PTSD, Comorbidities, Gender, and Increased Risk of Cardiovascular Disease in a Large Military Cohort.

Importance: Posttraumatic stress disorder (PTSD) is a prevalent mental health problem that increases risk of cardiovascular disease (CVD). It is not known whether gender or comorbidities modify associations between PTSD and CVD. Objective: To assess risk of hypertension and atherosclerotic CVD (ASCVD) associated with PTSD in a predominantly young military population, and determine if gender or PTSD comorbidities modify these associations. Design setting and participants: Using administrative medical records, this longitudinal, retrospective cohort study assessed relationships of PTSD, gender, comorbidities (metabolic risk factors [MRF], behavioral risk factors [BRF], depression, and sleep disorders) to subsequent hypertension and ASCVD among 863,993 active-duty U.S. Army enlisted soldiers (86.2% male; 93.7%

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

STUDY OBJECTIVES: The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those most likely to respond. As a step toward personalized care, we present results of a machine learning (ML) model to predict CBT-I response. METHODS: Administrative data were examined for n = 1,449 nondeployed US Army soldiers treated for insomnia with CBT-I who had moderate-severe baseline Insomnia Severity Index (ISI) scores and completed 1 or more follow-up ISIs 6-12 weeks after baseline. An ensemble ML model was developed in a 70% training sample to predict clinically significant ISI improvement (reduction of at least 2 standard deviations on the baseline ISI distribution). Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample. RESULTS: 19.8% of patients had clinically significant ISI improvement. Model area under the receiver operating characteristic curve (standard error) was 0.60 (0.03). The 20% of test-sample patients with the highest probabilities of improvement were twice as likely to have clinically significant improvement compared with the remaining 80% (36.5% vs 15.7%; χ21 = 9.2, P = .002). Nearly 85% of prediction accuracy was due to 10 variables, the most important of which were baseline insomnia severity and baseline suicidal ideation. CONCLUSIONS: Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment. Parallel models will be needed for alternative treatments before such a system is of optimal value. CITATION: Gabbay FH, Wynn GH, Georg MW, et al. Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia. J Clin Sleep Med. 2024;20(6):921-931.

Toward personalized care for insomnia in the US Army: development of a machine-learning model to predict response to pharmacotherapy.

STUDY OBJECTIVES: Although many military personnel with insomnia are treated with prescription medication, little reliable guidance exists to identify patients most likely to respond. As a first step toward personalized care for insomnia, we present results of a machine-learning model to predict response to insomnia medication. METHODS: The sample comprised n = 4,738 nondeployed US Army soldiers treated with insomnia medication and followed 6-12 weeks after initiating treatment. All patients had moderate-severe baseline scores on the Insomnia Severity Index (ISI) and completed 1 or more follow-up ISIs 6-12 weeks after baseline. An ensemble machine-learning model was developed in a 70% training sample to predict clinically significant ISI improvement, defined as reduction of at least 2 standard deviations on the baseline ISI distribution. Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample. RESULTS: 21.3% of patients had clinically significant ISI improvement. Model test sample area under the receiver operating characteristic curve (standard error) was 0.63 (0.02). Among the 30% of patients with the highest predicted probabilities of improvement, 32.5.% had clinically significant symptom improvement vs 16.6% in the 70% sample predicted to be least likely to improve (χ21 = 37.1, P < .001). More than 75% of prediction accuracy was due to 10 variables, the most important of which was baseline insomnia severity. CONCLUSIONS: Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment, but parallel models will be needed for alternative treatments before such a system is of optimal value. CITATION: Gabbay FH, Wynn GH, Georg MW, et al. Toward personalized care for insomnia in the US Army: development of a machine-learning model to predict response to pharmacotherapy. J Clin Sleep Med. 2023;19(8):1399-1410.

The amphetamine response moderates the relationship between negative emotionality and alcohol use.

BACKGROUND: Considerable evidence suggests that sensitivity to the stimulant effects of alcohol and other drugs is a risk marker for heavy or problematic use of those substances. A separate body of research implicates negative emotionality. The goal of the present study was to evaluate the independent and interactive effects of the stimulant response, assessed with an amphetamine challenge, and negative emotionality on alcohol and drug use. METHODS: Healthy young women and men completed the Multidimensional Personality Questionnaire (MPQ) and an inventory assessing alcohol and other drug use. Subsequently, the effects of 10-mg d-amphetamine were determined in the laboratory using the Stimulant scale of the Biphasic Alcohol Effects Scale. Hierarchical regression analyses evaluated the effects of amphetamine response and the MPQ factor Negative Emotionality on measures of substance use. RESULTS: The amphetamine response moderated relationships between negative emotionality and alcohol use: in combination with a robust amphetamine response (i.e., enhanced stimulant effects as compared with baseline), negative emotionality predicted greater alcohol consumption, more episodes of binge drinking, and more frequent intoxication in regression models. A strong stimulant response independently predicted having used an illicit drug, and there was a trend for it to predict having used alcohol. Negative emotionality alone was not associated with any measure of alcohol or drug use. CONCLUSIONS: Consistent with the idea that emotion-based behavioral dysregulation promotes reward seeking, a high level of negative emotionality was associated with maladaptive alcohol use when it co-occurred with sensitivity to drug-based reward. The findings contribute to our understanding of how differences in personality may interact with those in drug response to affect alcohol use.

