We examined how extra-hepatic comorbidity burden impacts mortality in patients with cirrhosis referred for liver transplantation (LT). Adults with cirrhosis evaluated for their first LT in 2012 were followed through their clinical course with last follow up in 2019. Extra-hepatic comorbidity burden was measured using the Charlson Comorbidity Index (CCI). The endpoints were 90-day transplant free survival (Cox-Proportional Hazard regression), and overall mortality (competing risk analysis). The study included 340 patients, mean age 56 ± 11, 63% male and MELD-Na 17.2 ± 6.6. The CCI was 0 (no comorbidities) in 44%, 1-2 in 44% and | 2 (highest decile) in 12%, with no differences based on gender but higher CCI in patients with fatty and cryptogenic liver disease. Thirty-three (10%) of 332 patients not receiving LT within 90 days died. Beyond MELD-Na, the CCI was independently associated with 90-day mortality (hazard ratio (HR), 1.32 (95% confidence interval (CI) 1.02-1.72). Ninety-day mortality was
OBJECTIVE: The influence of confounding neurocognitive comorbidities in people living with HIV (PLWH) on neuroimaging has not been systematically evaluated. We determined associations between comorbidity burden and brain integrity and examined the moderating effect of age on these relationships.DESIGN: Observational, cross-sectional substudy of the CNS HIV Antiretroviral Therapy Effects Research cohort.METHODS: A total of 288 PLWH (mean age = 44.2) underwent structural MRI and magnetic resonance spectroscopy as well as neurocognitive and neuromedical assessments. Consistent with Frascati criteria for HIV-associated neurocognitive disorders (HAND), neuromedical and neuropsychiatric comorbidity burden was classified as incidental (mild), contributing (moderate), or confounding (severe-exclusionary) to a diagnosis of HAND. Multiple regression modeling predicted neuroimaging outcomes as a function of comorbidity classification, age, and their interaction.RESULTS: Comorbidity classifications were 176 ...
Prognostic scores, and more specifically comorbidity scores, are important and widely used measures in the health care field and in health services research. A comorbidity is an existing disease an individual has in addition to a primary condition of interest, such as cancer. A comorbidity score is a summary score that can be created from these individual comorbidities for prognostic purposes, as well as for confounding adjustment. Despite their widespread use, the properties of and conditions under which comorbidity scores are valid dimension reduction tools in statistical models is largely unknown. This dissertation explores the use of summary comorbidity measures in statistical models. Three particular aspects are examined. First, it is shown that, under standard conditions, the predictive ability of these summary comorbidity measures remains as accurate as the individual comorbidities in regression models, which can include factors such as treatment variables and additional covariates. ...
This study evaluates the association between Internal Addiction (IA) and psychiatric co-morbidity in the literature. Meta-analyses were conducted on cross-sectional, case-control and cohort studies which examined the relationship between IA and psychiatric co-morbidity. Selected studies were extracted from major online databases. The inclusion criteria are as follows: 1) studies conducted on human subjects; 2) IA and psychiatric co-morbidity were assessed by standardised questionnaires; and 3) availability of adequate information to calculate the effect size. Random-effects models were used to calculate the aggregate prevalence and the pooled odds ratios (OR). Eight studies comprising 1641 patients suffering from IA and 11210 controls were included. Our analyses demonstrated a significant and positive association between IA and alcohol abuse (OR = 3.05, 95% CI = 2.14-4.37, z = 6.12, P | 0.001), attention deficit and hyperactivity (OR = 2.85, 95% CI = 2.15-3.77, z = 7.27, P | 0.001), depression (OR = 2
TY - JOUR. T1 - Autoimmune comorbidities are associated with brain injury in multiple sclerosis. AU - Zivadinov, R.. AU - Raj, B.. AU - Ramanathan, M.. AU - Teter, B.. AU - Durfee, J.. AU - Dwyer, M. G.. AU - Bergsland, N.. AU - Kolb, C.. AU - Hojnacki, D.. AU - Benedict, R. H.. AU - Weinstock-Guttman, B.. PY - 2016/6. Y1 - 2016/6. N2 - BACKGROUND AND PURPOSE: The effect of comorbidities on disease severity in MS has not been extensively characterized. We determined the association of comorbidities with MR imaging disease severity outcomes in MS. MATERIALS AND METHODS: Demographic and clinical history of 9 autoimmune comorbidities confirmed by retrospective chart review and quantitative MR imaging data were obtained in 815 patients with MS. The patients were categorized on the basis of the presence/ absence of total and specific comorbidities. We analyzed the MR imaging findings, adjusting for key covariates and correcting for multiple comparisons. RESULTS: Two hundred forty-one (29.6%) study ...
