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Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.
We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.
Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.
An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.
We present a timeseries of 14CO2 for the period 1910–2021 recorded by annual plants collected in the southwestern United States, centered near Flagstaff, Arizona. This timeseries is dominated by five commonly occurring annual plant species in the region, which is considered broadly representative of the southern Colorado Plateau. Most samples (1910–2015) were previously archived herbarium specimens, with additional samples harvested from field experiments in 2015–2021. We used this novel timeseries to develop a smoothed local record with uncertainties for “bomb spike” 14C dating of recent terrestrial organic matter. Our results highlight the potential importance of local records, as we document a delayed arrival of the 1963–1964 bomb spike peak, lower values in the 1980s, and elevated values in the last decade in comparison to the most current Northern Hemisphere Zone 2 record. It is impossible to retroactively collect atmospheric samples, but archived annual plants serve as faithful scribes: samples from herbaria around the Earth may be an under-utilized resource to improve understanding of the modern carbon cycle.
We examined the use of antibiotics for acute respiratory infections in an urgent-care setting.
Retrospective database review.
The study was conducted in 2 urgent-care clinics staffed by academic emergency physicians in San Diego, California.
Visits for acute respiratory infections were identified based on presenting complaints.
The primary outcome was a discharge prescription for an antibiotic. The patient and provider characteristics that predicted this outcome were analyzed using logistic regression. The variation in antibiotic prescriptions between providers was also analyzed.
In total, 15,160 visits were analyzed. The patient characteristics were not predictive of antibiotic treatment. Physicians were more likely than advanced practice practitioners to prescribe antibiotics (1.31; 95% confidence interval [CI], 1.21–1.42). For every year of seniority, a provider was 1.03 (95% CI, 1.02–1.03) more likely to prescribe an antibiotic. Although the providers saw similar patients, we detected significant variation in the antibiotic prescription rate between providers: the mean antibiotic prescription rate within the top quartile was 54.3% and the mean rate in the bottom quartile was 21.7%.
The patient and provider characteristics we examined were either not predictive or were only weakly predictive of receiving an antibiotic prescription for acute respiratory infection. However, we detected a marked variation between providers in the rate of antibiotic prescription. Provider differences, not patient differences, drive variations in antibiotic prescriptions. Stewardship efforts may be more effective if directed at providers rather than patients.
From 2016–2019, dry bulb onions were the suspected cause of three multistate outbreaks in the United States. We investigated a large multistate outbreak of Salmonella Newport infections that caused illnesses in both the United States and Canada in 2020. Epidemiologic, laboratory and traceback investigations were conducted to determine the source of the infections, and data were shared among U.S. and Canadian public health officials. We identified 1127 U.S. illnesses from 48 states with illness onset dates ranging from 19 June to 11 September 2020. Sixty-six per cent of ill people reported consuming red onions in the week before illness onset. Thirty-five illness sub-clusters were identified during the investigation and seventy-four per cent of sub-clusters served red onions to customers during the exposure period. Traceback for the source of onions in illness sub-clusters identified a common onion grower in Bakersfield, CA as the source of red onions, and onions were recalled at this time. Although other strains of Salmonella Newport were identified in environmental samples collected at the Bakersfield, CA grower, extensive environmental and product testing did not yield the outbreak strain. This was the third largest U.S. foodborne Salmonella outbreak in the last 30 years. It is the first U.S. multistate outbreak with a confirmed link to dry bulb onions, and it was nearly 10-fold larger than prior outbreaks with a suspected link to onions. This outbreak is notable for its size and scope, as well as the international data sharing that led to implication of red onions as the primary cause of the outbreak. Although an environmental assessment at the grower identified several factors that likely contributed to the outbreak, no main reason was identified. The expedient identification of the outbreak vehicle and response of multiple public health agencies allowed for recall and removal of product from the marketplace, and rapid messaging to both the public and industry on actions to protect consumers; these features contributed to a decrease in cases and expeditious conclusion of the outbreak.
We summarize what we assess as the past year's most important findings within climate change research: limits to adaptation, vulnerability hotspots, new threats coming from the climate–health nexus, climate (im)mobility and security, sustainable practices for land use and finance, losses and damages, inclusive societal climate decisions and ways to overcome structural barriers to accelerate mitigation and limit global warming to below 2°C.
