Predictors Of Quality Of Life Research Articles

A Systematic Review on Prognosis of Autism Using Machine Learning Techniques

Quality of life (QoL) and QoL predictors have become crucial in the pandemic. Neurological anomalies are at the highest level of QoL threats. Autism is a multi-system disorder that causes behavioural, neurological, cognitive, and physical differences. Recent studies state that neurological disorders can result in dysfunction of brain or whole nervous system, which may cause other symptoms of Autism. The paper focuses on reviewing various Machine Learning techniques used for diagnosing Autism at an early age with the help of multiple datasets. The study of brain Magnetic Resonance Imaging (MRI) provides astute knowledge of brain structure that helps to study any minor to significant changes inside the brain that have emerged due to the disorder. Early diagnosis leads to a healthy life by getting timely treatment and training. "Early diagnosis of Autism Spectrum Disorder" is an objective and one of the prime goals of health establishments worldwide. The research paper aims to systematically review and find which machine learning algorithms are efficient for prognosis of Autism.

Quality of life and experience with the national multiple sclerosis society strategic plan priorities for people with multiple sclerosis: Findings from a path analysis.

The National Multiple Sclerosis Society (NMSS) strives to ensure that people affected by multiple sclerosis (MS) can live their best lives. This mission is reflected in the Society's strategic plan, which establishes the roadmap for the Society's continued commitment to a world free of MS. The purpose of this article is to add to the understanding of both the scope and complexity of the impact of MS and MS-related supports on quality of life (QOL). A national sample of people with MS (n = 748) participated in the study by completing validated surveys assessing their QOL, physical and mental health, MS self-efficacy, resilience, participation in NMSS, perceived stress, emotional support, and social roles and activities. A path model was used to examine how the frequently identified MS QOL predictors, including demographic, MS, psychosocial, and physical functional status variables relate to each other and to QOL. The model exhibited reasonable model fit with hypothesized paths being statistically significant and in the hypothesized direction. Findings revealed that the relationships among mental health, demographic factors, overall MS experiences, QOL, NMSS participation, and resonance with the mission of the NMSS are complex, highly nuanced, and yet strongly correlated. More importantly, the study highlights the strong influence of variables that are more readily amenable to change through programmatic and clinical intervention, and active self-management and participation.

Predictors of Functional School Outcome in Children With Pediatric Acquired Brain Injury.

ObjectiveAmong the variety of domains that may be impacted after pediatric acquired brain injury (pABI) are functional school outcomes. The purpose of this study was to identify demographic, medical, and psychological factors associated with impairments in functional school outcomes, defined as school absence, need of educational and psychological services, quality of life (QoL) in the school setting, and academic performance in children with pABI, with a specific emphasis on the significance of fatigue.Materials and MethodWe used baseline data from a randomized controlled trial. The sample consisted of seventy-six children aged 10 to 17 (M = 13 yrs) with pABI in the chronic phase (>1 year). All completed assessments of school-related QoL, academic performance, global functioning, fatigue, IQ, behavioral problems, and executive function.ResultsFatigue, IQ, global functioning, behavioral problems, and sex emerged as potential predictors for functional school outcomes. Of note, overall fatigue emerged as the strongest potential predictor for parent-reported QoL in school (β = 0.548; p < 0.001) and self-reported QoL in school (β = 0.532; p < 0.001).ConclusionsFollowing pABI, specific psychological, medical, and demographic factors are associated with functional school outcomes. Neither of the injury-related variables age at insult and time since insult were associated with functional school outcomes. Overall, our findings may suggest that a reintroduction to school with personalized accommodations tailored to the child's specific function and symptoms, such as fatigue, is recommended.