Health, ...Comorbidities are common among patients with chronic obstructive pulmo... We followed 1664 COPD patients recruited from five pulmonary clinic...The 12 comorbidities with the strongest association with an increased ... We used these 12 comorbidities to develop a new comorbidity risk inde...,Comorbidities,increase,risk,of,mortality,in,COPD,patients,medicine,medical news today,latest medical news,medical newsletters,current medical news,latest medicine news
Two studies observed that a high comorbidity level prior to surgery has a profound impact on short-term revision risk (study II). A novel finding of this thesis was that high comorbidity also affects the long-term revision risk (study II), which has been confirmed by several recent studies. Due to the increasing burden of a variety of comorbidities in THR patients, their association with revision risk and the underlying mechanisms merit further research. To offer some possible explanations for how comorbidity affects revision risk, this thesis focused in more detail on THR patients with diabetes, which has a high and increasing prevalence in both the general population and the THR population. Diabetes increased the risk of revision due to infection, particularly in patients with diabetes for less than 5 years prior to THR, those with complications due to diabetes, and those with cardiovascular comorbidities prior to surgery (study V). These findings were also confirmed recently. However, the ...
The Elixhauser Comorbidity Index was developed using a California-based population dataset of adult, non-maternal inpatients from 438 acute care hospitals in 1992 [32]. The dataset included 1,779,167 patients and 41 comorbidities were listed. No consensus method was employed for making a list of potential candidates for the comorbidity index. Outcomes were defined as length of stay, charges and in-hospital mortality. Statistically unrelated comorbidities to the outcomes were excluded after a series of univariable and multivariable analyses, leading to a final set of 30 comorbidities (Additional file 1: Appendix D) [32]. The authors did not employ item weighting in the phases of development. The Elixhauser Comorbidity Index was developed mainly for use with administrative data. The index has good face validity as well as content validity as the items are mutually exclusive. Feasibility of using the index was not examined in maternal or related research. In the context of maternal health research, ...
We explored multimorbidity patterns and their 6-year evolution in people aged 65 years and older with multimorbidity attended in PHC. The most prevalent chronic diseases, Hypertension, uncomplicated and Lipid disorder, were represented in all clusters in all four groups (i.e., men and women aged 65-79 and ≥80 years). We found 6 clusters per group, 5 of them with a specific pattern related to an organic system: Musculoskeletal, Endocrine-metabolic, Digestive/Digestive-respiratory, Neuropsychiatric and Cardiovascular patterns. We analysed multimorbidity patterns over 6 years and found that they remained quite similar from the beginning to the end of the study period.. We observed a high prevalence of multimorbidity in our population sample, with a higher proportion for women, as in other published studies [5, 8] and described 6 patterns in each study group. In addition, the prevalence of chronic diseases and multimorbidity patterns was similar to previous studies in Catalonia [22] and in other ...
Learn more about how common certain comorbidities are in people with rheumatoid arthritis and why RA patients need health care to address them.
Ranganath VK, Maranian P, Elashoff DA, Woodworth T, Khanna D, Hahn T, Sarkisian C, Kremer JM, Furst DE, Paulus HE. Comorbidities are associated with poorer outcomes in community patients with rheumatoid arthritis.. Rheumatology (Oxford). Oct 1, 2013; 52: 10: 1809-17: PubMed PMID23813577; PubMed Central PMCID: PMC3775293 ...
