Interventions for Optimization of Guideline-Directed Medical Therapy: A Systematic Review.

Importance: Implementation of guideline-directed medical therapy (GDMT) in real-world practice remains suboptimal. It is unclear which interventions are most effective at addressing current barriers to GDMT in patients with heart failure with reduced ejection fraction (HFrEF). Objective: To perform a systematic review to identify which types of system-level initiatives are most effective at improving GDMT use among patients with HFrEF. Evidence Review: PubMed, Embase, Cochrane, CINAHL, and Web of Science databases were queried from January 2010 to November 2023 for randomized clinical trials that implemented a quality improvement intervention with GDMT use as a primary or secondary outcome. References from related review articles were also included for screening. Quality of studies and bias assessment were graded based on the Cochrane Risk of Bias tool and Oxford Centre for Evidence-Based Medicine. Findings: Twenty-eight randomized clinical trials were included with an aggregate sample size of 19 840 patients. Studies were broadly categorized as interdisciplinary interventions (n = 15), clinician education (n = 5), electronic health record initiatives (n = 6), or patient education (n = 2). Overall, interdisciplinary titration clinics were associated with significant increases in the proportion of patients on target doses of GDMT with a 10% to 60% and 2% to 53% greater proportion of patients on target doses of ß-blockers and renin-angiotensin-aldosterone system inhibitors, respectively, in intervention groups compared with usual care. Other interventions, such as audits, clinician and patient education, or electronic health record alerts, were also associated with some improvements in GDMT utilization, though these findings were inconsistent across studies. Conclusions and Relevance: This review summarizes interventions aimed at optimization of GDMT in clinical practice. Initiatives that used interdisciplinary teams, largely comprised of nurses and pharmacists, most consistently led to improvements in GDMT. Additional large, randomized studies are necessary to better understand other types of interventions, as well as their long-term efficacy and sustainability.

Non-Dipping Blood Pressure or Nocturnal Hypertension: Does One Matter More?

PURPOSE OF REVIEW: Nocturnal hypertension and non-dipping are both associated with increased cardiovascular risk; however, debate remains over which is a better prognosticator of cardiovascular outcomes. This review explores current literature on nocturnal hypertension and non-dipping to assess their relationship to cardiovascular disease and implications for clinical practice. RECENT FINDINGS: While current data remain inconclusive, some suggest that nocturnal hypertension is a more reliable and clinically significant marker of cardiovascular risk than non-dipping status. Importantly, reducing nocturnal HTN and non-dipping through chronotherapy, specifically evening dosing of antihypertensives, has not been conclusively shown to provide long-term cardiovascular benefits. Recent data suggests that non-dipping, compared to nocturnal hypertension, may be falling out of favor as a prognostic indicator for adverse cardiovascular outcomes. However, additional information is needed to understand how aberrant nighttime blood pressure patterns modulate cardiovascular risk to guide clinical management.

Longitudinal changes in co-involved drugs, comorbidities, and demographics of methamphetamine-related deaths in Los Angeles County.

INTRODUCTION: We conducted a population-based observational study of all medical examiner cases in Los Angeles County from January 2012 through June 2021 in which methamphetamine was listed as a cause of or contributing factor to death (n = 6125). We aimed to characterize demographics, comorbidities, and co-involved substances in methamphetamine-related deaths longitudinally in Los Angeles County, California. METHODS: We used detailed death record data to manually classify fatalities by involvement of each organ system, opioids, alcohol, cocaine, other drugs or medications, and external/traumatic causes. Primary outcomes included: the number of methamphetamine-involved deaths, demographics of decedents, percentage of methamphetamine deaths also involving other drugs, and percentage of methamphetamine deaths involving different organ systems. We performed Mann Kendall tests of trends to identify statistically significant longitudinal changes. RESULTS: During the study period, the percentage of methamphetamine-related deaths involving opioids significantly increased from 16 % in 2012 to 54 % in 2021 (p < 0.001). Concurrently, the percentage involving cardiovascular causes significantly decreased from 47 % to 26 % (p < 0.05). Methamphetamine-related deaths in LAC increasingly affected people experiencing homelessness, for whom the percentage tripled from 13 % in 2012 to 35 % in 2021. The share of decedents under 40 years old increased from 33 % to 41 %. The percentage of Black or African American decedents increased over five-fold from 3 % to 17 %. CONCLUSIONS: Methamphetamine-related deaths involving opioids more than tripled in Los Angeles County from 2012 to 2021, reflecting the drug supply's shift to illicit fentanyl. More than a quarter involved cardiovascular causes. These findings have implications for treatment and prevention, including scaling up contingency management, distributing naloxone to people who primarily use stimulants, and including cardiovascular care alongside these interventions directly targeted to reduce harms of methamphetamine use.

