982-P: Use of Antihyperglycemic Agents (AHA) with Cardioprotective Benefit in Older Patients with T2D and CVD or CV Risk Factors

Background: Daptomycin-induced eosinophilic pneumonia (DEP) is a rare but severe adverse effect and the risk factors are unknown. The aim of this study was to determine risk factors for DEP. Methods: A retrospective cohort study was performed at the Bone and Joint Infection Unit of the Hospital Universitari Bellvitge (January 2014–December 2018). To identify risk factors for DEP, cases were divided into two groups: those who developed DEP and those without DEP. Results: Among the whole cohort (n = 229) we identified 11 DEP cases (4.8%) and this percentage almost doubled in the subgroup of patients ≥70 years (8.1%). The risk factors for DEP were age ≥70 years (HR 10.19, 95%CI 1.28–80.93), therapy >14 days (7.71, 1.98–30.09) and total cumulative dose of daptomycin ≥10 g (5.30, 1.14–24.66). Conclusions: Clinicians should monitor cumulative daptomycin dosage to minimize DEP risk, and be cautious particularly in older patients when the total dose of daptomycin exceeds 10 g.

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30-Day Potentially Preventable Hospital Readmissions In Older Patients: Clinical Phenotype And Health Care Related Risk Factors

Clinical Interventions in Aging ◽

10.2147/cia.s208572 ◽

2019 ◽

Vol Volume 14 ◽

pp. 1851-1858

Author(s):

Valeria Calsolaro ◽

Rachele Antognoli ◽

Giuseppe Pasqualetti ◽

Chukwuma Okoye ◽

Ferruccio Aquilini ◽

...

Keyword(s):

Risk Factors ◽

Health Care ◽

Older Patients ◽

Clinical Phenotype ◽

Hospital Readmissions ◽

Related Risk

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Characteristics, outcomes, and risk factors of ICANS after axicabtagene ciloleucel: Does age matter?

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e19556 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e19556-e19556

Author(s):

Kitsada Wudhikarn ◽

Radhika Bansal ◽

Arushi Khurana ◽

Matthew Hathcock ◽

Michael Ruff ◽

...

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Older Patients ◽

Clinical Course ◽

International Prognostic Index ◽

Age Groups ◽

Central Nervous System Involvement ◽

Microvascular Disease ◽

B Cell Lymphoma ◽

Younger Patients

e19556 Background: CD19 chimeric antigen receptor T cell therapy possesses unique side effects including cytokine release syndrome (CRS) and immune effector cell associated neurotoxicity syndrome (ICANS). Age is a major risk factor for ICANS. However, whether ICANS in older patients is different compared to younger patients is unknown. Herein, we report clinical course, outcomes and risk factors for ICANS in older patients with large B cell lymphoma (LBCL) treated with axicabtagene ciloleucel (axi-cel). Methods: We comprehensively reviewed detailed clinical courses of ICANS in 78 adult patients with LBCL treated with axi-cel between June 2016 and October 2020. Incidence, manifestation, risk factors, treatment, and outcomes of ICANS were compared between patients age ≥60 (n=32) and <60 (n=46) years old. Results: Baseline characteristics were comparable between older and younger patients except higher proportion of high international prognostic index and underlying cerebral microvascular disease in older patients. ICANS was observed in 16 patients in the older and 24 patients in the younger age group, with a 30-day incidence of 52% and 50%, respectively. Median time to CRS and ICANS were similar between 2 age groups. The most common initial neurological findings included aphasia, dysgraphia and encephalopathy in both age groups. Table summarizes the characteristics, clinical course and interventions of ICANS in older and younger patients. In Cox regression model, the presence of CRS was the only factor associated with ICANS in both age groups. Age, history of central nervous system involvement and cerebral microvascular disease were not associated with ICANS. Importantly, all patients had complete resolution of ICANS. No elderly patients in our cohort experienced seizure as a manifestation of ICANS. Conclusions: In our study, older age was not a risk factor for ICANS. CRS was the only factor associated with ICANS in both younger and older patients. Incidence, clinical course and neurological outcomes of ICANS in older patients treated with axi-cel were comparable to younger patients. [Table: see text]

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Risk factors for poor outcome in older patients admitted in a surgical intensive care unit

Nursing in Critical Care ◽

10.1111/nicc.12686 ◽

2021 ◽

Author(s):

Emilie Occhiali ◽

Pierre Prolange ◽

Florence Cassiau ◽

Frédéric Roca ◽

Benoit Veber ◽

...

