Background The long-term prognosis after acute kidney injury (AKI) is variable. It is unclear how the prognosis of AKI and its relationship to prognostic factors (baseline kidney function, AKI ...severity, prior AKI episodes, and recovery of kidney function) change as follow-up progresses. Study Design Observational cohort study. Setting & Participants The Grampian Laboratory Outcomes Morbidity and Mortality Study II (GLOMMS-II) is a large regional population cohort with complete serial biochemistry and outcome data capture through data linkage. From GLOMMS-II, we followed up 17,630 patients hospitalized in 2003 through to 2013. Predictors AKI identified using KDIGO (Kidney Disease: Improving Global Outcomes) serum creatinine criteria, characterized by baseline kidney function (estimated glomerular filtration rate eGFR ≥ 60, 45-59, 30-44, and <30 mL/min/1.73 m2 ), AKI severity (KDIGO stage), 90-day recovery of kidney function, and prior AKI episodes. Outcomes Intermediate- (30-364 days) and long-term (1-10 years) mortality and long-term renal replacement therapy. Measurements Poisson regression in time discrete intervals. Multivariable Cox regression for those at risk in the intermediate and long term, adjusted for age, sex, baseline comorbid conditions, and acute admission circumstances. Results Of 17,630 patients followed up for a median of 9.0 years, 9,251 died. Estimated incidences of hospital AKI were 8.4% and 17.6% for baseline eGFRs ≥ 60 and <60 mL/min/1.73 m2 , respectively. Intermediate-term (30-364 days) adjusted mortality HRs for AKI versus no AKI were 2.48 (95% CI, 2.15-2.88), 2.50 (95% CI, 2.04-3.06), 1.90 (95% CI, 1.51-2.39), and 1.63 (95% CI, 1.20-2.22) for eGFRs ≥ 60, 45 to 59, 30 to 44, and <30 mL/min/1.73 m2 , respectively. Among 1-year survivors, long-term HRs were attenuated: 1.44 (95% CI, 1.31-1.58), 1.25 (95% CI, 1.09-1.43), 1.21 (95% CI, 1.03-1.42), and 1.08 (95% CI, 0.85-1.36), respectively. The excess long-term hazards in AKI were lower for lower baseline eGFRs ( P for interaction = 0.01). Limitations Nonprotocolized observational data. No adjustment for albuminuria. Conclusions The prognostic importance of a discrete AKI episode lessens over time. Baseline kidney function is of greater long-term importance.
Abstract
Background
Multimorbidity, the coexistence of multiple health conditions, is a growing public health challenge. Research and intervention development are hampered by the lack of consensus ...regarding defining and measuring multimorbidity. The aim of this systematic review was to pool the findings of systematic reviews examining definitions and measures of multimorbidity.
Methods
Medline, Embase, PubMed and Cochrane were searched from database inception to February 2017. Two authors independently screened titles, abstracts and full texts and extracted data from the included papers. Disagreements were resolved with a third author. Reviews were quality assessed.
Results
Of six reviews, two focussed on definitions and four on measures. Multimorbidity was commonly defined as the presence of multiple diseases or conditions, often with a cut-off of two or more. One review developed a holistic definition including biopsychosocial and somatic factors as well as disease. Reviews recommended using measures validated for the outcome of interest. Disease counts are an alternative if no validated measure exists.
Conclusions
To enable comparison between studies and settings, researchers and practitioners should be explicit about their choice of definition and measure. Using a cut-off of two or more conditions as part of the definition is widely adopted. Measure selection should be based on tools validated for the outcome being considered. Where there is no validated measure, or where multiple outcomes or populations are being considered, disease counts are appropriate.
