Is It “Aging” or Immunosenescence? The COVID-19 Biopsychosocial Risk Factors Aggravating Immunosenescence as Another Risk Factor of the Morbus. A Developmental-clinical Social Work Perspective

SummaryThe retrospective observational study surveys the relationship between development of inhibitors in the treatment of haemophilia patients and risk factors such as changing FVIII products. A total of 119 patients were included in this study, 198 changes of FVIII products were evaluated. Results: During the observation period of 12 months none of the patients developed an inhibitor, which was temporally associated with a change of FVIII products. A frequent change of FVIII products didn’t lead to an increase in inhibitor risk. The change between plasmatic and recombinant preparations could not be confirmed as a risk factor. Furthermore, no correlation between treatment regimens, severity, patient age and comorbidities of the patients could be found.

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Risk Factors of Collateralized Loan Obligations and Corporate Bonds

Zeitschrift für Bankrecht und Bankwirtschaft ◽

10.15375/zbb-2020-0604 ◽

2020 ◽

Vol 32 (6) ◽

pp. 347-355

Author(s):

Mark Wahrenburg ◽

Andreas Barth ◽

Mohammad Izadi ◽

Anas Rahhal

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Asset Pricing ◽

Systemic Risk ◽

Corporate Bonds ◽

Risk Exposure ◽

Expected Returns ◽

Yield Spreads ◽

Pricing Factors ◽

Return Difference

AbstractStructured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.

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Motivation For Therapeutic Interventions In Clinical Social Work In Kuwait

10.34120/0080-044-003-007 ◽

2016 ◽

pp. 9

Author(s):

هند المعصب

Keyword(s):

Social Work ◽

Clinical Social Work ◽

Therapeutic Interventions

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Cardiovascular Risk in Perimenopausal Women

Current Vascular Pharmacology ◽

10.2174/1570161116666181002145340 ◽

2019 ◽

Vol 17 (6) ◽

pp. 591-594 ◽

Cited By ~ 6

Author(s):

John C. Stevenson ◽

Sophia Tsiligiannis ◽

Nick Panay

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Ovarian Function ◽

Density Lipoprotein ◽

Premenopausal Women ◽

Therapeutic Interventions ◽

Additional Risk Factor ◽

Chd Risk ◽

Perimenopausal Women ◽

Chd Risk Factors

Cardiovascular disease, and particularly coronary heart disease (CHD), has a low incidence in premenopausal women. Loss of ovarian hormones during the perimenopause and menopause leads to a sharp increase in incidence. Although most CHD risk factors are common to both men and women, the menopause is a unique additional risk factor for women. Sex steroids have profound effects on many CHD risk factors. Their loss leads to adverse changes in lipids and lipoproteins, with increases being seen in low density lipoprotein (LDL) cholesterol and triglycerides, and decreases in high density lipoprotein (HDL) cholesterol. There is a reduction in insulin secretion and elimination, but increases in insulin resistance eventually result in increasing circulating insulin levels. There are changes in body fat distribution with accumulation in central and visceral fat which links to the other adverse metabolic changes. There is an increase in the incidence of hypertension and of type 2 diabetes mellitus, both major risk factors for CHD. Oestrogens have potent effects on blood vessels and their loss leads to dysfunction of the vascular endothelium. All of these changes result from loss of ovarian function contributing to the increased development of CHD. Risk factor assessment in perimenopausal women is recommended, thereby permitting the timely introduction of lifestyle, hormonal and therapeutic interventions to modify or reverse these adverse changes.

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Surviving “Risk Factor Frenzy”: The Perils of Incorrectly Applying Epidemiological Research in Health Education and Promotion

International Quarterly of Community Health Education ◽

10.2190/drcm-3pcg-90at-nr2l ◽

2002 ◽

Vol 21 (1) ◽

pp. 83-100 ◽

Cited By ~ 1

Author(s):

Jonathan I. Robison ◽

Gregory Kline

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Health Education ◽

Health Professionals ◽

Lifestyle Change ◽

Negative Consequences ◽

Epidemiological Research ◽

Health Practitioners ◽

Health Education And Promotion

In health education and promotion, “risk factors” for disease gathered from epidemiological research form the basis from which the majority of recommendations to individuals for lifestyle change are made. Unfortunately, many health practitioners are unaware that this type of research was never intended to be applied to individuals. The result is ongoing public confusion and anxiety concerning health recommendations and a loss of credibility for health professionals. This article: 1) briefly reviews the most commonly encountered limitations inherent in epidemiological research; 2) explores the problems and potential negative consequences of incorrectly applying epidemiological research in health education and promotion; and 3) makes recommendations to help health practitioners more skillfully interpret and incorporate into their work findings from epidemiological research.

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Knowledge, awareness and perceptions of diabetes mellitus among the Saudi population

Journal of Comparative Effectiveness Research ◽

10.2217/cer-2019-0137 ◽

2020 ◽

Vol 9 (6) ◽

pp. 413-422

Author(s):

Muhammad H Mujammami ◽

Abdulaziz A Alodhayani ◽

Mohammad Ibrahim AlJabri ◽

Ahmad Alhumaidi Alanazi ◽

Sultan Sayyaf Alanazi ◽

...