Keyword(s):

Risk Factors ◽

Intensive Care Unit ◽

Intensive Care ◽

Older Patients ◽

Surgical Intensive Care Unit ◽

Surgical Intensive Care ◽

Poor Outcome

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What are the Risk Factors for One-Year Mortality in Older Patients with Chronic Kidney Disease? An Analysis of the Cleveland Clinic CKD Registry

Nephron ◽

10.1159/000494298 ◽

2018 ◽

Vol 141 (2) ◽

pp. 98-104 ◽

Cited By ~ 4

Author(s):

Fahad Saeed ◽

Susana Arrigain ◽

Jesse D. Schold ◽

Joseph V. Nally Jr ◽

Sankar Dass Navaneethan

Keyword(s):

Risk Factors ◽

Chronic Kidney Disease ◽

Kidney Disease ◽

Older Patients ◽

Cleveland Clinic ◽

One Year

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Endothelial reactivity and cardiac risk factors in older patients with peripheral arterial disease

The American Journal of Cardiology ◽

10.1016/s0002-9149(98)00984-9 ◽

1999 ◽

Vol 83 (5) ◽

pp. 754-758 ◽

Cited By ~ 67

Author(s):

Alberto Rafael Yataco ◽

Mary Concepta Corretti ◽

Andrew William Gardner ◽

Christopher Joseph Womack ◽

Leslie Ira Katzel

Keyword(s):

Risk Factors ◽

Peripheral Arterial Disease ◽

Older Patients ◽

Arterial Disease ◽

Cardiac Risk ◽

Cardiac Risk Factors ◽

Peripheral Arterial

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Ischemic stroke with a preceding Trans ischemic attack(TIA) less than 24 hours: Predicting clinical risk factors for thrombolytic therapy

10.21203/rs.2.17137/v1 ◽

2019 ◽

Author(s):

Nicolas Poupore ◽

Dan Strat ◽

Tristan Mackey ◽

Ashley Snell ◽

Thomas Nathaniel

Keyword(s):

Risk Factors ◽

Ischemic Stroke ◽

Thrombolytic Therapy ◽

Older Patients ◽

Clinical Risk Factors ◽

Receiver Operating Curve ◽

Stroke Patients ◽

Clinical Risk ◽

Stroke Population ◽

Clinical Risks

Abstract Background Acute ischemic stroke attack with and without a recent TIA within or less than 24 hours may differ in clinical risk factors, and this may affect treatment outcomes following thrombolytic therapy. We examined whether the odds of exclusion or inclusion for thrombolytic therapy are greater in ischemic stroke with TIA less than 24 hours preceding ischemic stroke(TIA-24hr-ischemic stroke patients) as compared to those without recent TIA or non-TIA <24 hours.Methods A retrospective hospital-based analysis was conducted on 6,315 ischemic stroke patients, of whom 846 had proven brain diffusion-weighted magnetic resonance imaging (DW-MRI) of an antecedent TIA within 24 hours prior to ischemic stroke. The logistic regression model was developed to generate odds ratios (OR) to determine clinical factors that may increase the likelihood of exclusion or inclusion for thrombolytic therapy. The validity of the model was tested using a Hosmer-Lemeshow test, while the Receiver Operating Curve (ROC) was used to test the sensitivity of our model.Results In TIA-24hr-ischemic stroke population, patients with a history of alcohol abuse (OR = 5.525, 95% CI, 1.003-30.434, p = 0.05), migraine (OR=4.277, 95% CI, 1.095-16.703, p=0.037), and increasing NIHSS score (OR=1.156, 95% CI, 1.058-1.263, p = 0.001) were associated with the increasing odds of receiving rtPA, while older patients (OR = 0.965, 95% CI, 0.934‐0.997, P = 0.033) were associated with the increasing odds of not receiving rtPA.Conclusion In TIA-24hr-ischemic stroke patients, older patients with higher INR values are associated with increasing odds of exclusion from thrombolytic therapy. Our findings demonstrate clinical risks factors that can be targeted to improve the use and eligibility for rtPA in in TIA-24hr-ischemic stroke patients.

