A Prognostic Model for Critically Ill Children in Locations With Emerging Critical Care Capacity.

OBJECTIVES: To develop a clinical prediction model to risk stratify children admitted to PICUs in locations with limited resources, and compare performance of the model to nine existing pediatric severity scores. DESIGN: Retrospective, single-center, cohort study. SETTING: PICU of a pediatric hospital in Siem Reap, northern Cambodia. PATIENTS: Children between 28 days and 16 years old admitted nonelectively to the PICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Clinical and laboratory data recorded at the time of PICU admission were collected. The primary outcome was death during PICU admission. One thousand five hundred fifty consecutive nonelective PICU admissions were included, of which 97 died (6.3%). Most existing severity scores achieved comparable discrimination (area under the receiver operating characteristic curves [AUCs], 0.71-0.76) but only three scores demonstrated moderate diagnostic utility for triaging admissions into high- and low-risk groups (positive likelihood ratios [PLRs], 2.65-2.97 and negative likelihood ratios [NLRs], 0.40-0.46). The newly derived model outperformed all existing severity scores (AUC, 0.84; 95% CI, 0.80-0.88; p < 0.001). Using one particular threshold, the model classified 13.0% of admissions as high risk, among which probability of mortality was almost ten-fold greater than admissions triaged as low-risk (PLR, 5.75; 95% CI, 4.57-7.23 and NLR, 0.47; 95% CI, 0.37-0.59). Decision curve analyses indicated that the model would be superior to all existing severity scores and could provide utility across the range of clinically plausible decision thresholds. CONCLUSIONS: Existing pediatric severity scores have limited potential as risk stratification tools in resource-constrained PICUs. If validated, our prediction model would be a readily implementable mechanism to support triage of critically ill children at admission to PICU and could provide value across a variety of contexts where resource prioritization is important.

Relationship Between Clinician Language and the Success of Behavioral Weight Loss Interventions : A Mixed-Methods Cohort Study.

BACKGROUND: International guidelines recommend that primary care clinicians recognize obesity and offer treatment opportunistically, but there is little evidence on how clinicians can discuss weight and offer treatment in ways that are well received and effective. OBJECTIVE: To examine relationships between language used in the clinical visit and patient weight loss. DESIGN: Mixed-methods cohort study. SETTING: 38 primary care clinics in England participating in the Brief Intervention for Weight Loss trial. PARTICIPANTS: 246 patients with obesity seen by 87 general practitioners randomly sampled from the intervention group of the randomized clinical trial. MEASUREMENTS: Conversation analysis of recorded discussions between 246 patients with obesity and 87 clinicians regarding referral to a 12-week behavioral weight management program offered as part of the randomized clinical trial. Clinicians' interactional approaches were identified and their association with patient weight loss at 12 months (primary outcome) was examined. Secondary outcomes included patients' agreement to attend weight management, attendance, loss of 5% body weight, actions taken to lose weight, and postvisit satisfaction. RESULTS: Three interactional approaches were identified on the basis of clinicians' linguistic and paralinguistic practices: creating a sense of referrals as "good news" related to the opportunity of the referral (n = 62); "bad news," focusing on the harms of obesity (n = 82); or neutral (n = 102). Outcome data were missing from 57 participants, so weighted analyses were done to adjust for missingness. Relative to neutral news, good news was associated with increased agreement to attend the program (adjusted risk difference, 0.25 [95% CI, 0.15 to 0.35]), increased attendance (adjusted risk difference, 0.45 [CI, 0.34 to 0.56]), and weight change (adjusted difference, -3.60 [CI, -6.58 to -0.62]). There was no evidence of differences in mean weight change comparing bad and neutral news, and no evidence of differences in patient satisfaction across all 3 approaches. LIMITATIONS: Data were audio only, so body language and nonverbal cues could not be assessed. There is potential for selection bias and residual confounding. CONCLUSION: When raising the topic of excess weight in clinical visits, presenting weight loss treatment as a positive opportunity is associated with greater uptake of treatment and greater weight loss. PRIMARY FUNDING SOURCE: National Institute for Health and Care Research School for Primary Care Research and the Foundation for the Sociology of Health and Illness.

The association between antihypertensive treatment and serious adverse events by age and frailty: A cohort study.

