IMPORTANCE: Recent discussion has focused on questions related to the repeal and replacement of portions of the Affordable Care Act (ACA). However, issues central to the future of health and health ...care in the United States transcend the ACA provisions receiving the greatest attention. Initiatives directed to certain strategic and infrastructure priorities are vital to achieve better health at lower cost. OBJECTIVES: To review the most salient health challenges and opportunities facing the United States, to identify practical and achievable priorities essential to health progress, and to present policy initiatives critical to the nation’s health and fiscal integrity. EVIDENCE REVIEW: Qualitative synthesis of 19 National Academy of Medicine–commissioned white papers, with supplemental review and analysis of publicly available data and published research findings. FINDINGS: The US health system faces major challenges. Health care costs remain high at $3.2 trillion spent annually, of which an estimated 30% is related to waste, inefficiencies, and excessive prices; health disparities are persistent and worsening; and the health and financial burdens of chronic illness and disability are straining families and communities. Concurrently, promising opportunities and knowledge to achieve change exist. Across the 19 discussion papers examined, 8 crosscutting policy directions were identified as vital to the nation’s health and fiscal future, including 4 action priorities and 4 essential infrastructure needs. The action priorities—pay for value, empower people, activate communities, and connect care—recurred across the articles as direct and strategic opportunities to advance a more efficient, equitable, and patient- and community-focused health system. The essential infrastructure needs—measure what matters most, modernize skills, accelerate real-world evidence, and advance science—were the most commonly cited foundational elements to ensure progress. CONCLUSIONS AND RELEVANCE: The action priorities and essential infrastructure needs represent major opportunities to improve health outcomes and increase efficiency and value in the health system. As the new US administration and Congress chart the future of health and health care for the United States, and as health leaders across the country contemplate future directions for their programs and initiatives, their leadership and strategic investment in these priorities will be essential for achieving significant progress.
The decline in CD4+ cells and increased viral DNA and RNA burden in the blood of human immunodeficiency virus (HIV)-infected individuals have been used as closely related correlates of disease ...progression. However, little is known about levels of total or unintegrated viral DNA in lymphoid tissue of HIV-infected patients and how they relate to CD4+ cell decline or disease progression. Exploiting the similarities between HIV- and simian immunodeficiency virus (SIV)-induced disease, we examined lymphoid organs and peripheral blood from SIV-infected macaques for total (pol) and unintegrated 2-LTR circular viral DNA by polymerase chain reaction (PCR). Two SIV isolates (SIVmac/251 and SIVmne/E11S) that differ markedly in their biological and clinical properties were studied. The results indicate that total viral DNA burdens vary considerably between isolates. There was no strong association between total viral DNA levels and CD4% in lymphoid tissues when isolates were compared and death was not associated with any particular level of viral pol DNA. In contrast, accumulation of unintegrated viral DNA was closely associated with decline in CD4/CD8 ratios in lymphoid organs and AIDS. The appearance of both pol and unintegrated viral DNA in thymus of infected macaques also emerged as one of the single best correlates or possible predictors of advanced disease yet studied. Their roles in pathogenesis are discussed.
Traces of life are nearly ubiquitous on Earth. However, a central unresolved question is whether these traces always indicate an active microbial community or whether, in extreme environments, such ...as hyperarid deserts, they instead reflect just dormant or dead cells. Although microbial biomass and diversity decrease with increasing aridity in the Atacama Desert, we provide multiple lines of evidence for the presence of an at times metabolically active, microbial community in one of the driest places on Earth. We base this observation on four major lines of evidence: (i) a physico-chemical characterization of the soil habitability after an exceptional rain event, (ii) identified biomolecules indicative of potentially active cells e.g., presence of ATP, phospholipid fatty acids (PLFAs), metabolites, and enzymatic activity, (iii) measurements of in situ replication rates of genomes of uncultivated bacteria reconstructed from selected samples, and (iv) microbial community patterns specific to soil parameters and depths. We infer that the microbial populations have undergone selection and adaptation in response to their specific soil microenvironment and in particular to the degree of aridity. Collectively, our results highlight that even the hyperarid Atacama Desert can provide a habitable environment for microorganisms that allows them to become metabolically active following an episodic increase in moisture and that once it decreases, so does the activity of the microbiota. These results have implications for the prospect of life on other planets such as Mars, which has transitioned from an earlier wetter environment to today’s extreme hyperaridity.
Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and ...diseases. Heritability of plasma cortisol is estimated at 30-60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.
Accurate prediction of dengue incidence levels weeks in advance of an outbreak may reduce the morbidity and mortality associated with this neglected disease. Therefore, models were developed to ...predict high and low dengue incidence in order to provide timely forewarnings in the Philippines.
Model inputs were chosen based on studies indicating variables that may impact dengue incidence. The method first uses Fuzzy Association Rule Mining techniques to extract association rules from these historical epidemiological, environmental, and socio-economic data, as well as climate data indicating future weather patterns. Selection criteria were used to choose a subset of these rules for a classifier, thereby generating a Prediction Model. The models predicted high or low incidence of dengue in a Philippines province four weeks in advance. The threshold between high and low was determined relative to historical incidence data.
Model accuracy is described by Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, and Specificity computed on test data not previously used to develop the model. Selecting a model using the F0.5 measure, which gives PPV more importance than Sensitivity, gave these results: PPV = 0.780, NPV = 0.938, Sensitivity = 0.547, Specificity = 0.978. Using the F3 measure, which gives Sensitivity more importance than PPV, the selected model had PPV = 0.778, NPV = 0.948, Sensitivity = 0.627, Specificity = 0.974. The decision as to which model has greater utility depends on how the predictions will be used in a particular situation.
This method builds prediction models for future dengue incidence in the Philippines and is capable of being modified for use in different situations; for diseases other than dengue; and for regions beyond the Philippines. The Philippines dengue prediction models predicted high or low incidence of dengue four weeks in advance of an outbreak with high accuracy, as measured by PPV, NPV, Sensitivity, and Specificity.
The RAINBOW randomized clinical trial validated the efficacy of an integrated collaborative care intervention for obesity and depression in primary care, although the effect was modest. To inform ...intervention optimization, this study investigated within-treatment variability in participant engagement and progress.
Data were collected in 2014-2017 and analyzed post hoc in 2018. Cluster analysis evaluated patterns of change in weekly self-monitored weight from week 6 up to week 52 and depression scores on the Patient Health Questionnaire-9 (PHQ-9) from up to 15 individual sessions during the 12-month intervention. Chi-square tests and ANOVA compared weight loss and depression outcomes objectively measured by blinded assessors to validate differences among categories of treatment engagement and progress defined based on cluster analysis results.
Among 204 intervention participants (50.9 SD, 12.2 years, 71% female, 72% non-Hispanic White, BMI 36.7 6.9, PHQ-9 14.1 3.2), 31% (n = 63) had poor engagement, on average completing self-monitored weight in <3 of 46 weeks and <5 of 15 sessions. Among them, 50 (79%) discontinued the intervention by session 6 (week 8). Engaged participants (n = 141; 69%) self-monitored weight for 11-22 weeks, attended almost all 15 sessions, but showed variable treatment progress based on patterns of change in self-monitored weight and PHQ-9 scores over 12 months. Three patterns of weight change (%) represented minimal weight loss (n = 50, linear β1 = -0.06, quadratic β2 = 0.001), moderate weight loss (n = 61, β1 = -0.28, β2 = 0.002), and substantial weight loss (n = 12, β1 = -0.53, β2 = 0.005). Three patterns of change in PHQ-9 scores represented moderate depression without treatment progress (n = 40, intercept β0 = 11.05, β1 = -0.11, β2 = 0.002), moderate depression with treatment progress (n = 20, β0 = 12.90, β1 = -0.42, β2 = 0.006), and milder depression with treatment progress (n = 81, β0 = 7.41, β1 = -0.23, β2 = 0.003). The patterns diverged within 6-8 weeks and persisted throughout the intervention. Objectively measured weight loss and depression outcomes were significantly worse among participants with poor engagement or poor progress on either weight or PHQ-9 than those showing progress on both.
