Hypertension and cardiovascular risk factor management in a multi-ethnic cohort of adults with CKD: a cross sectional study in general practice.

BACKGROUND: Hypertension, especially if poorly controlled, is a key determinant of chronic kidney disease (CKD) development and progression to end stage renal disease (ESRD). AIM: To assess hypertension and risk factor management, and determinants of systolic blood pressure control in individuals with CKD and hypertension. DESIGN AND SETTING: Cross-sectional survey using primary care electronic health records from 47/49 general practice clinics in South London. METHODS: Known effective interventions, management of hypertension and cardiovascular disease (CVD) risk in patients with CKD Stages 3-5 were investigated. Multivariable logistic regression analysis examined the association of demographic factors, comorbidities, deprivation, and CKD coding, with systolic blood pressure control status as outcome. Individuals with diabetes were excluded. RESULTS: Adults with CKD Stages 3-5 and hypertension represented 4131/286,162 (1.4%) of the total population; 1984 (48%) of these individuals had undiagnosed CKD without a recorded CKD clinical code. Hypertension was undiagnosed in 25% of the total Lambeth population, and in patients with CKD without diagnosed hypertension, 23.0% had systolic blood pressure > 140 mmHg compared with 39.8% hypertensives, p < 0.001. Multivariable logistic regression revealed that factors associated with improved systolic blood pressure control in CKD included diastolic blood pressure control, serious mental illness, history of cardiovascular co-morbidities, CKD diagnostic coding, and age < 60 years. African ethnicity and obesity were associated with poorer systolic blood pressure control. CONCLUSION: We found both underdiagnosed CKD and underdiagnosed hypertension in patients with CKD. The poor systolic blood pressure control in older age groups ≥ 60 years and in Black African or obese individuals is clinically important as these groups are at increased risk of mortality for cardiovascular diseases

Uncoded chronic kidney disease in primary care: a cross-sectional study of inequalities and cardiovascular disease risk management.

BACKGROUND: Uncoded chronic kidney disease (CKD) is associated with poorer quality of care. AIM: To ascertain the proportion and determinants of CKD, which have not been formally recorded (Read coded), and identify differences in management and quality-of-care measures for patients with coded and uncoded CKD. DESIGN AND SETTING: Cross-sectional survey undertaken in an ethnically diverse adult population using primary care electronic health records (EHRs) from GP clinics in Lambeth, South London, UK. METHOD: Multivariable logistic regression analysis examined the association of demographic factors, selected comorbidities, deprivation, and cardiovascular disease risk management in CKD, with coding status as outcome. RESULTS: In total, the survey involved 286 162 adults, of whom 9325 (3.3%) were identified with CKD stage 3-5 (assigned as CKD based on estimated glomerular filtration rate [eGFR] values). Of those identified with CKD, 4239 (45.5%) were Read coded, and 5086 (54.5%) were uncoded. Of those identified with CKD stage 3-5, individuals aged ≥50 years were more likely to be coded for CKD, compared with those aged 50% of CKD was uncoded and, for those patients, quality of care was lower compared with those with coded CKD. Future research and practices should focus on areas of greater deprivation and targeted initiatives for those aged <50 years and of black African, black Caribbean, South Asian, or non-stated ethnic groups. Possible areas for improvement include diagnostic coding support, automated CKD recording, and clinical decision support (based on adjusted eGFR results) in the GP clinical records

Improving the diagnosis and treatment of urinary tract infection in young children in primary care:results from the ‘DUTY’ prospective diagnostic cohort study

PURPOSE Up to 50% of urinary tract infections (UTIs) in young children are missed in primary care. Urine culture is essential for diagnosis, but urine collection is often difficult. Our aim was to derive and internally validate a 2-step clinical rule using (1) symptoms and signs to select children for urine collection; and (2) symptoms, signs, and dipstick testing to guide antibiotic treatment. METHODS We recruited acutely unwell children aged under 5 years from 233 primary care sites across England and Wales. Index tests were parent-reported symptoms, clinician-reported signs, urine dipstick results, and clinician opinion of UTI likelihood (clinical diagnosis before dipstick and culture). The reference standard was microbiologically confirmed UTI cultured from a clean-catch urine sample. We calculated sensitivity, specificity, and area under the receiver operator characteristic (AUROC) curve of coefficient-based (graded severity) and points-based (dichotomized) symptom/sign logistic regression models, and we then internally validated the AUROC using bootstrapping. RESULTS Three thousand thirty-six children provided urine samples, and culture results were available for 2,740 (90%). Of these results, 60 (2.2%) were positive: the clinical diagnosis was 46.6% sensitive, with an AUROC of 0.77. Previous UTI, increasing pain/crying on passing urine, increasingly smelly urine, absence of severe cough, increasing clinician impression of severe illness, abdominal tenderness on examination, and normal findings on ear examination were associated with UTI. The validated coefficient- and points-based model AUROCs were 0.87 and 0.86, respectively, increasing to 0.90 and 0.90, respectively, by adding dipstick nitrites, leukocytes, and blood. CONCLUSIONS A clinical rule based on symptoms and signs is superior to clinician diagnosis and performs well for identifying young children for noninvasive urine sampling. Dipstick results add further diagnostic value for empiric antibiotic treatment