Multimorbidity (multiple coexisting chronic health conditions) is common and increasing worldwide, and makes care challenging for both patients and healthcare systems. To ensure care is ...patient-centred rather than specialty-centred, it is important to know which conditions commonly occur together and identify the corresponding patient profile. To date, no studies have described multimorbidity clusters within an unselected hospital population. Our aim was to identify and characterise multimorbidity clusters, in a large, unselected hospitalised patient population. Linked inpatient hospital episode data were used to identify adults admitted to hospital in Grampian, Scotland in 2014 who had ≥ 2 of 30 chronic conditions diagnosed in the 5 years prior. Cluster analysis (Gower distance and Partitioning around Medoids) was used to identify groups of patients with similar conditions. Clusters of conditions were defined based on clinical review and assessment of prevalence within patient groups and labelled according to the most prevalent condition. Patient profiles for each group were described by age, sex, admission type, deprivation and urban-rural area of residence. 11,389 of 41,545 hospitalised patients (27%) had ≥ 2 conditions. Ten clusters of conditions were identified: hypertension; asthma; alcohol misuse; chronic kidney disease and diabetes; chronic kidney disease; chronic pain; cancer; chronic heart failure; diabetes; hypothyroidism. Age ranged from 51 (alcohol misuse) to 79 (chronic heart failure). Women were a higher proportion in the chronic pain and hypothyroidism clusters. The proportion of patients from the most deprived quintile of the population ranged from 6% (hypertension) to 14% (alcohol misuse). Identifying clusters of conditions in hospital patients is a first step towards identifying opportunities to target patient-centred care towards people with unmet needs, leading to improved outcomes and increased efficiency. Here we have demonstrated the face validity of cluster analysis as an exploratory method for identifying clusters of conditions in hospitalised patients with multimorbidity.
Abstract
With increasing numbers infected by SARS-CoV-2, understanding long-COVID is essential to inform health and social care support. A Scottish population cohort of 33,281 laboratory-confirmed ...SARS-CoV-2 infections and 62,957 never-infected individuals were followed-up via 6, 12 and 18-month questionnaires and linkage to hospitalization and death records. Of the 31,486 symptomatic infections,1,856 (6%) had not recovered and 13,350 (42%) only partially. No recovery was associated with hospitalized infection, age, female sex, deprivation, respiratory disease, depression and multimorbidity. Previous symptomatic infection was associated with poorer quality of life, impairment across all daily activities and 24 persistent symptoms including breathlessness (OR 3.43, 95% CI 3.29–3.58), palpitations (OR 2.51, OR 2.36–2.66), chest pain (OR 2.09, 95% CI 1.96–2.23), and confusion (OR 2.92, 95% CI 2.78–3.07). Asymptomatic infection was not associated with adverse outcomes. Vaccination was associated with reduced risk of seven symptoms. Here we describe the nature of long-COVID and the factors associated with it.
A systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed ...studies internationally.
We systematically reviewed studies on multimorbidity, via a search of nine bibliographic databases (Ovid PsycINFO, Embase, Global Health, and MEDLINE, Web of Science, the Cochrane Library, CINAHL Plus, Scopus, and ProQuest Dissertations & Theses Global), from inception to Jan 21, 2020. Reference lists and tracked citations of retrieved articles were hand-searched. Eligible studies were full-text articles measuring multimorbidity for any purpose in community, primary care, care home, or hospital populations receiving a non-specialist service. Abstracts, qualitative research, and case series were excluded. Two reviewers independently reviewed the retrieved studies with conflicts resolved by discussion or a third reviewer, and a single researcher extracted data from published papers. To assess our objectives of how multimorbidity has been measured and examine variation in the chronic conditions included (in terms of number and type), we used descriptive analysis (frequencies, cross-tabulation, and negative binomial regression) to summarise the characteristics of multimorbidity studies and measures (study setting, source of morbidity data, study population, primary study purpose, and multimorbidity measure type). This systematic review is registered with PROSPERO, CRD420201724090.