Prediction of Quality of Life in Patients With Parkinson’s Disease With and Without Excessive Daytime Sleepiness: A Longitudinal Study

ObjectiveThere is a lack of longitudinal studies that directly compare the quality of life (QoL) and investigate the impact of clinical factors on QoL across different excessive daytime sleepiness (EDS) statuses in Parkinson’s disease (PD); therefore, we aimed to compare QoL and reveal the potential heterogeneous predictors of QoL between patients with PD with and without EDS.MethodsWe collected clinical data among 306 patients with PD over 2 years. EDS was assessed by the Epworth Sleepiness Scale and QoL was measured with the 39-item Parkinson’s Disease Questionnaire.ResultsWe found that at both baseline and follow-up, patients with PD with EDS had poorer QoL and suffered more non-motor symptoms including depression and clinical probable rapid eye movement sleep behavior disorder (cpRBD). The generalized linear mixed model analysis indicated that the major predictors of QoL in PD with EDS were the akinetic-rigid type, disease duration, and total levodopa equivalent dose, while in PD without EDS, the primary determinants of QoL were Hoehn and Yahr, Mini-Mental State Examination (MMSE), and cpRBD.ConclusionPatients with PD with EDS presented with poorer QoL. Besides, the baseline predictors of future QoL differed between patients with PD with and without EDS. These findings remind clinicians to target specific clinical factors when attempting to improve QoL among patients with PD.

Quality of life in children with cochlear implants in Kazakhstan

BackgroundAlthough cochlear implantation (CI) has been performed in Kazakhstan since 2007 little is known about quality of life of patients after CI. The aim of this study was to assess the health-related quality of life (HRQoL) of Kazakhstani children after CI.MethodsAltogether, 53 families with a child using a cochlear implant for at least 1 year participated in the study between July 20, 2019 and February 20, 2020 at the Audiological Сenter of Almaty, Kazakhstan. The parents/caregivers completed the “Children with Cochlear Implants: Parental Perspectives (CCIPP)” questionnaire.Results‘Well-being and happiness’ subdomain of the HRQoL yielded the highest ratings. ‘Communication’, ‘general functioning’, ‘self-reliance’, and ‘supporting the child’ subdomains each achieved significant (p < 0.01) associations with all HRQoL subdomains. There were positive correlations between language used by the parent who completed the questionnaire (Kazakh or Russian) and three HRQoL subdomains, including ‘well-being and happiness’, ‘supporting the child’ and ‘social relations’.ConclusionParents/caregivers reported high quality of life in all HRQoL subdomains. Further research in this area with more detailed socio-demographic and medical history data is required to identify quality of life predictors in children after cochlear implantation.

Predictors of vision-related quality of life in patients with macular oedema receiving intra-vitreal anti-VEGF treatment.

PurposeTo determine which demographic and clinical characteristics are predictive of vision‐related quality of life (VrQoL) and quality of life (QoL) in patients with macular oedema receiving intravitreal anti‐vascular endothelial growth factor (VEGF) treatment.MethodsVision‐related quality of life (VrQoL) and quality of life (QoL) were measured in 712 patients with retinal exudative disease receiving anti‐VEGF treatment at baseline, 6 and 12 months. VrQoL was measured using an item‐response theory based 47‐question item bank (EyeQ), whereas QoL was measured using the EuroQol Five Dimensions (EQ‐5D) questionnaire. The EQ‐5D score was dichotomized into a perfect score of 1 and a suboptimal score of <1. Demographic and clinical patient characteristics were considered as possible predictors of (Vr)QoL. Prediction models for (Vr)QoL were created with linear mixed models and generalised estimating equations, using a forward selection procedure.ResultsA worse VrQoL was predicted by poorer LogMAR visual acuity of the better eye, female sex, single civil status, older age, longer length of anti‐VEGF treatment at baseline and the presence of non‐ocular and ocular comorbidities. Suboptimal EQ‐5D scores were predicted by poorer LogMAR visual acuity of the better eye, female sex, single civil status, older age, the presence of non‐ocular comorbidities and a lower educational background.ConclusionsAlong with visual acuity of the better eye, which is the main factor used in clinical decision making, other patient characteristics should also be considered for the risk assessment of (Vr)QoL, such as sex, age, civil status, comorbidities and length of anti‐VEGF treatment.

