Assessment and Lifestyle Management of Patients With Obesity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
IMPORTANCE: Even though one-third of US adults are obese, identification and treatment rates for obesity remain low. Clinician engagement is vital to provide guidance and assistance to patients who are overweight or obese to address the underlying cause of many chronic diseases. OBJECTIVES: To describe current best practices for assessment and lifestyle management of obesity and to demonstrate how the updated Guidelines (2013) for Managing Overweight and Obesity in Adults based on a systematic evidence review sponsored by the National Heart, Lung, and Blood Institute (NHLBI) can be applied to an individual patient. EVIDENCE REVIEW: Systematic evidence review conducted for the Guidelines (2013) for Managing Overweight and Obesity in Adults supports treatment recommendations in 5 areas (risk assessment, weight loss benefits, diets for weight loss, comprehensive lifestyle intervention approaches, and bariatric surgery); for areas outside this scope, recommendations are supported by other guidelines (for obesity, 1998 NHLBI-sponsored obesity guidelines and those from the National Center for Health and Clinical Excellence and Canadian and US professional societies such as the American Association of Clinical Endocrinologists and American Society of Bariatric Physicians; for physical activity recommendations, the 2008 Physical Activity Guidelines for Americans); a PubMed search identified recent systematic reviews covering depression and obesity, motivational interviewing for weight management, metabolic adaptation to weight loss, and obesity pharmacotherapy. FINDINGS: The first step in obesity management is to screen all adults for overweight and obesity. A medical history should be obtained assessing for the multiple determinants of obesity, including dietary and physical activity patterns, psychosocial factors, weight-gaining medications, and familial traits. Emphasis on the complications of obesity to identify patients who will benefit the most from treatment is more useful than using body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) alone for treatment decisions. The Guidelines (2013) recommend that clinicians offer patients who would benefit from weight loss (either BMI of ≥30 with or without comorbidities or ≥25 along with 1 comorbidity or risk factor) intensive, multicomponent behavioral intervention. Some clinicians do this within their primary care practices; others refer patients for these services. Weight loss is achieved by creating a negative energy balance through modification of food and physical activity behaviors. The Guidelines (2013) endorse comprehensive lifestyle treatment by intensive intervention. Treatment can be implemented either in a clinician's office or by referral to a registered dietitian or commercial weight loss program. Weight loss of 5% to 10% is the usual goal. It is not necessary for patients to attain a BMI of less than 25 to achieve a health benefit. CONCLUSIONS AND RELEVANCE: Screening and assessment of patients for obesity followed by initiation or referral of treatment should be incorporated into primary care practice settings. If clinicians can identify appropriate patients for weight loss efforts and provide informed advice and assistance on how to achieve and sustain modest weight loss, they will be addressing the underlying driver of many comorbidities and can have a major influence on patients' health status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it