Serological response to vaccination in post-acute sequelae of COVID.

BACKGROUND: Individuals with post-acute sequelae of COVID (PASC) may have a persistence in immune activation that differentiates them from individuals who have recovered from COVID without clinical sequelae. To investigate how humoral immune activation may vary in this regard, we compared patterns of vaccine-provoked serological response in patients with PASC compared to individuals recovered from prior COVID without PASC. METHODS: We prospectively studied 245 adults clinically diagnosed with PASC and 86 adults successfully recovered from prior COVID. All participants had measures of humoral immunity to SARS-CoV-2 assayed before or after receiving their first-ever administration of COVID vaccination (either single-dose or two-dose regimen), including anti-spike (IgG-S and IgM-S) and anti-nucleocapsid (IgG-N) antibodies as well as IgG-S angiotensin-converting enzyme 2 (ACE2) binding levels. We used unadjusted and multivariable-adjusted regression analyses to examine the association of PASC compared to COVID-recovered status with post-vaccination measures of humoral immunity. RESULTS: Individuals with PASC mounted consistently higher post-vaccination IgG-S antibody levels when compared to COVID-recovered (median log IgG-S 3.98 versus 3.74, P < 0.001), with similar results seen for ACE2 binding levels (median 99.1 versus 98.2, P = 0.044). The post-vaccination IgM-S response in PASC was attenuated but persistently unchanged over time (P = 0.33), compared to in COVID recovery wherein the IgM-S response expectedly decreased over time (P = 0.002). Findings remained consistent when accounting for demographic and clinical variables including indices of index infection severity and comorbidity burden. CONCLUSION: We found evidence of aberrant immune response distinguishing PASC from recovered COVID. This aberrancy is marked by excess IgG-S activation and ACE2 binding along with findings consistent with a delayed or dysfunctional immunoglobulin class switching, all of which is unmasked by vaccine provocation. These results suggest that measures of aberrant immune response may offer promise as tools for diagnosing and distinguishing PASC from non-PASC phenotypes, in addition to serving as potential targets for intervention.

Natural Language Processing and Machine Learning to Identify People Who Inject Drugs in Electronic Health Records.

Background: Improving the identification of people who inject drugs (PWID) in electronic medical records can improve clinical decision making, risk assessment and mitigation, and health service research. Identification of PWID currently consists of heterogeneous, nonspecific International Classification of Diseases (ICD) codes as proxies. Natural language processing (NLP) and machine learning (ML) methods may have better diagnostic metrics than nonspecific ICD codes for identifying PWID. Methods: We manually reviewed 1000 records of patients diagnosed with Staphylococcus aureus bacteremia admitted to Veterans Health Administration hospitals from 2003 through 2014. The manual review was the reference standard. We developed and trained NLP/ML algorithms with and without regular expression filters for negation (NegEx) and compared these with 11 proxy combinations of ICD codes to identify PWID. Data were split 70% for training and 30% for testing. We calculated diagnostic metrics and estimated 95% confidence intervals (CIs) by bootstrapping the hold-out test set. Best models were determined by best F-score, a summary of sensitivity and positive predictive value. Results: Random forest with and without NegEx were the best-performing NLP/ML algorithms in the training set. Random forest with NegEx outperformed all ICD-based algorithms. F-score for the best NLP/ML algorithm was 0.905 (95% CI, .786-.967) and 0.592 (95% CI, .550-.632) for the best ICD-based algorithm. The NLP/ML algorithm had a sensitivity of 92.6% and specificity of 95.4%. Conclusions: NLP/ML outperformed ICD-based coding algorithms at identifying PWID in electronic health records. NLP/ML models should be considered in identifying cohorts of PWID to improve clinical decision making, health services research, and administrative surveillance.