We synthesize 10 topics within climate research where there have been significant advances or emerging scientific consensus since January 2021. The selection of these insights was based on input from an international open call with broad disciplinary scope. Findings concern: (1) new aspects of soft and hard limits to adaptation; (2) the emergence of regional vulnerability hotspots from climate impacts and human vulnerability; (3) new threats on the climate–health horizon – some involving plants and animals; (4) climate (im)mobility and the need for anticipatory action; (5) security and climate; (6) sustainable land management as a prerequisite to land-based solutions; (7) sustainable finance practices in the private sector and the need for political guidance; (8) the urgent planetary imperative for addressing losses and damages; (9) inclusive societal choices for climate-resilient development and (10) how to overcome barriers to accelerate mitigation and limit global warming to below 2°C.
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Science has evidence on barriers to mitigation and how to overcome them to avoid limits to adaptation across multiple fields.
To determine the proportion of hospitals that implemented 6 leading practices in their antimicrobial stewardship programs (ASPs). Design: Cross-sectional observational survey.
Advance letters and electronic questionnaires were initiated February 2020. Primary outcomes were percentage of hospitals that (1) implemented facility-specific treatment guidelines (FSTG); (2) performed interactive prospective audit and feedback (PAF) either face-to-face or by telephone; (3) optimized diagnostic testing; (4) measured antibiotic utilization; (5) measured C. difficile infection (CDI); and (6) measured adherence to FSTGs.
Of 948 hospitals invited, 288 (30.4%) completed the questionnaire. Among them, 82 (28.5%) had <99 beds, 162 (56.3%) had 100–399 beds, and 44 (15.2%) had ≥400+ beds. Also, 230 (79.9%) were healthcare system members. Moreover, 161 hospitals (54.8%) reported implementing FSTGs; 214 (72.4%) performed interactive PAF; 105 (34.9%) implemented procedures to optimize diagnostic testing; 235 (79.8%) measured antibiotic utilization; 258 (88.2%) measured CDI; and 110 (37.1%) measured FSTG adherence. Small hospitals performed less interactive PAF (61.0%; P = .0018). Small and nonsystem hospitals were less likely to optimize diagnostic testing: 25.2% (P = .030) and 21.0% (P = .0077), respectively. Small hospitals were less likely to measure antibiotic utilization (67.8%; P = .0010) and CDI (80.3%; P = .0038). Nonsystem hospitals were less likely to implement FSTGs (34.3%; P < .001).
Significant variation exists in the adoption of ASP leading practices. A minority of hospitals have taken action to optimize diagnostic testing and measure adherence to FSTGs. Additional efforts are needed to expand adoption of leading practices across all acute-care hospitals with the greatest need in smaller hospitals.
Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).
A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.
In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.
Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.
Background: Idiopathic Normal Pressure Hydrocephalus (iNPH) is a disorder of the elderly with progressive worsening of gait and balance, cognition, and urinary control which requires assessment using criteria recommended by International iNPH guidelines. Methods: Adult Hydrocephalus Clinical Research Network (AHCRN) prospective registry data from 5-centers over a 50-month interval included entry criteria; demographics; comorbidities; examination findings using standard AHCRN gait and neuropsychology assessments; shunt procedures, complications of CSF drainage, complications within 30 days of surgery, and 1-year postoperative follow-up. Results: 547 patients were referred for assessment of suspected-iNPH. 123 patients(21.6%) did not meet clinical criteria to proceed with further testing. 424 patients(74.4%;mean age 76.7 ± 6.0 years;males=269) underwent an LP or lumbar drain, and 193(45.6%) underwent insertion of a ventriculoperitoneal shunt. By 8-12 months after shunt surgery, gait velocity was 0.96±0.35m/s (54% faster than pre-CSF-drainage). Mean MoCA scores increased from 21.0 ± 5.0(median=22.0) at baseline to 22.6±5.5(median=24) 12-months post-surgery. Gait and cognitive improvements were clinically significant. No deaths occurred. 8% of shunt-surgery patients experienced minor complications. The 30-day reoperation rate was 4.1%. Conclusions: This AHCRN study demonstrated that CSF-drainage testing of patients with suspected-iNPH successfully identified those who could undergo CSF-shunt surgery with a high rate of improvement and a low rate of complications.