566 studies were included in our review, of which 206 (36·4%) did not report a reference definition for multimorbidity and 73 (12·9%) did not report the conditions their measure included. The number of conditions included in measures ranged from two to 285 (median 17 IQR 11–23). 452 (79·9%) studies reported types of condition within a single multimorbidity measure; most included at least one cardiovascular condition (441 97·6% of 452 studies), metabolic and endocrine condition (440 97·3%), respiratory condition (422 93·4%), musculoskeletal condition (396 87·6%), or mental health condition (355 78·5%) in their measure of multimorbidity. Chronic infections (123 27·2%), haematological conditions (110 24·3%), ear, nose, and throat conditions (107 23·7%), skin conditions (70 15·5%), oral conditions (19 4·2%), and congenital conditions (14 3·1%) were uncommonly included. Only eight individual conditions were included by more than half of studies in the multimorbidity measure used (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure), with individual mental health conditions under-represented. Of the 566 studies, 419 were rated to be of moderate risk of bias, 107 of high risk of bias, and 40 of low risk of bias according to the Effective Public Health Practice Project quality assessment tool.
Measurement of multimorbidity is poorly reported and highly variable. Consistent reporting of measure definitions should be required by journals, and consensus studies are needed to define core and study-dependent conditions to include in measures of multimorbidity.
Health Data Research UK.
Long-COVID prevalence estimates vary widely and should take account of symptoms that would have occurred anyway. Here we determine the prevalence of symptoms attributable to SARS-CoV-2 infection, ...taking account of background rates and confounding, in a nationwide population cohort study of 198,096 Scottish adults. 98,666 (49.8%) had symptomatic laboratory-confirmed SARS-CoV-2 infections and 99,430 (50.2%) were age-, sex-, and socioeconomically-matched and never-infected. While 41,775 (64.5%) reported at least one symptom 6 months following SARS-CoV-2 infection, this was also true of 34,600 (50.8%) of those never-infected. The crude prevalence of one or more symptom attributable to SARS-CoV-2 infection was 13.8% (13.2%,14.3%), 12.8% (11.9%,13.6%), and 16.3% (14.4%,18.2%) at 6, 12, and 18 months respectively. Following adjustment for potential confounders, these figures were 6.6% (6.3%, 6.9%), 6.5% (6.0%, 6.9%) and 10.4% (9.1%, 11.6%) respectively. Long-COVID is characterised by a wide range of symptoms that, apart from altered taste and smell, are non-specific. Care should be taken in attributing symptoms to previous SARS-CoV-2 infection.
Previous studies on the natural history of long-COVID have been few and selective. Without comparison groups, disease progression cannot be differentiated from symptoms originating from other causes. ...The Long-COVID in Scotland Study (Long-CISS) is a Scotland-wide, general population cohort of adults who had laboratory-confirmed SARS-CoV-2 infection matched to PCR-negative adults. Serial, self-completed, online questionnaires collected information on pre-existing health conditions and current health six, 12 and 18 months after index test. Of those with previous symptomatic infection, 35% reported persistent incomplete/no recovery, 12% improvement and 12% deterioration. At six and 12 months, one or more symptom was reported by 71.5% and 70.7% respectively of those previously infected, compared with 53.5% and 56.5% of those never infected. Altered taste, smell and confusion improved over time compared to the never infected group and adjusted for confounders. Conversely, late onset dry and productive cough, and hearing problems were more likely following SARS-CoV-2 infection.
Internationally, there have been substantial efforts to improve the early identification of chronic kidney disease (CKD), with a view to improving survival, reducing progression and minimizing ...cardiovascular morbidity and mortality. In 2002, a new and globally adopted definition of CKD was introduced. The burden of kidney function impairment in the population is unclear and widely ranging prevalence estimates have been reported.
We conducted a systematic literature review, searching databases to June 2009. We included all adult population screening studies and studies based on laboratory or clinical datasets where the denominator was clear. Studies reporting prevalence estimates based on at least one eGFR <60 mL/min/1.73m(2) or elevated creatinine above a stated threshold were included. Study design and quality were explored as potential factors leading to heterogeneity.
We identified 43 eligible studies (57 published reports) for inclusion. Substantial heterogeneity was observed with estimated prevalence (0.6-42.6%). The included studies demonstrated significant variation in methodology and quality that impacted on the comparability of their findings. From the higher quality studies, the six studies measuring impaired kidney function (iKF) using estimated glomerular filtration rate in community screening samples reported a prevalence ranging from 1.7% in a Chinese study to 8.1% in a US study, with four reporting an estimated prevalence of 3.2-5.6%. Heterogeneity was driven by the measure used, study design and study population.