Objectives - Diabetes frequently coexists with other conditions, resulting in poorer diabetes self-management and quality of life, higher risk for diabetes-related complications and higher health service use compared to those with diabetes only. Few Canadian studies have undertaken a comprehensive, population-level analysis of comorbidity and health service utilization by older adults with diabetes. This study examined comorbidity and its association with a broad range of health services in a cohort of community-dwelling older adults with diabetes in Ontario, Canada.. Methods - We linked multiple administrative databases to create a cohort of 448,736 older adults with diabetes, described their comorbidities and obtained their 1-year use of health services (physician visits, emergency department visits, inpatient hospital admissions, home care use, nursing home admissions). We examined comorbidity patterns by age and gender and estimated the prevalence of 20 comorbid conditions and the most ...
The present study showed that the mean (SD) HL score in our multimorbid primary care patient sample was 2.9 (0.5). In multimorbid patients, a high treatment burden and effects on patients quality of life due to problems with mobility and anxiety/depression were negatively associated with HL. However, our study revealed no association between HL and age. Although several studies have assessed HL, to the best of our knowledge, little is known about which factors are associated with low HL in multimorbid patients in primary care.. The present studys main finding was that the treatment burden facing multimorbid primary care patients was negatively associated with HL. In other words, the lower a multimorbid patients HL, the higher the treatment burden. This is a very interesting finding, and although the β coefficient is small, we believe that this result is clinically relevant and allows us to identify treatment burden as an element to take into account for potentially low literacy in ...
We found significantly higher rates of somatic comorbidity among migrants with PTSD and depression compared with migrants without a diagnosed psychiatric disorder. Adjusted rates were significantly higher in ten out of the fifteen diagnostic categories being especially high for infectious, neurological and pulmonary diseases. Our results further suggest difference in the rates of somatic comorbidity according to region of origin and according to the legal ground of obtaining residency.. Prior to our study, somatic comorbidity in migrants with PTSD and depression have only received scarce attention in the literature [18-21]. Albeit, diagnosis and treatment of somatic comorbidity may help improve management of mental disorders and vice versa. Further, patients with PTSD and depression suffering from somatic comorbidity will require regular treatment and check-up, such as diabetes may need tailored treatment programmes to ensure they are treated according to need. It is therefore important that ...
Background: Patients with HIV infection can present with multiple comorbidities prior to and following the initiation of antiretroviral therapy (ART) including potential risk factors for cardiovascular disease (CVD) and renal impairment and osteoporosis/fracture. Understanding these risk factors can help identify patients at high risk and help optimize HIV treatment. Methods: Adults diagnosed with HIV (ICD-9-CM code: 042.xx, 795.71, V08) in 2002-2013 were selected from MarketScan Commercial, Medicare, and Medicaid databases, which are longitudinal, allowing patients to be observed over multiple years. All patients were continuously enrolled for at least 1 calendar year during 2003-2013. Age and gender entered on the date of the first HIV diagnosis. Comorbid conditions during calendar years 2003-2013 were assessed using diagnosis and procedure codes ...
From 2008 to 2010, there were 319,775 ILI inpatient cases, of which 8.82% entered ICU and 3.83% died at hospital discharge. The significant comorbidity attributes varied in each age stratum: heart failure in any age, non-dialyzed renal insufficiency in any age, cancer in school-age children up to mid-age adults, tuberculosis in the elderly, stroke in adults, congenital anomaly in children and adolescents, transplant in school-age up to adolescents, or HIV in young adults. Comorbidity vector was (heart failure, non-dialyzed renal insufficiency, cancer, tuberculosis, stroke, congenital anomaly, transplant, HIV). Age vector was (1, 1, 6<=age<45, 75<=age, 18<=age<65, 0<age<=18, 6<=age<18, 18<=age<45). Comorbidity score, the dot product of comorbidity vector and age vector, showed significant correlation with hospitalization cost (Spearman rho=0.1885, p<0.0001), and with LOS (Spearman rho=0.1717, p<0.0001). Its ROC area-under-curves (AUC) were 0.7454 with death and 0
The index program assigns two index scores to the inpatient records, one for readmissions and one for in-hospital mortality. The index program can be used to transform the current 29 HCUP comorbidities variables into comorbidity index scores for each record. The comorbidity index scores for each observation are calculated as a weighted sum of each of the binary comorbidity variables on the record. The resulting comorbidity index scores can be used in analyses in place of the 29 individual measures. This program assumes that the input data file includes 29 binary comorbidity variables with specific variables names. ...