Longitudinal Prospective Evaluation of Quality of Life After Axillary Lymph Node Dissection.

Patients often fear axillary lymph node dissection (ALND) because of its associated complications; however, its effect on quality of life (QOL) is not well described. We aimed to evaluate the effect of ALND on QOL over time and to identify predictors of worse QOL. Breast cancer patients undergoing ALND were enrolled in a prospective lymphedema screening study. Arm volumes were measured and QOL questionnaires completed at baseline, postoperatively, and at 6-month intervals. The upper limb lymphedema-27 questionnaire was used to assess the effect of upper extremity symptoms on QOL in three domains (physical, psychological, and social). Predictors of QOL were identified by univariate and multivariable regression analyses. From November 2016 through March 2020, 304 ALND patients were enrolled; 242 patients with at least two measurements and 6 months of follow-up were included. Median age was 48 years, and median follow-up was 1.2 years. The 18-month lymphedema rate was 18%. Overall, QOL scores in all three domains decreased postoperatively and improved over time. On multivariable analysis, after adjusting for baseline scores, symptoms necessitating lymphedema therapy referral (p = 0.006) were associated with worse physical QOL. Younger age (p = 0.005) and lymphedema therapy referral (p = 0.006) were associated with worse psychological QOL. Arm volume was not correlated with QOL. QOL scores initially decreased after ALND but improved by 6 months post-surgery. Decreases in QOL were independent of arm volume. Patients with worse QOL more often sought lymphedema therapy, although the effect of therapy on QOL remains unknown.

Quality of Life, Anxiety, Depression and Psychological Distress in Patients with Cancer During the COVID 19 Pandemic: A Systematic Review

Introduction and Objectives: Quality of life (QOL) and psychological wellbeing deteriorate during the COVID 19 pandemic in patients with cancer. Purpose: This study aims to review the current evidence of QOL, anxiety, depression, psychological distress, and their inter-relationship in patients with cancer and survivors during the COVID 19 pandemic. Moreover, this study identifies factors associated with QOL and mental health in patients with cancer and survivors during the COVID 19 pandemic. Methods: An extensive electronic database search was conducted. Articles published in English assessing cancer patients and cancer survivors’ QOL and psychological wellbeing. Results: Twenty-seven articles with 22,134 participants were included. Concerns related to contracting COVID 19, along with potential treatment plans were predictors of impaired QOL. Advanced age, family support, being identified as a male and having less comorbid conditions were associated with the high level of QOL. Delay or change in treatment plan, contact with COVID 19 positive individuals, and emotional vulnerability were found to be independently associated with high levels of anxiety, depression, and distress. Conclusion: Health professionals, caregivers and support services should pay more attention on QOL and psychological wellbeing of the patients with cancer. Counselling sessions, support services should be established to improve their life satisfaction and wellbeing.

IDF21-0436 Pharmacotherapy, adherence to medications and quality of life among diabetic patients with heart failure