BACKGROUND: Antihypertensives are effective at reducing the risk of cardiovascular disease, but limited data exist quantifying their association with serious adverse events, particularly in older people with frailty. This study aimed to examine this association using nationally representative electronic health record data. METHODS AND FINDINGS: This was a retrospective cohort study utilising linked data from 1,256 general practices across England held within the Clinical Practice Research Datalink between 1998 and 2018. Included patients were aged 40+ years, with a systolic blood pressure reading between 130 and 179 mm Hg, and not previously prescribed antihypertensive treatment. The main exposure was defined as a first prescription of antihypertensive treatment. The primary outcome was hospitalisation or death within 10 years from falls. Secondary outcomes were hypotension, syncope, fractures, acute kidney injury, electrolyte abnormalities, and primary care attendance with gout. The association between treatment and these serious adverse events was examined by Cox regression adjusted for propensity score. This propensity score was generated from a multivariable logistic regression model with patient characteristics, medical history and medication prescriptions as covariates, and new antihypertensive treatment as the outcome. Subgroup analyses were undertaken by age and frailty. Of 3,834,056 patients followed for a median of 7.1 years, 484,187 (12.6%) were prescribed new antihypertensive treatment in the 12 months before the index date (baseline). Antihypertensives were associated with an increased risk of hospitalisation or death from falls (adjusted hazard ratio [aHR] 1.23, 95% confidence interval (CI) 1.21 to 1.26), hypotension (aHR 1.32, 95% CI 1.29 to 1.35), syncope (aHR 1.20, 95% CI 1.17 to 1.22), acute kidney injury (aHR 1.44, 95% CI 1.41 to 1.47), electrolyte abnormalities (aHR 1.45, 95% CI 1.43 to 1.48), and primary care attendance with gout (aHR 1.35, 95% CI 1.32 to 1.37). The absolute risk of serious adverse events with treatment was very low, with 6 fall events per 10,000 patients treated per year. In older patients (80 to 89 years) and those with severe frailty, this absolute risk was increased, with 61 and 84 fall events per 10,000 patients treated per year (respectively). Findings were consistent in sensitivity analyses using different approaches to address confounding and taking into account the competing risk of death. A strength of this analysis is that it provides evidence regarding the association between antihypertensive treatment and serious adverse events, in a population of patients more representative than those enrolled in previous randomised controlled trials. Although treatment effect estimates fell within the 95% CIs of those from such trials, these analyses were observational in nature and so bias from unmeasured confounding cannot be ruled out. CONCLUSIONS: Antihypertensive treatment was associated with serious adverse events. Overall, the absolute risk of this harm was low, with the exception of older patients and those with moderate to severe frailty, where the risks were similar to the likelihood of benefit from treatment. In these populations, physicians may want to consider alternative approaches to management of blood pressure and refrain from prescribing new treatment.

Self-monitoring for improving control of blood pressure in patients with hypertension: a Cochrane intervention review.

BACKGROUND: Hypertension is a major risk factor for cardiovascular events with only a minority of people treated to satisfactory levels. There is an increasing body of literature pertaining to the beneficial effect of self-blood pressure monitoring (SBPM) on blood pressure control in hypertensive patients. It is cost-effective, well tolerated, and has been shown to be a better predictor of end organ damage than traditional office blood pressure monitoring (OBPM). The aim of this Cochrane review is to provide an up-to-date assessment on the effectiveness of self-monitoring in the management of hypertension.Is SBPM more efficacious in reducing blood pressure, compared with OBPM or usual care?Is SBPM with additional supports more efficacious in reducing blood pressure, compared with no additional support?Are there any adverse events associated with SBPM, compared with OBPM or usual care? METHODS: All randomised controlled trials of adult patients with a diagnosis of primary hypertension where the intervention of interest is SBPM will be included. Data extraction, analysis and risk of bias assessment will be carried out by two independent authors. Analysis will be based on intention-to-treat (ITT) data from individual trials. RESULTS: Primary outcome measures include change in mean office systolic and/or diastolic BP, change in mean ambulatory blood pressure, the proportion of patients reaching target BP, and adverse events including mortality or cardiovascular morbidity or related to treatment with antihypertensive agents. DISCUSSION: This review will help to determine if self-monitoring of blood pressure, with or without co-interventions, is effective in lowering blood pressure. Results will be available for conference.

Facilitating Safe Discharge Through Predicting Disease Progression in Moderate Coronavirus Disease 2019 (COVID-19): A Prospective Cohort Study to Develop and Validate a Clinical Prediction Model in Resource-Limited Settings.