The Diagnosis of Urinary Tract infection in Young children (DUTY): a diagnostic prospective observational study to derive and validate a clinical algorithm for the diagnosis of urinary tract infection in children presenting to primary care with an acute illness

Background: It is not clear which young children presenting acutely unwell to primary care should be investigated for urinary tract infection (UTI) and whether or not dipstick testing should be used to inform antibiotic treatment.Objectives: To develop algorithms to accurately identify pre-school children in whom urine should be obtained; assess whether or not dipstick urinalysis provides additional diagnostic information; and model algorithm cost-effectiveness.Design: Multicentre, prospective diagnostic cohort study.Setting and participants: Children &lt; 5 years old presenting to primary care with an acute illness and/or new urinary symptoms.Methods: One hundred and seven clinical characteristics (index tests) were recorded from the child’s past medical history, symptoms, physical examination signs and urine dipstick test. Prior to dipstick results clinician opinion of UTI likelihood (‘clinical diagnosis’) and urine sampling and treatment intentions (‘clinical judgement’) were recorded. All index tests were measured blind to the reference standard, defined as a pure or predominant uropathogen cultured at ? 105 colony-forming units (CFU)/ml in a single research laboratory. Urine was collected by clean catch (preferred) or nappy pad. Index tests were sequentially evaluated in two groups, stratified by urine collection method: parent-reported symptoms with clinician-reported signs, and urine dipstick results. Diagnostic accuracy was quantified using area under receiver operating characteristic curve (AUROC) with 95% confidence interval (CI) and bootstrap-validated AUROC, and compared with the ‘clinician diagnosis’ AUROC. Decision-analytic models were used toidentify optimal urine sampling strategy compared with ‘clinical judgement’.Results: A total of 7163 children were recruited, of whom 50% were female and 49% were &lt; 2 years old. Culture results were available for 5017 (70%); 2740 children provided clean-catch samples, 94% of whom were ? 2 years old, with 2.2% meeting the UTI definition. Among these, ‘clinical diagnosis’ correctly identified 46.6% of positive cultures, with 94.7% specificity and an AUROC of 0.77 (95% CI 0.71 to 0.83). Four symptoms, three signs and three dipstick results were independently associated with UTI with an AUROC (95% CI; bootstrap-validated AUROC) of 0.89 (0.85 to 0.95; validated 0.88) for symptoms and signs, increasing to 0.93 (0.90 to 0.97; validated 0.90) with dipstick results. Nappy pad samples were provided from the other 2277 children, of whom 82% were &lt; 2 years old and 1.3% met the UTI definition.‘Clinical diagnosis’ correctly identified 13.3% positive cultures, with 98.5% specificity and an AUROC of 0.63 (95% CI 0.53 to 0.72). Four symptoms and two dipstick results were independently associated with UTI, with an AUROC of 0.81 (0.72 to 0.90; validated 0.78) for symptoms, increasing to 0.87 (0.80 to 0.94; validated 0.82) with the dipstick findings. A high specificity threshold for the clean-catch model was more accurate and less costly than, and as effective as, clinical judgement. The additional diagnostic utility of dipstick testing was offset by its costs. The cost-effectiveness of the nappy pad model was not clear-cut.Conclusions: Clinicians should prioritise the use of clean-catch sampling as symptoms and signs can cost-effectively improve the identification of UTI in young children where clean catch is possible. Dipstick testing can improve targeting of antibiotic treatment, but at a higher cost than waiting for a laboratory result. Future research is needed to distinguish pathogens from contaminants, assess the impact of the clean-catch algorithm on patient outcomes, and the cost-effectiveness of presumptive versus dipstick versus laboratory-guided antibiotic treatment.Funding: The National Institute for Health Research Health Technology Assessment programme.<br/

Patient experience and the role of postgraduate GP training:a cross-sectional analysis of national Patient Survey data in England