Background: Patients with heart failure (HF) and diabetes mellitus (DM) have poorer clinical outcomes than patients with HF without DM. These patients may experience a striking deterioration, frequent hospitalizations, and increased all-cause mortality. Adherence to effective pharmacotherapy influences their quality of life (QOL). Aim: The objectives of this study were to evaluate the patterns of pharmacotherapy, assess factors affecting adherence to medication and quality of life (QOL) in diabetic patients with heart failure in an Indian tertiary care hospital setting. Method: We conducted a cross sectional study among patients with Type 2 Diabetes mellitus (T2 DM) and heart failure in an Indian tertiary care hospital from April 2018 to March 2020 after obtaining the informed consent (IEC approval No 82/2018). Data on sociodemographic characteristics, clinical features, pharmacotherapy, adherence to medication (Adherence and refills to medication scale) and quality of life (EQ 5D-3L) were collected prospectively by record review and patient interview. Data were analysed by independent samples t test, chi square test and multiple logistic regression analysis using SPSS 26.0. Results: We included 125 patients with Type 2 Diabetes mellitus (T2 DM) and heart failure. The mean age was 60.2 ±9.45 years with a male preponderance (74%). Smoking was noticed in 84% of patients and alcohol use in 57%. About 58% had other comorbidities, with hypertension in 58%. Mean HbA1C was 8.28±1.04. About 45% had a reduced ejection fraction (EF) and 55% had preserved EF. Polypharmacy was noted in 90%. The five most common drug classes used were diuretics (95%), antihypertensives (90%), antiplatelets (90%) insulin (78%), and statins (67%). Oral hypoglycaemic were used by 40%. Beta blockers were prescribed in 28% of patients. The most common adverse outcome was end stage renal disease (17%). Poor adherence to medications was noted in 54% of patients. Poor educational status <12th standard (38.8% vs 55.1%) and lower mean monthly income (15586.21±1874.79 vs 22044.78±1957.07) were noticed among those with overall poor adherence (p<0.05). On multivariate analysis, poor educational status (OR= 0.16, CI= 0.070-0.365, p<0.001) was noticed as an important predictor for poor adherence. Overall poor mean QOL score (0.67 ±0.22) was noticed in patients with type 2 DM and HF. Alcohol use (OR= 3.64, CI= 1.603-8.301, p= 0.002), chewable tobacco use (OR= 2.39, CI=1.030-5.549,P=0.04) and low overall health scale score (OR= 1.06, CI= 1.024-1.099, p<0.001)) were noticed as predictors of poor QOL. Discussion: Diabetic patients with congestive heart failure were found to have a male preponderance, multiple comorbidities, polypharmacy, poor adherence to medications, and an overall poor QOL score. Utilization of diuretics, antihypertensives, antiplatelets, insulin, and statins were noticed in most patients. Poor educational status and lower mean monthly income were associated with poor medication adherence. Alcohol and chewable tobacco usage and lower health scale scores were noticed as predictors poor QOL.

Understanding the Independent Predictors of Dysphagia-Related Quality of Life in Stroke Survivors.

It is important to pinpoint modifiable factors contributing to reduced dysphagia-related quality of life (QoL) in order to improve treatment outcomes and patient health given that a large proportion of stroke survivors experience dysphagia. The purpose of this exploratory study was to identify the independent predictors of dysphagia-related QoL in community-dwelling stroke survivors. A sample of 31 adult stroke survivors with dysphagia (M age = 62 years; 23 males) and their partners (M age = 57 years; seven males) participated in the study. Survivors were > 3 months poststroke and living with their partner. Backward regression analysis methods were employed to determine independent predictors of dysphagia-related QoL using scores from the Swallowing-Related Quality of Life questionnaire. Independent variables tested included age, employment status, receiving dysphagia treatment, number of medical conditions, level of diet modification, Stroke Impact Scale (SIS) scores, relationship with partner, partner age, partner employment status, partner burden, and partner depression. Results indicated that number of survivor medical conditions, degree of diet modification, SIS emotional subscale score, and partner employment status significantly predicted dysphagia-related QoL (p < .001). More specifically, stroke survivors with more medical conditions or a partner who worked outside of the home had worse dysphagia-related QoL, and those with better mental health or a less modified diet had better dysphagia-related QoL. Factors related to dysphagia-related QoL are multifactorial and include both survivor and spousal variables. The results of this exploratory study highlight the need for clinicians and researchers to consider patient function and needs more wholistically to maximize perceived QoL.

