbbVie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal, MSD, Celgene, Medac, Pharma Kern and GAfPA; grants and non-financial support from Pfizer; and non-financial support from Grünenthal, outside the submitted work. AS reports grants from a consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi Aventis and UCB) supporting the German RABBIT register, and personal fees from lectures for AbbVie, MSD, Roche, BMS and Pfizer, outside the submitted work. AD-G has no disclosures relevant to this study. His work is supported by grants from the Centers for Disease Control and Prevention and the Rheumatology Research Foundation. KMD is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258) and the Rheumatology Research Foundation. NJP is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258). PD has received research support from Bristol-Myers Squibb, Chugai and Pfizer, and performed consultancy for Boehringer Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche and Janssen, unrelated to this work. NS is supported by the RRF Investigator Award and the American Heart Association. MFU-G reports grant support from Janssen and Pfizer. SB reports no competing interests related to this work. He reports non-branded consulting fees for AbbVie, Horizon, Novartis and Pfizer (all <$10 000). RG reports no competing interests related to this work. Outside of this work she reports personal and/or speaking fees from AbbVie, Janssen, Novartis, Pfizer and Cornerstones, and travel assistance from Pfizer (all <$10 000). JH reports no competing interests related to this work. He is supported by grants from the Rheumatology Research Foundation and the Childhood Arthritis and Rheumatology Research Alliance. He has performed consulting for Novartis, Sobi and Biogen, all unrelated to this work (<$10 000). JL has received research funding from Pfizer, outside the submitted work. ES is a Board Member of the Canadian Arthritis Patient Alliance, a patient-run, volunteer-based organisation whose activities are largely supported by independent grants from pharmaceutical companies. PS reports no competing interests related to this work. He reports honorarium for doing social media for American College of Rheumatology journals (<$10 000). PMM has received consulting/speaker’s fees from AbbVie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all <$10 000). PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). PCR reports no competing interests related to this work. Outside of this work he reports personal consulting and/or speaking fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer and UCB, and travel assistance from Roche (all <$10 000). JY reports no competing interests related to this work. Her work is supported by grants from the National Institutes of Health, Centers for Disease Control, and the Agency for Healthcare Research and Quality. She has performed consulting for Eli Lilly and AstraZeneca, unrelated to this project. Publisher Copyright: © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.Objective To investigate baseline use of biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) and COVID-19 outcomes in rheumatoid arthritis (RA). Methods We analysed the COVID-19 Global Rheumatology Alliance physician registry (from 24 March 2020 to 12 April 2021). We investigated b/tsDMARD use for RA at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAKi), interleukin 6 inhibitors (IL-6i) or tumour necrosis factor inhibitors (TNFi, reference group). The ordinal COVID-19 severity outcome was (1) no hospitalisation, (2) hospitalisation without oxygen, (3) hospitalisation with oxygen/ventilation or (4) death. We used ordinal logistic regression to estimate the OR (odds of being one level higher on the ordinal outcome) for each drug class compared with TNFi, adjusting for potential baseline confounders. Results Of 2869 people with RA (mean age 56.7 years, 80.8% female) on b/tsDMARD at the onset of COVID-19, there were 237 on ABA, 364 on RTX, 317 on IL-6i, 563 on JAKi and 1388 on TNFi. Overall, 613 (21%) were hospitalised and 157 (5.5%) died. RTX (OR 4.15, 95% CI 3.16 to 5.44) and JAKi (OR 2.06, 95% CI 1.60 to 2.65) were each associated with worse COVID-19 severity compared with TNFi. There were no associations between ABA or IL6i and COVID-19 severity. Conclusions People with RA treated with RTX or JAKi had worse COVID-19 severity than those on TNFi. The strong association of RTX and JAKi use with poor COVID-19 outcomes highlights prioritisation of risk mitigation strategies for these people.publishersversionPeer reviewe

Assessing change in patient-reported quality of life after elective surgery: protocol for an observational comparison study [version 1; referees: 2 approved]