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Clinical Characteristics, Risk Factors and Predictive Value of COVID-19 Pneumonia: A Retrospective Study of 173 Patients in Wuhan, China

10.21203/rs.3.rs-76134/v1 ◽

2020 ◽

Author(s):

Yang Zhang ◽

Jun Xue ◽

Mi Yan ◽

Jing Chen ◽

Hai Liu ◽

...

Keyword(s):

Risk Factors ◽

Predictive Model ◽

Disease Severity ◽

Roc Curve ◽

Predictive Value ◽

Older Patients ◽

Clinical Characteristics ◽

Lactic Dehydrogenase ◽

Older Age ◽

Hospital Outcome

Abstract Background: COVID-19 is a globally emerging infectious disease. As the global epidemic continues to spread, the risk of COVID-19 transmission and diffusion in the world will also remain. Currently, several studies describing its clinical characteristics have focused on the initial outbreak, but rarely to the later stage. Here we described clinical characteristics, risk factors for disease severity and in-hospital outcome in patients with COVID-19 pneumonia from Wuhan. Methods: Patients with COVID-19 pneumonia admitted to Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from February 13 to March 8, 2020, were retrospectively enrolled. Multivariable logistic regression analysis was used to identify risk factors for disease severity and in-hospital outcome and establish predictive models. Receiver operating characteristic (ROC) curve was used to assess the predictive value of above models.Results: 106 (61.3%) of the patients were female. The mean age of study populations was 62.0 years, of whom 73 (42.2%) had underlying comorbidities mainly including hypertension (24.9%). The most common symptoms on admission were fever (67.6%) and cough (60.1%), digestive symptoms (22.0%) was also very common. Older age (OR: 3.420; 95%Cl: 1.415-8.266; P=0.006), diarrhea (OR: 0.143; 95%Cl: 0.033-0.611; P=0.009) and lymphopenia (OR: 4.769; 95%Cl: 2.019-11.266; P=0.000) were associated with severe illness on admission; the area under the ROC curve (AUC) of predictive model were 0.860 (95%CI: 0.802-0.918; P=0.000). Older age (OR: 0.309; 95%Cl: 0.142-0.674; P=0.003), leucopenia (OR: 0.165; 95%Cl: 0.034-0.793; P=0.025), increased lactic dehydrogenase (OR: 0.257; 95%Cl: 0.100-0.659; P=0.005) and interleukins-6 levels (OR: 0.294; 95%Cl: 0.099-0.872; P=0.027) were associated with poor in-hospital outcome; AUC of predictive model were 0.752 (95%CI: 0.681-0.824; P=0.000).Conclusion: Older patients with diarrhea and lymphopenia need early identification and timely intervention to prevent the progression to severe COVID-19 pneumonia. However, older patients with leucopenia, increased lactic dehydrogenase and interleukins-6 levels are at a high risk for poor in-hospital outcome.Trial registration: ChiCTR2000029549

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Vaping and subsequent comorbidities potentially associated with increased mortality and more severe illness in COVID-19: a narrative review

10.22514/sv.2021.113 ◽

2021 ◽

Keyword(s):