Development and Validation of Machine Models Using Natural Language Processing to Classify Substances Involved in Overdose Deaths.

Importance: Overdose is one of the leading causes of death in the US; however, surveillance data lag considerably from medical examiner determination of the death to reporting in national surveillance reports. Objective: To automate the classification of deaths related to substances in medical examiner data using natural language processing (NLP) and machine learning (ML). Design, Setting, and Participants: Diagnostic study comparing different natural language processing and machine learning algorithms to identify substances related to overdose in 10 health jurisdictions in the US from January 1, 2020, to December 31, 2020. Unstructured text from 35 433 medical examiner and coroners' death records was examined. Exposures: Text from each case was manually classified to a substance that was related to the death. Three feature representation methods were used and compared: text frequency-inverse document frequency (TF-IDF), global vectors for word representations (GloVe), and concept unique identifier (CUI) embeddings. Several ML algorithms were trained and best models were selected based on F-scores. The best models were tested on a hold-out test set and results were reported with 95% CIs. Main Outcomes and Measures: Text data from death certificates were classified as any opioid, fentanyl, alcohol, cocaine, methamphetamine, heroin, prescription opioid, and an aggregate of other substances. Diagnostic metrics and 95% CIs were calculated for each combination of feature extraction method and machine learning classifier. Results: Of 35 433 death records analyzed (decedent median age, 58 years [IQR, 41-72 years]; 24 449 [69%] were male), the most common substances related to deaths included any opioid (5739 [16%]), fentanyl (4758 [13%]), alcohol (2866 [8%]), cocaine (2247 [6%]), methamphetamine (1876 [5%]), heroin (1613 [5%]), prescription opioids (1197 [3%]), and any benzodiazepine (1076 [3%]). The CUI embeddings had similar or better diagnostic metrics compared with word embeddings and TF-IDF for all substances except alcohol. ML classifiers had perfect or near perfect performance in classifying deaths related to any opioids, heroin, fentanyl, prescription opioids, methamphetamine, cocaine, and alcohol. Classification of benzodiazepines was suboptimal using all 3 feature extraction methods. Conclusions and Relevance: In this diagnostic study, NLP/ML algorithms demonstrated excellent diagnostic performance at classifying substances related to overdoses. These algorithms should be integrated into workflows to decrease the lag time in reporting overdose surveillance data.

Awareness of SARS-CoV-2 Omicron Variant Infection Among Adults With Recent COVID-19 Seropositivity.