In this chapter the principles of ERP treatment are repeated. Various problems and issues which can arise in therapy are then discussed. Even if you do not succeed at first, that does not mean that you will not in the future. It is always worthwhile rethinking your treatment programme and having another try. If in doubt, you should seek advice from the various OCD organisations or a trusted doctor or healthcare professional.
This chapter will examine the idea of obsessive-compulsive slowness and how to tackle this problem, as well as examining perfectionism, the need to perform actions until they feel ‘just right’, and symmetry obsessions. Ideas such as ‘Lucky Dip’ and ‘Chance’ programmes will be described.
The overlap between autism and OCD will also be examined, as well as consideration about the role of other diagnoses in symmetry obsessions.
This chapter examines the treatment of ‘taboo’ obsessions. People with these kinds of obsessions often have very distressing images, thoughts, or even impulses which are against everything they believe in. These types of thoughts can be amongst the most distressing for an individual. Occasionally they are misunderstood by society or even healthcare professionals. Treatment involves accepting these distressing obsessions as thoughts rather than an active desire to commit abhorrent acts and allowing the thoughts to come without trying to push them away or ‘put them right’.
Fear of loss of an object or even fear of losing part of your body is a fairly common obsessive fear. Other people fear inadvertently divulging personal or other information and will go to great lengths of checking to ensure this does not occur. Treatment as always involves taking the risk and facing up to the fear. Also, in this chapter, we will examine hoarding, both as a symptom of OCD and also as a standalone condition.
This chapter will introduce the concept of graded exposure and self-imposed response prevention (ERP). It will describe the vicious cycle of compulsions and reassurance-seeking behaviours and the way they are rewarded by a reduction in discomfort. However, although these behaviours reduce discomfort, it is reduced only slightly, and the effect is often short-lived. Overall, therefore, the compulsions and reassurance-seeking serve to prolong and worsen the obsessive-compulsive symptoms. Later in this book, we will be discussing the practice of ERP in greater detail.
Avoidance of discomfort-inducing situations is also frequently found in OCD. This avoidance can lead to further worsening of the condition and an abnormal lifestyle which might, at its most extreme, threaten general health.
The treatment using ERP will be explained in full. Personal stories explaining the principles of ERP treatment will be given. We will also examine the success and likely outcomes of treatment with ERP.
The reasons why an ERP programme may not work in any specific case will be examined, and tips for moving forward in subsequent ERP programmes are presented.
Finally, the role of other therapies, including cognitive strategies as well as counselling, psychotherapy, and family therapy, will be mentioned.
This chapter will examine the obsessive fear that a person may commit an act they do not wish to do. This includes people who have images of themselves performing violent acts, people who worry that they may shout out something inappropriate or detrimental, as well as a variety of other behaviours. One example of a very distressing type of obsession is people who have images of themselves harming others by knocking people over in the road or even starting to wonder if they have committed an awful crime which they may have heard about via the media. People with this type of obsessive thoughts have been known to ‘confess’ to the police and in severe cases may be arrested for wasting police time.
The idea of ‘thought-action fusion’ is the idea that having a thought is as bad as performing the act or that thinking of an event makes it more likely to happen.
Fear of shouting out something inappropriate or obscene is also discussed and the distinction between this and Tourette syndrome.
Taboo obsessions involving fear of paedophilia are often in this category but because of the extreme distress and misunderstanding these obsessions can cause, they will be discussed in a separate chapter.
Treatment for all types of OCD is essentially the same and features prolonged graded exposure in real life to the feared situation combined with self-imposed response prevention. The necessary steps to set about doing this have been fully explained in . This chapter will address additional factors and difficulties which may arise with contamination fears. The chapter will describe what constitutes contamination fears, and look at fear of dirt, germs, and illness as well as the idea of ‘mental contamination’, when an individual fears becoming ‘contaminated’ by an abstract agent such as ‘evil’ or ‘bad thoughts’. Risks and dangers of both OCD with contamination fears and risks of any treatment itself will be explored. Issues such as how the pandemic impacts on successful treatment and what should be done in such circumstances are also discussed. Personal stories will be used as a guide to help you plan your treatment.