BACKGROUND: Quality indicators for primary care focus predominantly on the public health model and organisational measures. Patient experience is an important dimension of quality. Accreditation for GP training practices requires demonstration of a series of attributes including patient-centred care. AIM: The national GP Patient Survey (GPPS) was used to determine the characteristics of general practices scoring highly in responses relating to the professional skills and characteristics of doctors. Specifically, to determine whether active participation in postgraduate GP training was associated with more positive experiences of care. DESIGN AND SETTING: Retrospective cross-sectional study in general practices in England. METHOD: Data were obtained from the national QOF dataset for England, 2011/12 (8164 general practices); the GPPS in 2012 (2.7 million questionnaires in England; response rate 36%); general practice and demographic characteristics. Sensitivity analyses included local data validated by practice inspections. Outcome measures: multilevel regression models adjusted for clustering. RESULTS: GP training practice status (29% of practices) was a significant predictor of positive GPPS responses to all questions in the ‘doctor care’ (n = 6) and ‘overall satisfaction’ (n = 2) domains but not to any of the ‘nurse care’ or ‘out-of-hours’ domain questions. The findings were supported by the sensitivity analyses. Other positive determinants were: smaller practice and individual GP list sizes, more older patients, lower social deprivation and fewer ethnic minority patients. CONCLUSION: Based on GPPS responses, doctors in GP training practices appeared to offer more patient-centred care with patients reporting more positively on attributes of doctors such as ‘listening’ or ‘care and concern’

Long term condition morbidity in English general practice:a cross-sectional study using three composite morbidity measures

BACKGROUND: The burden of morbidity represented by patients with long term conditions (LTCs) varies substantially between general practices. This study aimed to determine the characteristics of general practices with high morbidity burden. METHOD: Retrospective cross-sectional study; general practices in England, 2014/15. Three composite morbidity measures (MMs) were constructed to quantify LTC morbidity at practice level: a count of LTCs derived from the 20 LTCs included in the UK Quality and Outcomes Framework (QOF) disease registers, expressed as ‘number of QOF LTCs per 100 registered patients’; the % of patients with one or more QOF LTCs; the % of patients with one or more of 15 broadly defined LTCs included in the GP Patient Survey (GPPS). Determinants of MM scores were analysed using multi-level regression models. Analysis was based on a national dataset of English general practices (n = 7779 practices); GPPS responses (n = 903,357); general practice characteristics (e.g. list size, list size per full time GP); patient demographic characteristics (age, deprivation status); secondary care utilisation (out-patient, emergency department, emergency admission rates). RESULTS: Mean MM scores (95% CIs) were: 57.7 (±22.3) QOF LTCs per 100 registered patients; 22.8% (±8.2) patients with a QOF LTC; 63.5% (±11.7) patients with a GPPS LTC. The proportion of elderly patients and social deprivation scores were the strongest predictors of each MM score; scores were largely independent of practice characteristics. MM scores were positive predictors of secondary care utilization and negative predictors’ access, continuity of care and overall satisfaction. CONCLUSIONS: Wide variation in LTC morbidity burden was observed across English general practice. Variation was determined by demographic factors rather than practice characteristics. Higher rates of secondary care utilisation in practices with higher morbidity burden have implications for resource allocation and commissioning budgets; lower reported satisfaction in these practices suggests that practices may struggle with increased workload. There is a need for a readily available metric to define the burden of morbidity and multimorbidity in general practice

Determinants of long‐term opioid prescribing in an urban population: A cross‐sectional study

BACKGROUND: Opioid prescribing has more than doubled in the UK between 1998 and 2016. Potential adverse health implications include dependency, falls and increased health expenditure. AIM: To describe the predictors of long‐term opioid prescribing (LTOP) (≥3 opioid prescriptions in a 90‐day period). DESIGN AND SETTING: A retrospective cross‐sectional study in 41 general practices in South London. METHOD: Multi‐level multivariable logistic regression to investigate the determinants of LTOP. RESULTS: Out of 320 639 registered patients ≥18 years, 2679 (0.8%) were identified as having LTOP. Patients were most likely to have LTOP if they had ≥5 long‐term conditions (LTCs) (adjusted odds ratio [AOR] 36.5, 95% confidence interval [CI] 30.4‐43.8) or 2‐4 LTCs (AOR 13.8, CI 11.9‐16.1) in comparison to no LTCs, were ≥75 years compared to 18‐24 years (AOR 12.31, CI 7.1‐21.5), were smokers compared to nonsmokers (AOR 2.2, CI 2.0‐2.5), were female rather than male (AOR 1.9, CI 1.7‐2.0) and in the most deprived deprivation quintile (AOR 1.6, CI 1.4‐1.8) compared to the least deprived. In a separate model examining individual LTCs, the strongest associations for LTOP were noted for sickle cell disease (SCD) (AOR 18.4, CI 12.8‐26.4), osteoarthritis (AOR 3.0, CI 2.8‐3.3), rheumatoid arthritis (AOR 2.8, CI 2.2‐3.4), depression (AOR 2.6, CI 2.3‐2.8) and multiple sclerosis (OR 2.5, CI 1.4‐4.4). CONCLUSION: LTOP was significantly higher in those aged ≥75 years, with multimorbidity or specific LTCs: SCD, osteoarthritis, rheumatoid arthritis, depression and multiple sclerosis. These characteristics may enable the design of targeted interventions to reduce LTOP