Figure 1: 7MM, Diagnosed Prevalent Cases of Type 2 Diabetes with Comorbidity, 2016, Men and Women, Ages ≥20 Years. Source: GlobalData.. Type 2 diabetes (T2D) is a chronic disorder of glucose equilibrium that results from the bodys inability to make use of available insulin along with relative insulin deficiency. Among adults only, T2D is expected to make up at least 95% of all diabetes cases.. It is one of the most common non-communicable diseases and is an escalating public health problem globally, with an estimated 415 million people afflicted. Additionally, poorly managed diabetes leads to serious complications such as heart attack, stroke, kidney failure, leg amputation, vision loss, nerve damage, and other serious complications. Figure 1 presents the most common comorbidities in persons with T2D.. GlobalData Epidemiologists forecast that there were 56,060,328 diagnosed prevalent cases of T2D in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan). Additionally, ...
Multi-morbidity in chronic long-term conditions is a major concern for health services. Self-management in concert with clinical care forms part of the effective management of multi-morbidity. Self-efficacy is a mechanism through which self-management can be achieved. Quality of life is adversely impacted by multi-morbidity but could be improved by effective self-management. This study examines the relationship between self-efficacy and quality of life in primary care patients with multi-morbidity. A cross-sectional survey was conducted with primary care patients in England. Potential participants were mailed a questionnaire containing quality of life measures (the EQ-5D-5L and the Long-Term Conditions Questionnaire (LTCQ)), the Disease Burden Impact Scale (DBIS) and the Self-efficacy for Managing Chronic Disease Scale. Descriptive statistics, analysis of variance and linear regression analyses were conducted to examine the relationship between quality of life (dependent variable), self-efficacy, and
Background: While research in the area of e-mental health has received considerable attention over the last decade, there are still many areas that have not been addressed. One such area is the comorbidity of psychological disorders in a Web-based sample using online assessment and diagnostic tools, and the relationships between comorbidities and psychosocial variables. Objective: We aimed to identify comorbidities of psychological disorders of an online sample using an online diagnostic tool. Based on diagnoses made by an automated online assessment and diagnostic system administered to a large group of online participants, multiple comorbidities (co-occurrences) of 21 psychological disorders for males and females were identified. We examined the relationships between dyadic comorbidities of anxiety and depressive disorders and the psychosocial variables sex, age, suicidal ideation, social support, and quality of life. Methods: An online complex algorithm based on the criteria of the Diagnostic ...
This is a non-randomized open label dose-ranging study of Bendamustine and Rituximab (BR) in patients with previously untreated or relapsed/refractory CLL who have multiple comorbidities (Cumulative Illness Rating Scale [CIRS]≥7) with or without renal insufficiency (estimated creatinine clearance [CrCL] 15-40 mL/min, but not receiving dialysis).. The study will accrue two independent patient cohorts. Both cohorts will follow a standard 3+3 Phase I design. Once the maximum tolerated dose (MTD) is determined, two expansion cohorts will be enrolled. Dose limiting toxicities (DLT) will be assessed during the 1st cycle of treatment.. Patients with CLL who have significant comorbidities (CIRS≥7; at least one category grade 3-4), with or without minor renal dysfunction (CrCL,40 mL/min) will be accrued onto Cohort 1 of the study. At dose level 1, patients will receive bendamustine 45 mg/m2 in combination with rituximab (375 mg/m2 with cycle 1 and 500 mg/m2 with subsequent cycles). If safe, the dose ...