Despite their widespread use, the two main methods of assessing quality of life after surgery have never been directly compared. To support patient decision-making and study design, we aim to compare these two methods. The first of these methods is to assess quality of life before surgery and again after surgery using the same validated scale. The second is simply to ask patients whether or not they think their post-operative quality of life is better, worse, or the same. Our primary objective is to assess agreement between the two measures. Secondary objectives are to calculate the minimum clinically important difference (MCID) and to describe the variation across surgical specialties. To accomplish these aims, we will administer surveys to patients undergoing elective surgery, both before surgery and again 30 days after surgery. This protocol follows detailed guidelines for observational study protocols

Data from: Preoperative falls predict postoperative falls and other adverse patient-reported outcomes

BACKGROUND: Falls are common and linked to morbidity. Our objectives were to characterize postoperative falls, and determine whether preoperative falls independently predicted postoperative falls (primary outcome), functional dependence, quality of life, complications, and readmission. METHODS: This prospective cohort study included 7982 unselected patients undergoing elective surgery. Data were collected from the medical record, a baseline survey, and follow-up surveys approximately 30days and one year after surgery. RESULTS: Fall rates (per 100 person-years) peaked at 175 (hospitalization), declined to 140 (30-day survey), and then to 97 (one-year survey). After controlling for confounders, a history of one, two, and ≥three preoperative falls predicted postoperative falls at 30days (adjusted odds ratios [aOR] 2.3, 3.6, 5.5) and one year (aOR 2.3, 3.4, 6.9). One, two, and ≥three falls predicted functional decline at 30days (aOR 1.2, 2.4, 2.4) and one year (aOR 1.3, 1.5, 3.2), along with in-hospital complications (aOR 1.2, 1.3, 2.0). Fall history predicted adverse outcomes better than commonly-used metrics, but did not predict quality of life deterioration or readmission. CONCLUSIONS: Falls are common after surgery, and preoperative falls herald postoperative falls and other adverse outcomes. A history of preoperative falls should be routinely ascertained

Preoperative Falls and Their Association with Functional Dependence and Quality of Life

Light court, view looking up at adjoining apartment block; In 2002, Mariscal's multidisciplinary career culminated with the integral design of the Gran Hotel Domine Bilbao, nestling between the Guggenheim Museum in Bilbao and the ria, the creative concept of which is based on reflecting the history of design of the 20th century. Mariscal designed things from the uniforms to the façade, including the graphic image and its website. He did the interior design of the GHDB with Fernando Salas. Source: Wikipedia; http://en.wikipedia.org/wiki/Main_Page (accessed 7/16/2010

Preoperative Falls Predict Postoperative Falls, Functional Decline, and Surgical Complications

Background: Falls are common and linked to morbidity. Our objectives were to characterize postoperative falls, and determine whether preoperative falls independently predicted postoperative falls (primary outcome), functional dependence, quality of life, complications, and readmission. Methods: This prospective cohort study included 7982 unselected patients undergoing elective surgery. Data were collected from the medical record, a baseline survey, and follow-up surveys approximately 30 days and one year after surgery. Results: Fall rates (per 100 person-years) peaked at 175 (hospitalization), declined to 140 (30-day survey), and then to 97 (one-year survey). After controlling for confounders, a history of one, two, and ≥three preoperative falls predicted postoperative falls at 30 days (adjusted odds ratios [aOR] 2.3, 3.6, 5.5) and one year (aOR 2.3, 3.4, 6.9). One, two, and ≥three falls predicted functional decline at 30 days (aOR 1.2, 2.4, 2.4) and one year (aOR 1.3, 1.5, 3.2), along with in-hospital complications (aOR 1.2, 1.3, 2.0). Fall history predicted adverse outcomes better than commonly-used metrics, but did not predict quality of life deterioration or readmission. Conclusions: Falls are common after surgery, and preoperative falls herald postoperative falls and other adverse outcomes. A history of preoperative falls should be routinely ascertained