Keyword(s):

Diabetes Mellitus ◽

Risk Factors ◽

Social Media ◽

Risk Factor ◽

Healthcare Workers ◽

Health Workers ◽

Saudi Population ◽

Limited Data ◽

High Prevalence ◽

Associated Risk Factors

Background: High prevalence of undiagnosed cases of diabetes mellitus (DM) has increased over the last two decades, most patients with DM only become aware of their condition once they develop a complication. Limited data are available regarding the knowledge and awareness about DM and the associated risk factors, complications and management in Saudi society. Aim: This study aimed to assess knowledge of DM in general Saudi society and among Saudi healthcare workers. Results: Only 37.3% of the participants were aware of the current DM prevalence. Obesity was the most frequently identified risk factor for DM. Most comparisons indicated better awareness among health workers. Conclusion: A significant lack of knowledge about DM in Saudi society was identified. Social media and educational curriculum can improve knowledge and awareness of DM.

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A-126 Clinical Utility of Risk Factors to Predict Self-reported Neurobehavioral Outcome Following Traumatic Brain Injury: PTSD, Sleep, Resilience, and Lifetime Blast Exposure

Archives of Clinical Neuropsychology ◽

10.1093/arclin/acaa068.126 ◽

2020 ◽

Vol 35 (6) ◽

pp. 919-919

Author(s):

Lange R ◽

Lippa S ◽

Hungerford L ◽

Bailie J ◽

French L ◽

...

Keyword(s):

Risk Factors ◽

Traumatic Brain Injury ◽

Risk Factor ◽

Brain Injury ◽

Clinical Utility ◽

Poor Sleep ◽

Post Injury ◽

Poor Outcome ◽

Blast Exposure ◽

Neurobehavioral Outcome

Abstract Objective To examine the clinical utility of PTSD, Sleep, Resilience, and Lifetime Blast Exposure as ‘Risk Factors’ for predicting poor neurobehavioral outcome following traumatic brain injury (TBI). Methods Participants were 993 service members/veterans evaluated following an uncomplicated mild TBI (MTBI), moderate–severe TBI (ModSevTBI), or injury without TBI (Injured Controls; IC); divided into three cohorts: (1) < 12 months post-injury, n = 237 [107 MTBI, 71 ModSevTBI, 59 IC]; (2) 3-years post-injury, n = 370 [162 MTBI, 80 ModSevTBI, 128 IC]; and (3) 10-years post-injury, n = 386 [182 MTBI, 85 ModSevTBI, 119 IC]. Participants completed a 2-hour neurobehavioral test battery. Odds Ratios (OR) were calculated to determine whether the ‘Risk Factors’ could predict ‘Poor Outcome’ in each cohort separately. Sixteen Risk Factors were examined using all possible combinations of the four risk factor variables. Poor Outcome was defined as three or more low scores (< 1SD) on five TBI-QOL scales (e.g., Fatigue, Depression). Results In all cohorts, the vast majority of risk factor combinations resulted in ORs that were ‘clinically meaningful’ (ORs > 3.00; range = 3.15 to 32.63, all p’s < .001). Risk factor combinations with the highest ORs in each cohort were PTSD (Cohort 1 & 2, ORs = 17.76 and 25.31), PTSD+Sleep (Cohort 1 & 2, ORs = 18.44 and 21.18), PTSD+Sleep+Resilience (Cohort 1, 2, & 3, ORs = 13.56, 14.04, and 20.08), Resilience (Cohort 3, OR = 32.63), and PTSD+Resilience (Cohort 3, OR = 24.74). Conclusions Singularly, or in combination, PTSD, Poor Sleep, and Low Resilience were strong predictors of poor outcome following TBI of all severities and injury without TBI. These variables may be valuable risk factors for targeted early interventions following injury.

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Proposal for the use of echocardiography in bloodstream infections due to different streptococcal species

BMC Infectious Diseases ◽

10.1186/s12879-021-06391-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Sandra Chamat-Hedemand ◽

Niels Eske Bruun ◽

Lauge Østergaard ◽

Magnus Arpi ◽

Emil Fosbøl ◽

...

Keyword(s):