BACKGROUND: In locations where few people have received coronavirus disease 2019 (COVID-19) vaccines, health systems remain vulnerable to surges in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Tools to identify patients suitable for community-based management are urgently needed. METHODS: We prospectively recruited adults presenting to 2 hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 to develop and validate a clinical prediction model to rule out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 BPM; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex, and SpO2) and 1 of 7 shortlisted biochemical biomarkers measurable using commercially available rapid tests (C-reactive protein [CRP], D-dimer, interleukin 6 [IL-6], neutrophil-to-lymphocyte ratio [NLR], procalcitonin [PCT], soluble triggering receptor expressed on myeloid cell-1 [sTREM-1], or soluble urokinase plasminogen activator receptor [suPAR]), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration, and clinical utility of the models in a held-out temporal external validation cohort. RESULTS: In total, 426 participants were recruited, of whom 89 (21.0%) met the primary outcome; 257 participants comprised the development cohort, and 166 comprised the validation cohort. The 3 models containing NLR, suPAR, or IL-6 demonstrated promising discrimination (c-statistics: 0.72-0.74) and calibration (calibration slopes: 1.01-1.05) in the validation cohort and provided greater utility than a model containing the clinical parameters alone. CONCLUSIONS: We present 3 clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources.

Combining simple blood tests to identify primary care patients with unexpected weight loss for cancer investigation: Clinical risk score development, internal validation, and net benefit analysis.

BACKGROUND: Unexpected weight loss (UWL) is a presenting feature of cancer in primary care. Existing research proposes simple combinations of clinical features (risk factors, symptoms, signs, and blood test data) that, when present, warrant cancer investigation. More complex combinations may modify cancer risk to sufficiently rule-out the need for investigation. We aimed to identify which clinical features can be used together to stratify patients with UWL based on their risk of cancer. METHODS AND FINDINGS: We used data from 63,973 adults (age: mean 59 years, standard deviation 21 years; 42% male) to predict cancer in patients with UWL recorded in a large representative United Kingdom primary care electronic health record between January 1, 2000 and December 31, 2012. We derived 3 clinical prediction models using logistic regression and backwards stepwise covariate selection: Sm, symptoms-only model; STm, symptoms and tests model; Tm, tests-only model. Fifty imputations replaced missing data. Estimates of discrimination and calibration were derived using 10-fold internal cross-validation. Simple clinical risk scores are presented for models with the greatest clinical utility in decision curve analysis. The STm and Tm showed improved discrimination (area under the curve ≥ 0.91), calibration, and greater clinical utility than the Sm. The Tm was simplest including age-group, sex, albumin, alkaline phosphatase, liver enzymes, C-reactive protein, haemoglobin, platelets, and total white cell count. A Tm score of 5 balanced ruling-in (sensitivity 84.0%, positive likelihood ratio 5.36) and ruling-out (specificity 84.3%, negative likelihood ratio 0.19) further cancer investigation. A Tm score of 1 prioritised ruling-out (sensitivity 97.5%). At this threshold, 35 people presenting with UWL in primary care would be referred for investigation for each person with cancer referred, and 1,730 people would be spared referral for each person with cancer not referred. Study limitations include using a retrospective routinely collected dataset, a reliance on coding to identify UWL, and missing data for some predictors. CONCLUSIONS: Our findings suggest that combinations of simple blood test abnormalities could be used to identify patients with UWL who warrant referral for investigation, while people with combinations of normal results could be exempted from referral.

The association between unexpected weight loss and cancer diagnosis in primary care: a matched cohort analysis of 65,000 presentations.

BACKGROUND: We aimed to understand the time period of cancer diagnosis and the cancer types detected in primary care patients with unexpected weight loss (UWL) to inform cancer guidelines. METHODS: This retrospective matched cohort study used cancer registry linked electronic health records from the UK's Clinical Practice Research Datalink from between 2000 and 2014. Univariable and multivariable time-to-event analyses examined the association between UWL, and all cancers combined, cancer site and stage. RESULTS: In all, 63,973 patients had UWL recorded, of whom 1375 (2.2%) were diagnosed with cancer within 2 years (days-to-diagnosis: mean 181; median 80). Men with UWL (HR 3.28 (2.88-3.73)) and women (1.87 (1.68-2.08)) were more likely than comparators to be diagnosed with cancer within 3 months. The association was greatest in men aged ≥50 years and women ≥70 years. The commonest cancers were pancreas, cancer of unknown primary, gastro-oesophageal, lymphoma, hepatobiliary, lung, bowel and renal-tract. The majority were late-stage, but there was some evidence of association with stage II and stage III cancers. In the 3-24 months after presenting with UWL, cancer diagnosis was less likely than in comparators. CONCLUSION: UWL recorded in primary care is associated with a broad range of cancer sites of early and late-stage.