Importance: Some individuals who were infected by the SARS-CoV-2 Omicron variant may have been completely unaware of their infectious status while the virus was actively transmissible. Objective: To examine awareness of infectious status among individuals during the recent Omicron variant surge in a diverse and populous urban region of Los Angeles County. Design, Setting, and Participants: This cohort study analyzed the records of adult employees and patients of an academic medical center who were enrolled in a longitudinal COVID-19 serological study in Los Angeles County, California. These participants had 2 or more serial anti-nucleocapsid IgG (IgG-N) antibody measurements at least 1 month apart, with the first occurring after the end of a regional Delta variant surge (September 15, 2021) and a subsequent one occurring after the start of a regional Omicron variant surge (December 15, 2021). Adults with evidence of new SARS-CoV-2 infection occurring during the Omicron variant surge period through May 4, 2022, were included in the present study sample. Exposures: Recent Omicron variant infection as evidenced by SARS-CoV-2 seroconversion. Main Outcomes and Measures: Awareness of recent SARS-CoV-2 infection was ascertained from review of self-reported health updates, medical records, and COVID-19 testing data. Results: Of the 210 participants (median [range] age, 51 (23-84) years; 136 women [65%]) with serological evidence of recent Omicron variant infection, 44% (92) demonstrated awareness of any recent Omicron variant infection and 56% (118) reported being unaware of their infectious status. Among those who were unaware, 10% (12 of 118) reported having had any symptoms, which they attributed to a common cold or other non-SARS-CoV-2 infection. In multivariable analyses that accounted for demographic and clinical characteristics, participants who were health care employees of the medical center were more likely than nonemployees to be aware of their recent Omicron variant infection (adjusted odds ratio, 2.46; 95% CI, 1.30-4.65). Conclusions and Relevance: Results of this study suggest that more than half of adults with recent Omicron variant infection were unaware of their infectious status and that awareness was higher among health care employees than nonemployees, yet still low overall. Unawareness may be a highly prevalent factor associated with rapid person-to-person transmission within communities.

Selecting deep neural networks that yield consistent attribution-based interpretations for genomics.

Deep neural networks (DNNs) have advanced our ability to take DNA primary sequence as input and predict a myriad of molecular activities measured via high-throughput functional genomic assays. Post hoc attribution analysis has been employed to provide insights into the importance of features learned by DNNs, often revealing patterns such as sequence motifs. However, attribution maps typically harbor spurious importance scores to an extent that varies from model to model, even for DNNs whose predictions generalize well. Thus, the standard approach for model selection, which relies on performance of a held-out validation set, does not guarantee that a high-performing DNN will provide reliable explanations. Here we introduce two approaches that quantify the consistency of important features across a population of attribution maps; consistency reflects a qualitative property of human interpretable attribution maps. We employ the consistency metrics as part of a multivariate model selection framework to identify models that yield high generalization performance and interpretable attribution analysis. We demonstrate the efficacy of this approach across various DNNs quantitatively with synthetic data and qualitatively with chromatin accessibility data.

Perioperative and Long-Term Outcomes of Robot-Assisted Partial Nephrectomy: A Systematic Review.

BACKGROUND: Adoption of the robotic surgical platform for small renal cancers has rapidly expanded, but its utility compared to other approaches has not been established. The objective of this review is to assess perioperative and long-term oncologic and functional outcomes of robot-assisted partial nephrectomy (RAPN) compared to laparoscopic partial nephrectomy (LPN) and open partial nephrectomy (OPN). METHODS: A search in PubMed, Embase, and Cochrane (2010-2019) was conducted. Of 3877 articles screened, 7 observational studies were included. RESULTS: RAPN was associated with 24-50 mL less intraoperative blood loss compared to LPN and 39-84 mL less than OPN. RAPN also demonstrated trends of other postoperative benefits, such as shorter length of stay and fewer major complications. Several studies reported better long-term functional kidney outcomes, but these findings were inconsistent. Recurrence and cancer-specific survival (CSS) were similar across groups. While RAPN had a 5-year CSS of 90.1%-97.9%, LPN and OPN had survival rates of 85.9%-86.9% and 88.5-96.3% respectively. CONCLUSIONS: RAPN may be associated with a lower estimated blood loss and comparable long-term outcomes when compared to other surgical approaches. However, additional randomized or propensity matched studies are warranted to fully assess long-term functional kidney and oncologic outcomes.

Association of implicit intensity values incorporated into work RVUs with objective measures.