Quality of Life Predictors in Patients With Melanoma: A Machine Learning Approach

Health related quality of life (HRQoL) is an important recognized health outcome for cancer treatments, but also disease course with slower recovery and increased morbidity. These issues are of implication in melanoma, which maintains a risk of disease progression for many years after diagnosis. This study aimed to explore and weigh factors in the perception of the quality of life and possible relationships with demographic–clinical characteristics in people with melanoma via a machine learning approach. In this observational study, patients with melanoma, without metastatic disease, were recruited from January 2020 to December 2021 with a follow-up of at least one year. Demographic variables and clinics were collected, and the 12-Item Short-Form Health Survey (SF-12) was adopted as the physical and mental aspects of the Health-Related Quality of Life (HRQoL) measure. All the variables were processed in a random forest model to weigh at each node of each tree of this machine learning regression model, their actual weight in SF-12 score. We included 203 melanoma patients, mean aged 59.25 ± 15.1 years: 56 (27%) affecting the upper limbs and 147 (73%) affecting the trunk. The model of 142 patients with no missing value, generating 92 trees (MSE = 0.45, R2 of 0.78), reported that the lesion site was the most influencing variable on HRQoL based on the decrease in Gini impurity in variable weighing at each node intersection in forest generation. In this scenario, we built two distinct models for lesion sites and demonstrated that the variable that most influenced the quality of life in upper limb melanoma was lymphedema, while BMI was in the trunk. Given these results, random forest regressions could play a crucial role in the clinical and rehabilitation approach. The machine-learning model for detecting the HRQoL predictor in melanoma patients indicates that the experienced lymphedema and BMI may influence the HRQoL perception. This study suggests that the prevention and treatment of lymphedema and bodyweight reduction might improve the quality of life in melanoma.

Quality of Life in Internet Use Disorder Patients With and Without Comorbid Mental Disorders.

IntroductionEvidence from clinical studies on quality of life (QoL) in patients suffering from internet use disorders (IUD) is still limited. Furthermore, the impact of additional mental comorbidities on QoL in IUD patients has rarely been investigated yet.Materials and MethodsIn a cross-sectional clinical study 149 male subjects were analyzed for the presence and severity of an IUD as well as other mental disorders by experienced clinicians. The sample consisted of 60 IUD patients with and without comorbid mental disorders, 34 non-IUD patients with other mental disorders, and 55 healthy participants. Standardized clinical interviews (M.I.N.I. 6.0.0) and questionnaires on IUD symptom severity (s-IAT), QoL (WHOQOL-BREF), depression and anxiety symptoms (BDI-II and BAI), and general psychological symptoms (BSI) were used.ResultsInternet use disorder patients showed significantly reduced QoL compared to healthy controls (Cohen’s d = 1.64–1.97). Furthermore, IUD patients suffering from comorbid mental disorders showed significantly decreased levels of physical, social, and environmental QoL compared to IUD patients without any comorbidity (p < 0.05–0.001). Multiple linear regression analyses revealed that low levels of psychological, social and environmental QoL were mainly predicted by symptoms of depression. IUD factors were only significant predictors for the social and physical QoL.DiscussionInternet use disorder patients with comorbid mental disorder reported the lowest QoL. Depression symptom severity was the most significant predictor of low QoL in IUD. Strategies to reduce depressive symptoms should therefore be considered in IUD treatment to increase patients’ QoL.

Prediction of quality of life in schizophrenia using machine learning models on data from Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial

While research focus remains mainly on psychotic symptoms, it is questionable whether we are placing enough emphasis on improving the quality of life (QoL) of schizophrenia patients. To date, the predictive power of QoL remained limited. Therefore, this study aimed to accurately predict the QoL within schizophrenia using supervised learning methods. The authors report findings from participants of a large randomized, double-blind clinical trial for schizophrenia treatment. Potential predictors of QoL included all available and non-redundant variables from the dataset. By optimizing parameters, three linear LASSO regressions were calculated (N = 697, 692, and 786), including 44, 47, and 41 variables, with adjusted R-squares ranging from 0.31 to 0.36. Best predictors included social and emotion-related symptoms, neurocognition (processing speed), education, female gender, treatment attitudes, and mental, emotional, and physical health. These results demonstrate that machine learning is an excellent predictive tool to process clinical data. It appears that the patient’s perception of their treatment has an important impact on patients’ QoL and that interventions should consider this aspect.Trial registration: ClinicalTrials.gov Identifier: NCT00014001.