Participants demonstrating poor engagement or poor progress could be identified early during the intervention and were more likely to fail treatment at the end of the intervention. This insight could inform individualized and timely optimization to enhance treatment efficacy.
ClinicalTrials.gov# NCT02246413.
Tropical forest degradation emits carbon at a rate of ∼0.5 Pg·y⁻¹, reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to ...managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 km·y⁻¹, and an inner wave of lower value charcoal production 2 km·y⁻¹. This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES carbon, 0.2 Mg·ha⁻¹; 0.1 species per sample area (0.4 ha). Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.
Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on‐ground conservation problems is still ...scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision‐making contexts when used within a structured and transparent decision‐making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision‐making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.
The Global Alignment and Proportion (GAP) score, based on pelvic incidence-based proportional parameters, was recently developed to predict mechanical complications after surgery for spinal ...deformities in adults. However, this score has not been validated in an independent external dataset.
After adult spinal deformity surgery, is a higher GAP score associated with (1) an increased risk of mechanical complications, defined as rod fractures, implant-related complications, proximal or distal junctional kyphosis or failure; (2) a higher likelihood of undergoing revision surgery to treat a mechanical complication; and (3) is a lower (more proportioned) GAP score category associated with better validated outcomes scores using the Oswestry Disability Index (ODI), Scoliosis Research Society-22 (SRS-22) and the Short Form-36 questionnaires?
A total of 272 patients who had undergone corrective surgeries for complex spinal deformities were enrolled in the Scoli-RISK-1 prospective trial. Patients were included in this secondary analysis if they fulfilled the original inclusion criteria by Yilgor et al. From the original 272 patients, 14% (39) did not satisfy the radiographic inclusion criteria, the GAP score could not be calculated in 14% (37), and 24% (64) did not have radiographic assessment at postoperative 2 years, leaving 59% (159) for analysis in this review of data from the original trial. A total of 159 patients were included in this study,with a mean age of 58 ± 14 years at the time of surgery. Most patients were female (72%, 115 of 159), the mean number of levels involved in surgery was 12 ± 4, and three-column osteotomy was performed in 76% (120 of 159) of patients. The GAP score was calculated using parameters from early postoperative radiographs (between 3 and 12 weeks) including pelvic incidence, sacral slope, lumbar lordosis, lower arc lordosis and global tilt, which were independently obtained from a computer software based on centralized patient radiographs. The GAP score was categorized as proportional (scores of 0 to 2), moderately disproportional (scores of 3 to 6), or severely disproportional (scores higher than 7 to 13). Receiver operating characteristic area under curve (AUC) was used to assess associations between GAP score and risk of mechanical complications and risk of revision surgery. An AUC of 0.5 to 0.7 was classified as "no or low associative power", 0.7 to 0.9 as "moderate" and greater than 0.9 as "high". We analyzed differences in validated outcome scores between the GAP categories using Wilcoxon rank sum test.
At a minimum of 2 years' follow-up, a higher GAP score was not associated with increased risks of mechanical complications (AUC = 0.60 95% CI 0.50 to 0.70). A higher GAP score was not associated with a higher likelihood of undergoing a revision surgery to treat a mechanical complication (AUC = 0.66 95% 0.53 to 0.78). However, a moderately disproportioned GAP score category was associated with better SF-36 physical component summary score (36 ± 10 versus 40 ± 11; p = 0.047), better SF-36 mental component summary score (46 ± 13 versus 51 ± 12; p = 0.01), better SRS-22 total score (3.4 ± 0.8 versus 3.7 ± 0.7, p = 0.02) and better ODI score (35 ± 21 versus 25 ± 20; p = 0.003) than severely disproportioned GAP score category.
Based on the findings of this external validation study, we found that alignment targets based on the GAP score alone were not associated with increased risks of mechanical complications and mechanical revisions in patients with complex adult spinal disorders. Parameters not included in the original GAP score needed to be considered to reduce the likelihood of mechanical complications.
Level III, diagnostic study.
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