BACKGROUND: The "intensity" of a surgical procedure is supposed to be incorporated into work RVUs to allow higher compensation rates for more complex procedures. However, updates to work RVUs are subjective and it is unclear if these intensity values correlate to objective measures of a procedure's complexity. METHODS: Centers for Medicare and Medicaid Services (CMS) data were used to calculate intraservice intensity values for CPT codes in 2017 ("CMS intensity values"). Twenty-six objective measures- spanning patient, case, and risk characteristics - were generated using the 2017 participant use file from NSQIP. CMS intensity values were compared to objective measures using scatterplots and correlations. RESULTS: Among 473 CPT codes, CMS intensity values ranged from 0.0031 to 0.142 work RVUs/minute. CMS intensity values were positively associated with 3 objective measures, negatively associated with 5 measures, and not associated with the remaining 18 measures. CONCLUSIONS: Despite intensity values - and therefore compensation rates - varying over 40-fold in the wRVU scale, there was generally no association between their magnitude and objective measures of surgical intensity.

Surgeon work captured by the National Surgical Quality Improvement Program across specialties.

BACKGROUND: The National Surgical Quality Improvement Program (NSQIP) database is increasingly used for surgical research. However, it is unclear how well this database represents the breadth of work performed by different specialties. METHODS: Using the 2017 NSQIP participant use file and the 2017 Medicare Physician/Supplier Procedure Summary file, we evaluated (1) what proportion of surgical work is captured by NSQIP, (2) what procedures and disciplines are undersampled, and (3) the overall concordance between the NSQIP sample and a national sample. RESULTS: The NSQIP database reported at least one case for 4,463 out of the 5,272 Current Procedures Terminology codes in the Medicare file, potentially capturing 97.8% of surgical work across all 10 specialties. However, this proportion decreased to 72.1% when only procedures with at least 100 cases in NSQIP were considered. Limiting our analysis to only those procedures with 100 cases had markedly different effects by specialty. In part, this was owing to undersampling of minor procedures, which are more common in disciplines such as otolaryngology and urology. The overall association between the size of the NSQIP sample and the Medicare sample was 0.08. CONCLUSION: Although NSQIP has the potential to capture a diverse surgical caseload, some specialties and procedures are undersampled, limiting the ability for NSQIP to generate valid benchmarks. There was little correlation between the sample sizes in NSQIP and a national sample. Increasing sampling of underrepresented procedures and developing weights to scale NSQIP to a national sample would strengthen the program's ability to inform health outcomes research and provide valid comparisons across procedures and specialties.

Effects of Branched-Chain Amino Acid Supplementation on Spontaneous Seizures and Neuronal Viability in a Model of Mesial Temporal Lobe Epilepsy.

BACKGROUND: The essential branched-chain amino acids (BCAAs) leucine, isoleucine, and valine have recently emerged as a potential novel treatment for medically refractory epilepsy. Blood-derived BCAAs can readily enter the brain, where they contribute to glutamate biosynthesis and may either suppress or trigger acute seizures. However, the effects of BCAAs on chronic (ie, spontaneous recurrent) seizures and epilepsy-associated neuron loss are incompletely understood. MATERIALS AND METHODS: Sixteen rats with mesial temporal lobe epilepsy were randomized into 2 groups that could drink, ad libitum, either a 4% solution of BCAAs in water (n=8) or pure water (n=8). The frequency and relative percent of convulsive and nonconvulsive spontaneous seizures were monitored for a period of 21 days, and the brains were then harvested for immunohistochemical analysis. RESULTS: Although the frequency of convulsive and nonconvulsive spontaneous recurrent seizures over a 3-week drinking/monitoring period were not different between the groups, there were differences in the relative percent of convulsive seizures in the first and third week of treatment. Moreover, the BCAA-treated rats had over 25% fewer neurons in the dentate hilus of the hippocampus compared with water-treated controls. CONCLUSIONS: Acute BCAA supplementation reduces seizure propagation, whereas chronic oral supplementation with BCAAs worsens seizure propagation and causes neuron loss in rodents with mesial temporal lobe epilepsy. These findings raise the question of whether such supplementation has a similar effect in humans.