Computing comorbidity scores such as the weighted Charlson score (Charlson, 1987 ,doi:10.1016/0021-9681(87)90171-8,) and the Elixhauser comorbidity score (Elixhauser, 1998 ,doi:10.1097/00005650-199801000-00004,) using ICD-9-CM or ICD-10 codes (Quan, 2005 ,doi:10.1097/01.mlr.0000182534.19832.83,).. ...
Younger smokers are more likely to be dependent on nicotine and have psychiatric and substance use disorders than their older counterparts, new research shows ...
Despite the major public health impact of diabetes, recent population-based data regarding its prevalence and comorbidity are sparse. The prevalence and comorbidity of diabetes mellitus were analyzed in a nationally representative sample (N = 9133) of the non-institutionalized German adult population aged 50 years and older. Information on physician-diagnosed diabetes and 20 other chronic health conditions was collected as part of the national telephone health interview survey German Health Update (GEDA) 2009. Overall, 51.2% of contacted persons participated. Among persons with diabetes, diabetes severity was defined according to the type and number of diabetes-concordant conditions: no diabetes-concordant condition (grade 1); hypertension and/or hyperlipidemia only (grade 2); one comorbidity likely to represent diabetes-related micro- or macrovascular end-organ damage (grade 3); several such comorbidities (grade 4). Determinants of diabetes severity were analyzed by multivariable ordinal regression.
This is the first report of a projected series regarding the comorbidity of cardiovascular disease (CVD), diabetes and chronic kidney disease (CKD) in Australia. Comorbidity refers to any two or more of these diseases that occur in one person at the same time. The questions to be answered in this report include: 1. How many Australians have comorbidity of CVD, diabetes and CKD? 2. What is the proportion of hospitalisations with these comorbidities? 3. How much do these comorbidities contribute to deaths? 4. What is the magnitude of comorbidity in the context of each individual disease? 5. Are there differences in the distribution of these comorbidities among age groups and sexes ...
Dimensional diagnostic measures, such as those being proposed for use in DSM-5, reveal a more complex symptom profile for public-sector patients with serious mental illness than do categorical diagnoses, said William Narrow, M.D., M.P.H, associate director of APAs Division of Research, at a symposium at APAs Institute on Psychiatric Services last week in San Francisco. Narrow presented a study by the American Psychiatric Institute for Research and Education in which rates of categorical diagnoses and dimensional symptom ratings were examined for patients with schizophrenia, major depressive disorder, PTSD, and substance use disorders. ...
Comorbidities are additional chronic conditions that may compromise the health of people living with HIV. Some comorbid conditions are more common in people with HIV because they have similar risk factors or because the immune changes associated with HIV infection or the side effects of antiretroviral drugs increase a persons risk of developing them. These comorbidities are now the most common causes of death and disability in people living with HIV. Research on comorbidities aims to understand the underlying links between comorbidities and HIV, and to develop treatment strategies and guidelines to reduce their impact on the lives and well-being of people living with HIV.. ...
BACKGROUND: Pre-existing cardiovascular diseases (CVDs) have been proposed to identify patients at higher risk of adverse COVID-19 outcomes, but existing evidence is conflicting. Thus, it is unclear whether pre-existing CVDs are independently important predictors for severe COVID-19.. METHODS AND RESULTS: In a nationwide Danish cohort of hospital-screened COVID-19 patients aged , =40, we investigated if pre-existing CVDs predict the 30-day risk of (1) composite outcome of severe COVID-19 and (2) all-cause mortality. We estimated 30-day risks using a Cox regression model including age, sex, each CVD comorbidity, COPD-asthma, diabetes, and chronic kidney disease. To illustrate CVD comorbidities importance, we evaluated the predicted risks of death and severe infection, for each sex, along ages 40 - 85. 4,090 COVID-19 hospital-screened patients were observed as of August 26, 2020; 22.1% had ≥ 1 CVD, 23.7% had severe infection within 30 days and 12.6% died. Predicted risks of both outcomes at age ...