Risk Factors ◽

Risk Factor ◽

High Risk ◽

Blood Culture ◽

Positive Blood Culture ◽

Bloodstream Infections ◽

Low Risk ◽

Moderate Risk ◽

Streptococcal Species ◽

Very High

Abstract Background Infective endocarditis (IE) is diagnosed in 7–8% of streptococcal bloodstream infections (BSIs), yet it is unclear when to perform transthoracic (TTE) and transoesophageal echocardiography (TOE) according to different streptococcal species. The aim of this sub-study was to propose a flowchart for the use of echocardiography in streptococcal BSIs. Methods In a population-based setup, we investigated all patients admitted with streptococcal BSIs and crosslinked data with nationwide registries to identify comorbidities and concomitant hospitalization with IE. Streptococcal species were divided in four groups based on the crude risk of being diagnosed with IE (low-risk < 3%, moderate-risk 3–10%, high-risk 10–30% and very high-risk > 30%). Based on number of positive blood culture (BC) bottles and IE risk factors (prosthetic valve, previous IE, native valve disease, and cardiac device), we further stratified cases according to probability of concomitant IE diagnosis to create a flowchart suggesting TTE plus TOE (IE > 10%), TTE (IE 3–10%), or “wait & see” (IE < 3%). Results We included 6393 cases with streptococcal BSIs (mean age 68.1 years [SD 16.2], 52.8% men). BSIs with low-risk streptococci (S. pneumoniae, S. pyogenes, S. intermedius) are not initially recommended echocardiography, unless they have ≥3 positive BC bottles and an IE risk factor. Moderate-risk streptococci (S. agalactiae, S. anginosus, S. constellatus, S. dysgalactiae, S. salivarius, S. thermophilus) are guided to “wait & see” strategy if they neither have a risk factor nor ≥3 positive BC bottles, while a TTE is recommended if they have either ≥3 positive BC bottles or a risk factor. Further, a TTE and TOE are recommended if they present with both. High-risk streptococci (S. mitis/oralis, S. parasanguinis, G. adiacens) are directed to a TTE if they neither have a risk factor nor ≥3 positive BC bottles, but to TTE and TOE if they have either ≥3 positive BC bottles or a risk factor. Very high-risk streptococci (S. gordonii, S. gallolyticus, S. mutans, S. sanguinis) are guided directly to TTE and TOE due to a high baseline IE prevalence. Conclusion In addition to the clinical picture, this flowchart based on streptococcal species, number of positive blood culture bottles, and risk factors, can help guide the use of echocardiography in streptococcal bloodstream infections. Since echocardiography results are not available the findings should be confirmed prospectively with the use of systematic echocardiography.

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Prevalence and prognostic impact of left ventricular systolic dysfunction after acute myocardial infarction

European Heart Journal ◽

10.1093/ehjci/ehaa946.1796 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

T.J Jernberg ◽

E.O Omerovic ◽

E.H Hamilton ◽

K.L Lindmark ◽

L.D Desta ◽

...

Keyword(s):

Diabetes Mellitus ◽

Risk Factors ◽

Myocardial Infarction ◽

Atrial Fibrillation ◽

Risk Factor ◽

Reperfusion Therapy ◽

Left Ventricular ◽

Funding Source ◽

Additional Risk Factor ◽

Additional Risk

Abstract Background Left ventricular dysfunction after an acute myocardial infarction (MI) is associated with poor outcome. The PARADISE-MI trial is examining whether an angiotensin receptor-neprilysin inhibitor reduces the risk of cardiovascular death or worsening heart failure (HF) in this population. The aim of this study was to examine the prevalence and prognosis of different subsets of post-MI patients in a real-world setting. Additionally, the prognostic importance of some common risk factors used as risk enrichment criteria in the PARADISE-MI trial were specifically examined. Methods In a nationwide myocardial infarction registry (SWEDEHEART), including 87 177 patients with type 1 MI between 2011–2018, 3 subsets of patients were identified in the overall MI cohort (where patients with previous HF were excluded); population 1 (n=27 568 (32%)) with signs of acute HF or an ejection fraction (EF) <50%, population 2 (n=13 038 (15%)) with signs of acute HF or an EF <40%, and population 3 (PARADISE-MI like) (n=11 175 (13%)) with signs of acute HF or an EF <40% and at least one risk factor (Age ≥70, eGFR <60, diabetes mellitus, prior MI, atrial fibrillation, EF <30%, Killip III-IV and STEMI without reperfusion therapy). Results When all MIs, population 1 (HF or EF <50%), 2 (HF or EF <40%) and 3 (HF or EF <40% + additional risk factor (PARADISE-MI like)) were compared, the median (IQR) age increased from 70 (61–79) to 77 (70–84). Also, the proportion of diabetes (22% to 33%), STEMI (38% to 50%), atrial fibrillation (10% to 24%) and Killip-class >2 (1% to 7%) increased. After 3 years of follow-up, the cumulative probability of death or readmission because of heart failure in the overall MI population and in population 1 to 3 was 17.4%, 26.9%, 37.6% and 41.8%, respectively. In population 2, all risk factors were independently associated with death or readmission because of HF (Age ≥70 (HR (95% CI): 1.80 (1.66–1.95)), eGFR <60 (1.62 (1.52–1.74)), diabetes mellitus (1.35 (1.26–1.44)), prior MI (1.16 (1.07–1.25)), atrial fibrillation (1.35 (1.26–1.45)), EF <30% (1.69 (1.58–1.81)), Killip III-IV (1.34 (1.19–1.51)) and STEMI without reperfusion therapy (1.34 (1.21–1.48))) in a multivariable Cox regression analysis. The risk increased with increasing number of risk factors (Figure 1). Conclusion Depending on definition, post MI HF is present in 13–32% of all MI patients and is associated with a high risk of subsequent death or readmission because of HF. The risk increases significantly with every additional risk factor. There is a need to optimize management and improve outcomes for this high risk population. Figure 1 Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Novartis

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