In the general population, estimated iKF, particularly eGFR 30-59 mL/min/1.73m(2) was common with prevalence similar to diabetes mellitus. Appropriate care of patients poses a substantial global health care challenge.
One in eight children in the United Kingdom are estimated to have a mental health condition, and many do not receive support or treatment. The COVID-19 pandemic has negatively impacted mental health ...and disrupted the delivery of care. Prevalence of poor mental health is not evenly distributed across age groups, by sex or socioeconomic groups. Equity in access to mental health care is a policy priority but detailed socio-demographic trends are relatively under-researched.
We analysed records for all mental health prescriptions and referrals to specialist mental health outpatient care between the years of 2015 and 2021 for children aged 2 to 17 years in a single NHS Scotland health board region. We analysed trends in prescribing, referrals, and acceptance to out-patient treatment over time, and measured differences in treatment and service use rates by age, sex, and area deprivation.
We identified 18,732 children with 178,657 mental health prescriptions and 21,874 referrals to specialist outpatient care. Prescriptions increased by 59% over the study period. Boys received double the prescriptions of girls and the rate of prescribing in the most deprived areas was double that in the least deprived. Mean age at first mental health prescription was almost 1 year younger in the most deprived areas than in the least. Referrals increased 9% overall. Initially, boys and girls both had an annual referral rate of 2.7 per 1000, but this fell 6% for boys and rose 25% for girls. Referral rate for the youngest decreased 67% but increased 21% for the oldest. The proportion of rejected referrals increased steeply since 2020 from 17 to 30%. The proportion of accepted referrals that were for girls rose to 62% and the mean age increased 1.5 years.
The large increase in mental health prescribing and changes in referrals to specialist outpatient care aligns with emerging evidence of increasing poor mental health, particularly since the start of the COVID-19 pandemic. The static size of the population accepted for specialist treatment amid greater demand, and the changing demographics of those accepted, indicate clinical prioritisation and unmet need. Persistent inequities in mental health prescribing and referrals require urgent action.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Education is widely associated with better physical and mental health, but isolating its causal effect is difficult because education is linked with many socioeconomic advantages. One way to isolate ...education's effect is to consider environments where similar students are assigned to different educational experiences based on objective criteria. Here we measure the health effects of assignment to selective schooling based on test score, a widely debated educational policy.
In 1960s Britain, children were assigned to secondary schools via a test taken at age 11. We used regression discontinuity analysis to measure health differences in 5039 people who were separated into selective and non-selective schools this way. We measured selective schooling's effect on six outcomes: mid-life self-reports of health, mental health, and life limitation due to health, as well as chronic disease burden derived from hospital records in mid-life and later life, and the likelihood of dying prematurely. The analysis plan was accepted as a registered report while we were blind to the health outcome data.
Effect estimates for selective schooling were as follows: self-reported health, 0.1 worse on a 4-point scale (95%CI - 0.2 to 0); mental health, 0.2 worse on a 16-point scale (- 0.5 to 0.1); likelihood of life limitation due to health, 5 percentage points higher (- 1 to 10); mid-life chronic disease diagnoses, 3 fewer/100 people (- 9 to + 4); late-life chronic disease diagnoses, 9 more/100 people (- 3 to + 20); and risk of dying before age 60, no difference (- 2 to 3 percentage points). Extensive sensitivity analyses gave estimates consistent with these results. In summary, effects ranged from 0.10-0.15 standard deviations worse for self-reported health, and from 0.02 standard deviations better to 0.07 worse for records-derived health. However, they were too imprecise to allow the conclusion that selective schooling was detrimental.
We found that people who attended selective secondary school had more advantaged economic backgrounds, higher IQs, higher likelihood of getting a university degree, and better health. However, we did not find that selective schooling itself improved health. This lack of a positive influence of selective secondary schooling on health was consistent despite varying a wide range of model assumptions.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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