BK viremia is not associated with adverse outcomes in the absence of BK nephropathy.

There are limited data regarding the association of different levels of BK viremia and BK nephropathy (BKN), and graft outcomes. We studied the BK plasma PCR levels of all kidney transplant recipients (KTR) transplanted at our institution between 01/01/2006 and 06/30/2014. Patients were divided into groups based on their highest BK plasma PCR level within the first year following transplantation: undetectable, low (<1000 copies/mL), moderate (1000-10 000 copies/mL), high (>10 000-100 000 copies/mL), very high (>100 000 copies/mL), and those that had biopsy-proven BKN. There were a total of 1146 KTR during the study period: 813 with undetectable BK levels and 333 with any detectable BK level (87 with low, 79 with moderate, 88 with high, 34 with very high level BK, and 45 that had BKN). Compared to KTR with an undetectable BK level, incidence of mortality, graft failure, rejections,and infections were not significantly different for those with low, moderate, high, or very high BK level. Patients with BKN had a higher rate of infection and higher rates of total graft failure or death-censored graft failure compared to those with undetectable BK levels. BK viremia in the absence of BKN does not significantly increase the risk of rejection, infections, or graft failure compared to an undetectable BK level.

Dietary Behaviors and Caregiver Perceptions of Overweight and Obesity among Chinese Preschool Children.

Introduction: Early childhood obesity in China has become a pressing public health concern. A substantial barrier to healthy weight management is poor parental recognition of child overweight. This study examined the relationship between caregiver perceptions of child weight and dietary practices. Methods: A total of 364 children between 2 and 6 years old from six urban preschools in Changsha (China) were included in a cross-sectional study. Information on household demographics, health behaviors, and caregiver attitudes was collected through a self-administered caregiver questionnaire. Chi-squared tests, t-tests, and multivariable logistic regression analysis were used to determine the relationship between caregiver perceptions, dietary behaviors, and child weight status. Results: Over 60% of caregivers with overweight/obese children underestimated their children's weight status. These caregivers were less likely to worry about weight and restrict their children's dietary intakes. Children of caregivers who incorrectly classified their weights were also more likely to have a poor appetite. Caregivers of male children and those from families with incomes between 7000 and 11,000 Ren Min Bi (RMB) were more likely to underestimate weight compared to caregivers with daughters and those from higher income households. Conclusions: Although accurate weight perception may be important for motivating healthy behavioral changes, it may also lead to greater restriction of children's diets, which has been linked to long-term weight gain. Interventions to improve awareness of child overweight should be coupled with efforts that teach caregivers about healthy weight management strategies.

The Relationship between Obesity, Sleep and Physical Activity in Chinese Preschool Children.

BACKGROUND: Pediatric overweight and obesity has become a major public health problem in China. The goal of this study is to understand overweight and obesity in preschool children in Changsha City in the context of their sleep and physical activity. These results offer feasible proposals to reduce levels of overweight and obesity among preschool children. METHODS: A total of 112 preschoolers aged three to six years old were investigated using multiple stage stratified cluster sampling and simple random sampling. Questionnaires were used to collect general information about children and their families. Body mass index (BMI) was used as an indicator of overweight and obesity. Age- and sex-specific cutoff values for Chinese children and adolescents were used to determine child weight status. Children's sedentary time was reported by caregivers, while physical activity and sleep were recorded using fitness bracelets (Misfit Shine 2). RESULTS: The prevalence of childhood overweight and obesity were 15.2% and 9.8% respectively. Preschool-aged children travelled 11,111 ± 3357 and 10,350 ± 2973 steps per day on weekdays and weekends respectively. The number of daily steps was not statistically different between weekdays and weekends. The amount of time spent daily doing vigorous activity on weekdays and weekends was significantly different, with an average time of 20.5 ± 31.6 min and 10.3 ± 15.3 min respectively (p = 0.002). Furthermore, 10.7% and 50.9% of children used screens for more than two hours on weekdays and weekends respectively (p < 0.001). Children slept for significantly longer on weekends (8.3 ± 0.9 h) than on weekdays (8.1 ± 0.7 h) (p = 0.037). A significantly higher proportion of students also fell asleep before 10:00 p.m. on weekends (26.8%) compared to weekdays (15.2%) (p < 0.001). Parent's BMI values were positively correlated with child BMI, the monthly household income was negatively associated with child BMI. Male children were more likely to have a higher BMI than female children. Children who were obese were also more likely to have shorter sleep times compared to children of normal weight (p = 0.047). CONCLUSIONS: There was a high prevalence of overweight and obesity among the Chinese preschool children in this study. Students also demonstrated poor sleep and physical activity habits. Future research is necessary to explore the relationship between sleep, physical activity and weight status for young children in China.