Особенности фармакотерапии коморбидных сердечно-сосудистых заболеваний у женщин с постменопаузальным остеопорозом
The object of this article was to systematically review available methods to measure comorbidity and to assess their validity and reliability. A search was made in Medline and Embase, with the keywords comorbidity and multi-morbidity, to identify articles in which a method to measure comorbidity was …
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BackgroundAtypical depression has been found to be distinct from other types of depression in terms of psychiatric symptom profile and treatment response. Howev
TY - JOUR. T1 - Underdiagnosing and overdiagnosing psychiatric comorbidities. T2 - Insights into common diagnostic oversights. AU - Basco, Monica Ramirez. AU - Jacquot, Colette. AU - Thomas, Christina. AU - Knack, Jennifer M.. PY - 2008/10/1. Y1 - 2008/10/1. N2 - There is no substitute for being thorough in conducting a diagnostic evaluation. This includes taking the time to gather information from the patient and significant others, going over prior medical records, and/or observing the patient over time and updating the diagnosis if appropriate. Keep in mind the importance of probing for comorbidities, of not jumping to conclusions about their presence when a patient presents with a few striking symptoms, and of the need to interpret symptoms correctly. Clinicians may be forced to draw quick diagnostic conclusions with limited information in busy practice settings or when patients are acutely ill. In these cases, it is important to follow up after patients have been stabilized, to reevaluate ...
Data was collected between 2006 and 2010 from adults 18 years of age or older in Boston who have a current diagnosis of alcohol dependence and heavy drinking and/or drug dependence and recent drug use.. Specifically, the following inclusion criteria were met at study entry: (1) Male and female subjects must be 18 years of age or older; (2) Must have a current diagnosis of Alcohol dependence and heavy drinking: Alcohol dependence as determined using the (10-items if none skipped) Composite International Diagnostic Interview Short Form (CIDI-SF) that yields a DSM-IV diagnosis and heavy drinking in the past 30 days, defined as greater than or equal to 4 standard drinks for women, greater than or equal to 5 for men at least twice in the past month, or greater than or equal to 22 drinks per week for men or greater than or equal to 15 drinks per week for women in an average week in the past month and/or Drug dependence and recent drug use: Drug dependence (DD) as determined by using the Composite ...
Accountable Care Organizations, which used to be the wave of the future, are the here and now. As groups of doctors, hospitals and other healthcare providers come together to coordinate care, it is essential they include behavioral health providers in the mix. According to a recent National Comorbidity Survey, 17 percent of the adult population had comorbid mental and medical conditions within a 12-month period. Patients with comorbidities require a comprehensive treatment plan to truly bend the cost curve. For…. ...
The OS benefit associated with standard treatment diminished in patients older than 80 with high comorbidity scores, but other age groups fared better.
The diagnosis of comorbidities, which refers to the coexistence of different acute and chronic diseases, is difficult due to the modern extreme specialisation of physicians. We envisage that a software dedicated to comorbidity diagnosis could result in an effective aid to the health practice. We have developed an R software comoR to compute novel estimators of the disease comorbidity associations. Starting from an initial diagnosis, genetic and clinical data of a patient the software identifies the risk of disease comorbidity. Then it provides a pipeline with different causal inference packages (e.g. pcalg, qtlnet etc) to predict the causal relationship of diseases. It also provides a pipeline with network regression and survival analysis tools (e.g. Net-Cox, rbsurv etc) to predict more accurate survival probability of patients. The input of this software is the initial diagnosis for a patient and the output provides evidences of disease comorbidity mapping. The functions of the comoR offer flexibility
The degree to which complications contaminated estimation of comorbidity depended both on the procedures studied and on the covariates selected. The unique structure of the algorithm for the Charlson comorbidity index led to complication diagnoses having only a minor effect on the comorbidity score …
Background: CVD, AH and DM are common comorbidities in COPD. Their association with the new GOLD 2011 classification has not been evaluated.. Objective:To evaluate the prevalence of CVD, AH and DM in patients admitted to the hospital for COPD exacerbation (AECOPD).. Methods:609 patients admitted for AECOPD were followed-up monthly for one year.. Results:Patients classification according to GOLD 2011 and the prevalence of CVD, AH and DM are shown in Table 1. Comorbid diseases were more common in more severe COPD. Patients without comorbidities had fewer AECOPD in 1 year compared to patients with 1, 2 and 3 comorbidities (0.4±0.5, 1.9±2.5, 3.6±3.3 and 4.6±3.5 respectively, p,0.001) as well as fewer hospitalizations for AECOPD (0.1±0.3, 0.7±1.6, 1.6±1.9 and 2.0±2.6, respectively, p,0.001). Patients in group B with comorbidities had more AECOPD and hospitalizations in 1 year compared to group C (p,0.001). The presence of comorbidities was an independent predictor of AECOPD and ...