Risk Factors ◽

Cigarette Smoking ◽

Health Risks ◽

Older Patients ◽

Significant Risk ◽

Self Report ◽

Severe Illness ◽

Protective Effects ◽

Cigarette Use

Introduction: COVID-19 (or COVID) is a highly virulent viral disease which more frequently presents severe infection in specific populations, such as the elderly, patients with hypertension, patients with respiratory disease, and patients who smoke. The effects vaping (i.e., an electronic cigarette or JUUL device) has on COVID progression remains unclear, because there is an information paucity correlating e-cigarette use and COVID. This review sought to identify links between vape use and COVID severity via literature review. Additionally, because there is more widespread information about cigarette smoking than about vaping, this review sought to illustrate commonalities between smoking and vaping. If smoking and vaping are deemed near-identical practices, then it is possible the effects of smoking on human health and on COVID disease could be comparable in vaping. Methods: Several searches were performed on PubMed with MeSH headings and JSTOR between 17 December 2020 and 22 December 2020. Search results were excluded if they were not trials or controlled clinical trials, if the articles were not about COVID, if the articles were about smoking behaviors or habits, or if the articles were not related to vaping or smoking. Key findings were summarized and tabled based on relevance, substantiability, and applicability to COVID. Results: Multiple sources viewed smoking and vaping as equal risk factors for COVID disease, whereas other sources viewed the two as unique risk factors. Because of this controversy, it is challenging to view the two practices as similar enough to pose equivalent risks for COVID. Both practices pose significant health risks to its users, but these health risks are unique to each practice. Discussion: There are several limitations which exacerbate ambiguity—(1) it is unclear how harmful smoking is for COVID patients, because several publications found smoking may have protective effects; (2) few older patients vape, but yet most severe COVID cases occur in older populations; (3) older patients and impoverished patients show a statistically significant risk for severe COVID disease independent of other factors; (4) vaping is a relatively new practice, and there are few patients who self-report long-term e-cigarette use or long-term adverse effects as a result thereof. Conclusion: Although vaping may present serious health risks, clinically, it is uncertain how significantly vaping affects COVID disease, especially when compared against cigarette smoking. More research is needed on both the effects of vaping on COVID and the likeness of vaping versus smoking.

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Advanced and metastatic renal cell carcinoma – Ain Shams Clinical Oncology Department Experience

Journal of Solid Tumors ◽

10.5430/jst.v10n1p18 ◽

2020 ◽

Vol 10 (1) ◽

pp. 18

Author(s):

Ahmed Nagy ◽

Mona Kamal ◽

Hesham El Halawani

Keyword(s):

Risk Factors ◽

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Clinical Oncology ◽

Renal Cell ◽

Older Patients ◽

Treatment Options ◽

Tumor Grade ◽

Kaplan Meier ◽

Younger Age

Background: Renal cell carcinoma is a rare tumor and till recently few treatment options were available. It is poorly understood why people develop RCC since only a few etiologic factors have been clinically identified as risk factors for RCC.Purpose: To analyze our experience at Ain Shams University Clinical Oncology department in Egypt with patients presenting with advanced renal cell carcinoma to provide a correlations between clinic-pathological factors, treatment and survival outcomes.Methodology: Retrospective review of the data of 54 patients who were diagnosed as RCC and presented to Ain Shams University Clinical Oncology department in Egypt from 1 May 2013 till 1 May 2015. Descriptive and clinic-pathological data were described using simple and relative frequencies. Survival outcome for the patients will be described using Kaplan Meier curves stratified according to morphology, age group and treatment received.Results: The sample included 54 patients (53.7% were males) of whom 14.3% were less than 40 years and 3.7% were elderly (≥ 70 years old). The median age was 55.5 years (SD ± 13.6 , range 19-71). Median PFS was 6.5 months (SD ± 12.3846 Range 43) while the median OS was 13 months (SD ± 12.161 Range 46). PFS in patients aged below 55.5 years was 9 months (95% CI=6.509-11.491) compared to 4 months (95% CI=2.704-5.296) in older patients (p = .004). PFS in patients who achieved PR after sunitinb was 17 months (95% CI=6.916-27.084) compared to 5 months (95% CI=3.699-6.301) in patients who didn’t achieved PR (p < .001). OS in patients aged below 55.5 years was 15 months (95% CI=9.131-20.869) compared to 11 months (95% CI=8.947-13.053) in older patients (p = .012). Favorable pathology status was associated with prolonged OS of 14 months (95% CI= 9.403-18.597) versus 11 months (95% CI=8.363-13.637) for unfavourable pathology status (p = .11). Low grades histopathogy was associated with prolonged OS of 44 months (95% CI= 38.456-49.544) versus 12 months (95% CI=10.077-13.923) for higher grades (p = < .001).Conclusion: Multivariate analyses supported a conclusion that younger age was an independent prognostic factor for survival along with other known risk factors such as tumor grade and pathology status.

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