The impact of schizotypy on quality of life among adults with autism spectrum disorder

BackgroundAutism spectrum disorder (ASD) and schizotypal personality disorder can be difficult to distinguish. Deficits in social relationships and social interaction, present in both conditions, are known to impair quality of life. The aim of the present study was to investigate if schizotypal symptoms affect quality of life among adults diagnosed with autism spectrum disorder and to study the association between schizotypy and autistic traits among them.MethodsParticipants diagnosed with autism spectrum disorder (n = 110) completed questionnaires exploring schizotypy (Schizotypal Personality Questionnaire – Brief Revised (SPQ-BR)), autistic traits (The Ritvo Autism, Asperger Diagnostic Scale-Revised Screen 14 items), anxiety and depression (The Hospital Anxiety and Depression scale) and quality of life (Brunnsviken Brief Quality of Life Scale and the European quality of life index version 5D).ResultsSchizotypy was found to be associated with anxiety, depressive and autistic symptoms, and poor quality of life. Although schizotypy was a predictor for impaired quality of life, this relationship was mediated by symptoms of anxiety and depression, plausibly inherent to autism. Autistic traits were positively associated with all higher order constructs of the SPQ-BR, i.e. positive and negative schizotypy, disorganization and social anxiety, as well as with poor quality of life.ConclusionsThere is considerable overlap between schizotypy and autism that needs to be considered in research. Prominent schizotypal traits in people with ASD may constitute an endophenotype coinciding with a particularly poor quality of life.Trial registrationClinicalTrials.gov identifier: NCT03570372: Internet-based Treatment for Adults with Autism Spectrum Disorder (MILAS).

Physical and Mental Aspects of Quality of Life in Patients With Charcot-Marie-Tooth Disease Type 1A.

IntroductionCharcot-Marie-Tooth type 1A (CMT1A) comprises ~50% of all CMT cases. CMT1A is a slowly progressive motor and sensory neuropathy that leads to significant disability. We aimed to investigate the quality of life (QoL) in Serbian patients with CMT1A and to assess sociodemographic and clinical features associated with their QoL.Material and MethodsForty-five genetically confirmed patients with CMT1A were included −60% women [age 50.4 ± 12.6 years, disease duration 22 (12.5–31.5) years]. SF-36, Medical Research Council (MRC) Sum Score, CMT Examination Score (CMTES), Overall Neuropathy Limitation Scale (ONLS), Beck Depression Inventory (BDI), and Krupp's Fatigue Severity Scale (FSS) were used in the study.ResultsRegarding SF-36, Mental Health and Social Functioning were the scales with the best achievements, whereas Role Physical was the worst domain. Worse QoL in patients with CMT1A was associated with elder age (rho = −0.34, p < 0.05), longer disease duration (rho = −0.31, p < 0.05), more pronounced muscle weakness measured by MRC-SS (rho = 0.43, p < 0.01), presence of tremor (p < 0.05), worse CMTES (rho = −0.68, p < 0.01), more severe disability in upper (rho = −0.70, p < 0.01) and lower limbs (rho = −0.61, p < 0.01) measured by ONLS scores, use of walking aids (p < 0.01), and with depression (p < 0.01) and fatigue (p < 0.01). Worse scores on CMTES (beta = −0.43, p < 0.01), BDI (beta = −0.39, p < 0.01), and FSS (beta = −0.36, p < 0.01) were significant independent predictors of worse QoL in patients with CMT1A (adjusted R2 = 0.77, p < 0.001).ConclusionBesides impairment made directly by CMT1A itself, QoL in these patients was also strongly affected by the presence of depression and fatigue. Since CMT1A is still not a curable disease, it is of interest to identify factors associated with QoL that are amenable to treatment.