Study on the Status of Health Service Utilization among Caregivers of Left-Behind Children in Poor Rural Areas of Hunan Province: A Baseline Survey.

BACKGROUND: The caregivers of left-behind children (CLBC) in China's poor, rural areas are mostly elderly and women. Their health status and access to health services have not been previously characterized. This study aims to explore the status of CLBC in terms of their health service utilization and to provide a scientific basis for guiding effective implementation of health policy in rural Hunan. METHODS: Random cluster sampling was used to survey CLBC in two rural counties. Face-to-face interviews and questionnaires were used to collect data, including socioeconomic status and health service utilization. The two-week prevalence rate was used to reflect health service needs, while the two-week visiting rate, annual hospitalization rate and participation in basic public health services were used to evaluate health service utilization. RESULTS: Of the 518 respondents in the study, 95.9% were farmers and 88.4% were over 40 years old. The two-week prevalence rate was 36.1%. Furthermore, 40.1% of ill caregivers' activities were partly restricted by illness and 3.7% needed to be on bed rest. The two-week visiting rate was 21.0%. The main reasons for not seeing a doctor were "self-medication" (39.1%) or "financial difficulties" (32.6%). The annual hospitalization rate of the CLBC was 22.6% and the non-hospitalization rate of those who needed hospitalization was 41.5%. "Lack of time" (22.3%) and "financial difficulties" (50.5%) were the major factors affecting the utilization of hospitalization services. In terms of participation in basic public health services, only 35.1% CLBC clearly knew that township hospitals have established health records for them. Only 50.6% of caregivers received free health examinations in village clinics or township hospitals and 81.3% of the caregivers did not participate in health education or lectures organized by local health institutions in 2014. CONCLUSIONS: The utilization rate of health services was extremely low, which may affect the quality of care for left-behind children. Better public health education through multi-sector cooperation is urgently needed to improve health cognition among CLBC in rural China.

Effectiveness of UNAIDS targets and HIV vaccination across 127 countries.

The HIV pandemic continues to impose enormous morbidity, mortality, and economic burdens across the globe. Simultaneously, innovations in antiretroviral therapy, diagnostic approaches, and vaccine development are providing novel tools for treatment-as-prevention and prophylaxis. We developed a mathematical model to evaluate the added benefit of an HIV vaccine in the context of goals to increase rates of diagnosis, treatment, and viral suppression in 127 countries. Under status quo interventions, we predict a median of 49 million [first and third quartiles 44M, 58M] incident cases globally from 2015 to 2035. Achieving the Joint United Nations Program on HIV/AIDS 95-95-95 target was estimated to avert 25 million [20M, 33M] of these new infections, and an additional 6.3 million [4.8M, 8.7M] reduction was projected with the 2020 introduction of a 50%-efficacy vaccine gradually scaled up to 70% coverage. This added benefit of prevention through vaccination motivates imminent and ongoing clinical trials of viable candidates to realize the goal of HIV control.