Matrix factorization (MF) is an established paradigm for large-scale biological data analysis with tremendous potential in computational biology. Here, we challenge MF in depicting the molecular bases of epidemiologically described disease–disease (DD) relationships. As a use case, we focus on the inverse comorbidity association between Alzheimer’s disease (AD) and lung cancer (LC), described as a lower than expected probability of developing LC in AD patients. To this day, the molecular mechanisms underlying DD relationships remain poorly explained and their better characterization might offer unprecedented clinical opportunities. To this goal, we extend our previously designed MF-based framework for the molecular characterization of DD relationships. Considering AD–LC inverse comorbidity as a case study, we highlight multiple molecular mechanisms, among which we confirm the involvement of processes related to the immune system and mitochondrial metabolism. We then distinguish
Background There has been an increasing prevalence of both depression and chronic medical conditions globally but the relationship between depression and multi-morbidity is not well understood. The...
Mental health comorbidities are a predictor of readmission and revision after spine surgery, but few surgeons perform psychological screenings for prospective patients.
In this analysis we demonstrate that, despite strict inclusion and exclusion criteria for eligibility to enroll in a clinical trial, there are significant differences in baseline clinical characteristics among study sites according to enrollment volume. Such variations have been previously reported related to regional differences among participants. To our knowledge, this is the first report that shows significant differences in participants baseline clinical characteristics on the basis of the number of participants enrolled by any individual clinical trial site. These differences spanned demographic and clinical characteristics, comorbidity burden, and laboratory parameters. Participants from the trial sites that enrolled fewer individuals had worse health at baseline. The less prevalent dyspnea and rales coupled with lower blood pressure and worse renal function, and higher use of inotropes all suggest that participants enrolled at lower enrolling sites likely represent a proportion of ...
Comorbidity (say koh-mor-BID-uh-tee) means that a person has two or more diseases at the same time. These are usually long-term (chronic) diseases that need treatment for a lifetime.. Examples of comorbidities include having both high blood pressure and diabetes, or having high cholesterol, heart failure, and diabetes.. Comorbidities can change treatment options. One disease can make another disease worse, and the total effect of all the diseases may be more than each one on its own. ...
This quick-reference chart names the most common comorbid conditions that come with ADHD, plus symptoms, common treatments, and recommended resources for each.
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We are looking for a PhD student! The PhD fellow will be part of a team working on several projects focused on the immunopathology of tuberculosis and testing drugs and vaccine candidates in several animal models. The PhD student will focus his/her research on understanding how comorbidities are involved in the pathogenesis of tuberculosis while being…
In a recent study to help inform future interventions for patients who have both diabetes and other comorbid conditions, Dr. Elizabeth Magnan et al. examined how 62 chronic conditions individually related to achievement of diabetes care quality goals. The authors found that the 62 conditions varied in their relationships to diabetes care goal achievement, with congestive heart failure, obesity, mental health conditions, and substance use disorders relating to a lack of achievement in at least one measure. ...
Research Hospitalization Volume, DRGs, Quality Outcomes, Top Hospitals & Physicians for DRG 374: DIGESTIVE MALIGNANCY WITH MAJOR COMPLICATION OR COMORBIDITY (MCC)