Quality of life predictors in patients with melanoma: a machine learning approach

Quality of life predictors in patients with melanoma: a machine learning approach

Quality of life, disability, and clinical variables in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a motor neuron disease that results in a progressive increase in dysfunctions, limitations and restrictions over time, which can impact on quality of life (QoL). Therefore, expanding knowledge on QoL and possible factors associated with ALS can enable the development of actions to ensure greater wellbeing for the population. To investigate QoL in ALS and determine associations with demographic, functional and clinical aspects. Forty-five individuals with ALS (56.4±11.1 years) participated in the study. Demographic, clinical and functional aspects were investigated. Functioning and QoL were assessed using disease-specific tools (ALS Functional Ranting Scale-Revised/ALSFRS-R and ALS Assessment Questionnaire/ALSAQ-40). Fatigue was assessed using the Fatigue Severity Scale. Descriptive, correlation and stepwise multiple linear regression analyses were performed with the aid of the SPSS. The mean ALSAQ-40 score was 279.0±118.3. QoL was significantly worse among women (p=0.001) and poor QoL was associated with the inability to walk (p=0.014), pain (p=0.021) and disease severity (p≤0.002). QoL was strongly correlated with the ALSFRS-R score (r=-0.82). Moderate to weak correlations were found for mobility [turning in bed (r=-0.62), locomotion (r=-0.33) and sit to stand (r=-0.40)], strength (r=-0.49), fatigue (r=0.35) and pain (r=-0.32) (p<0.03). The regression analysis revealed that the ALSFRS-R score (β=-0.76; p=0.00) and fatigue (β=0.20; p=0.04) were predictors of QoL. QoL was worse in women, older people, severe stages of ALS, patients with impaired mobility, those with a poorer physical performance and those who reported pain. Functional status and fatigue are predictors of QoL in ALS.

Abstract P080: Health-related Quality Of Life Predictors Of Exercise Intervention Dropout

Introduction: Though many individuals know the health benefits of participating in exercise, few report sufficient activity to meet the US 2018 Physical Activity Guidelines. Current research assessing predictors of exercise adherence and dropout has primarily focused on cognitive factors, physiological factors, and demographic characteristics. The purpose of this analysis was to determine if baseline self-rated HrQoL measures are predictive of dropout from an exercise intervention across two STRRIDE trials. Methods: A total of 444 adults with dyslipidemia (STRRIDE AT/RT) or prediabetes (STRRIDE-PD) were randomized to one of seven exercise interventions, ranging from doses of 10-16 kcal/kg/week (KKW); intensities of 50-75% V̇O 2peak ; and durations of 6-9 months. Six groups included aerobic exercise, two groups included resistance training, and one group included dietary intervention (weight loss goal of 7%). Dropout was defined as a participant who did not complete the exercise intervention due to one or more of several reported reasons (e.g., time, motivation, re-occurring injury). Backwards stepwise logistic regression determined significant baseline HrQoL predictors of exercise intervention dropout, while controlling for age, sex, race, and intervention group assignment. Results: A total of 117 individuals were classified as being exercise intervention dropouts (STRRIDE AT/RT: n=55; STRRIDE-PD: n=62). In STRRIDE AT/RT, the logistic regression identified baseline sleep quality, sleep latency, sleep efficiency, sleep disturbance, bodily pain, and social functioning scores as predictors of dropout (R 2 =0.39). In STRRIDE-PD, the logistic regression identified baseline role-emotional, satisfaction with appearance, and physical component scores as predictors of dropout (R 2 =0.08). Conclusion: Among individuals with dyslipidemia, baseline HrQoL measures were able to explain about 39% of the variance in dropout from an exercise intervention, with primarily sleep measures, bodily pain, and social functioning being identified as important predictors of dropout. In contrast, among individuals farther along the disease spectrum, with prediabetes, baseline HrQoL measures only explained about 8% of the variance in dropout, with emotional well-being, perceived appearance, and physical function being important predictors of dropout. Future research should investigate molecular and biological predictors of dropout in combination with HrQoL, physiological, cognitive, and demographic factors to improve predictive power.