Factors associated with the prescribing of high-dose opioids in primary care: a systematic review and meta-analysis.

BACKGROUND: The risks of harms from opioids increase substantially at high doses, and high-dose prescribing has increased in primary care. However, little is known about what leads to high-dose prescribing, and studies exploring this have not been synthesized. We, therefore, systematically synthesized factors associated with the prescribing of high-dose opioids in primary care. METHODS: We conducted a systematic review of observational studies in high-income countries that used patient-level primary care data and explored any factor(s) in people for whom opioids were prescribed, stratified by oral morphine equivalents (OME). We defined high doses as ≥ 90 OME mg/day. We searched MEDLINE, Embase, Web of Science, reference lists, forward citations, and conference proceedings from database inception to 5 April 2019. Two investigators independently screened studies, extracted data, and appraised the quality of included studies using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. We pooled data on factors using random effects meta-analyses and reported relative risks (RR) or mean differences with 95% confidence intervals (CI) where appropriate. We also performed a number needed to harm (NNTH) calculation on factors when applicable. RESULTS: We included six studies with a total of 4,248,119 participants taking opioids, of whom 3.64% (n = 154,749) were taking high doses. The majority of included studies (n = 4) were conducted in the USA, one in Australia and one in the UK. The largest study (n = 4,046,275) was from the USA. Included studies were graded as having fair to good quality evidence. The co-prescription of benzodiazepines (RR 3.27, 95% CI 1.32 to 8.13, I2 = 99.9%), depression (RR 1.38, 95% CI 1.27 to 1.51, I2 = 0%), emergency department visits (RR 1.53, 95% CI 1.46 to 1.61, I2 = 0%, NNTH 15, 95% CI 12 to 20), unemployment (RR 1.44, 95% CI 1.27 to 1.63, I2 = 0%), and male gender (RR 1.21, 95% CI 1.14 to 1.28, I2 = 78.6%) were significantly associated with the prescribing of high-dose opioids in primary care. CONCLUSIONS: High doses of opioids are associated with greater risks of harms. Associated factors such as the co-prescription of benzodiazepines and depression identify priority areas that should be considered when selecting, identifying, and managing people taking high-dose opioids in primary care. Coordinated strategies and services that promote the safe prescribing of opioids are needed. STUDY REGISTRATION: PROSPERO, CRD42018088057.

Biomarkers for diagnosing serious bacterial infections in older outpatients: a systematic review.

BACKGROUND: The value of biomarkers for diagnosing bacterial infections in older outpatients is uncertain and limited official guidance exists for clinicians in this area. The aim of this review is to critically appraise and evaluate biomarkers for diagnosing bacterial infections in older adults (aged 65 years and above). METHODS: We searched Medline, Embase, Web of Science and the Cochrane Library, from inception to January 2018. We included studies assessing the diagnostic accuracy of blood, urinary, and salivary biomarkers in diagnosing bacterial infections in older adults. The QUADAS-2 tool was used to assess study quality. RESULTS: We identified 11 eligible studies of moderate quality (11,034 participants) including 51 biomarkers at varying thresholds for diagnosing bacterial infections. An elevated Procalcitonin (≥ 0.2 ng/mL) may help diagnose bacteraemia in older adults [+ve LR range 1.50 to 2.60]. A CRP ≥ 50 mg/L only raises the probability of bacteraemia by 5%. A positive urine dipstick aids diagnosis of UTI (+ve LR range 1.23 to 54.90), and absence helps rule out UTI (-ve LR range 0.06 to 0.46). An elevated white blood cell count is unhelpful in diagnosing intra-abdominal infections (+ve LR range 0.75 to 2.62), but may aid differentiation of bacterial infection from other acute illness (+ve LR range 2.14 to 7.12). CONCLUSIONS: The limited available evidence suggests that many diagnostic tests useful in younger patients, do not help to diagnose bacterial infections in older adults. Further evidence from high quality studies is urgently needed to guide clinical practice. Until then, symptoms and signs remain the mainstay of diagnosis in community based populations.