Malnutrition by GLIM criteria in chronic pancreatitis: Prevalence, predictors, and its impact on quality of life

IntroductionMalnutrition in chronic pancreatitis (CP) has prognostic value and there is limited data on the prevalence, predictors of malnutrition in CP and its effect on Quality of life (QoL). MethodsA retrospective study was conducted in patients with CP to assess the prevalence of malnutrition as per the Global Leadership Initiative on Malnutrition (GLIM) criteria. Multivariable-adjusted regression was used to identify independent predictors of both malnutrition and global QoL. ResultsA total of 297 patients were included and the most common etiology of CP was idiopathic (75%) and alcohol (25%). The prevalence of malnutrition was 46.4% as per GLIM criteria. On univariate analysis, the risk of malnutrition was significantly higher in alcoholic etiology (p = 0.001), current alcohol consumption (p = 0.001), smokers (p < 0.001), those having higher cumulative days of pain in last 6 months (p < 0.001) and lower daily calorie intake (p = 0.019). On multivariate analysis, malnutrition was independently associated with current alcohol consumption (Odds ratio: 3.22, p = 0.017), current smokers (OR: 2.23, p = 0.042) and those having higher cumulative days of abdominal pain (OR: 1.01, p < 0.001), while higher daily calorie intake (per 100 kcal) (OR:0.94, p = 0.023) has reduced risk of malnutrition. Malnutrition (p = 0.015) and higher cumulative days of abdominal pain (p < 0.001) were independently associated with lower global QoL in patients with CP. ConclusionMalnutrition is frequent in patients with CP; and current alcohol consumption, smoking and higher cumulative days of abdominal pain independently predicts risk of developing malnutrition. Patients with malnutrition and higher cumulative days of pain has poorer quality of life.

Long-Term Effects of Obstetric Fistula on the Overall Quality of Life among Survivors Who Had Undergone Obstetric Fistula Repair, Central Gondar Zone, Northwest Ethiopia, 2020: A Community-Based Study.

Introduction Childbirth is a special time in the lives of women and families at large. It can also be a time of great tragedy. International reports show that, annually, more than 500,000 women die from pregnancy and childbirth complications globally. For every woman who dies in childbirth, majorities remain alive, but scarred by permanent disabilities. Obstetric fistula is, without a doubt, the most severe of pregnancy-related disabilities. Objective This research is aimed at assessing the long-term effects of obstetric fistula on the overall quality of life among fistula survivors in central Gondar zone. Methods A community-based cross-sectional study was conducted among women who had undergone obstetric fistula repair, 1-4 years after the surgery, in the central Gondar zone. The participants were reached through appointments that were made by the researchers using census approach after having the participants' contact lists (specific residence and cell phone numbers), and research interviews have taken place at the respondents' home or residence using an adapted and validated tool. Data entry and analysis were done using Epi Info version 7 and SPSS version 20, respectively. Results A total of 182 fistula survivors were interviewed giving a 94.8% response rate. This study indicated that 84.1% (95% CI: 78.8, 89.4) of respondents had a poor overall quality of life. Maternal age (>30 years) (AOR = 3.8, 95% CI: 2.6, 12.3), marital status (divorced survivors) (AOR = 2.7, 95% CI: 1.3, 8.5), and urinary incontinence (AOR = 1.9, 95% CI: 2.4, 11.2) were positive predictors for poor overall quality of life. The majority of fistula survivors, 82.4%, were stigmatized which could make reintegration into the community challenging for them. Healthcare providers have to implement counseling to women for social reintegration and the possibility of gainful societal activities after repairing.