Brain potential indices of novelty processing are associated with preference for amphetamine.

A behavioral drug preference procedure was used to identify two groups of healthy individuals. One group preferred 10 mg of d-amphetamine over placebo (Choosers) and the other preferred placebo (Nonchoosers). In separate sessions, participants were administered placebo, 10, and 15 mg of d-amphetamine, and event-related brain potentials (ERPs) were recorded while participants performed two 3-stimulus oddball tasks. The effect of d-amphetamine on P3a, an ERP index of the orienting response, differed between groups: In Choosers, target stimuli elicited P3a after d-amphetamine but not after placebo; in Nonchoosers, the drug had no effect on P3a. Moreover, two group differences were evident after placebo and were unaffected by d-amphetamine. (1) N100 was larger in Nonchoosers than in Choosers, suggesting that Nonchoosers were more attentive than Choosers to the physical features of the stimuli. (2) The reorienting negativity (RON) elicited by targets in both tasks and by rare nontargets in a novelty oddball task (i.e., novel sounds) was larger in Nonchoosers than in Choosers. This suggests that Nonchoosers more effectively refocused attention on the task after distraction. It is hypothesized that these processing differences reflect a group difference in the balance between midbrain dopamine function and ascending cholinergic influences. The findings have implications for vulnerability to addiction and illustrate the promise of ERPs in parsing elemental phenotypes.

Evidence for a new late positive ERP component in an attended novelty oddball task.

In attended novelty oddball tasks, rare nontarget stimuli can elicit two late positive ERP components: P3a and P300. In passive oddball tasks, P300 is not elicited by these stimuli. In passive tasks, however, P3a is accompanied by another positive component, termed eP3a, which may have evaded detection in attended oddball tasks because of its spatiotemporal overlap with P300. To address this, temporal-spatial principal components analysis was used to quantify ERPs recorded in attended three-tone and novelty oddball tasks. As expected, novel stimuli elicited both P3a and P300. The analysis also identified a third component, evident in novelty ERPs as an inflection on the leading edge of P3a. This component has the same antecedent conditions as P3a, but is earlier and more centrally distributed. Its spatiotemporal characteristics suggest that it may be the eP3a component recently described in passive oddball tasks.

Family history of alcoholism and response to amphetamine: sex differences in the effect of risk.

BACKGROUND: Individuals at risk for alcoholism exhibit an enhanced stimulant response to alcohol. It is not known whether individuals at risk also exhibit a heightened sensitivity to other drugs with stimulant properties. METHODS: Healthy young men and women each received, in separate sessions, placebo and 10 mg of d-amphetamine in counterbalanced order. Stimulant and sedative subjective effects were recorded before and three times after capsule administration using the Biphasic Alcohol Effects Scale. The sample comprised 19 family-history-positive (FHP; 58% women) and 53 family-history-negative (FHN; 51% women) participants. RESULTS: As compared with placebo, amphetamine increased ratings of stimulation in the sample as a whole. In addition, the ratings revealed an enhanced, as well as a protracted, stimulant response to amphetamine among FHP men, as compared with FHN men: for FHP men, ratings of stimulation made 3 and 6 hr after amphetamine administration were greater than baseline ratings. Moreover, in FHP men, the effect of amphetamine, as compared with placebo, was most evident 6 hr after capsule administration. In contrast, despite a dose x hour interaction in FHN men, post hoc comparisons revealed no differences between the baseline and any of the postamphetamine measurements or between amphetamine and placebo ratings at any of the time points. Among women, the drug effect did not differentiate the family-history groups. CONCLUSIONS: Consistent with previous research on alcohol, high-risk men exhibited a heightened stimulant response to amphetamine. Thus, for men, sensitivity to the stimulant properties of drugs may be an endophenotype for alcoholism. Whereas the present results suggest that women at risk do not exhibit an enhanced stimulant response to amphetamine, further study is needed, including evaluation at various points in the menstrual cycle.

Variations in affect following amphetamine and placebo: markers of stimulant drug preference.

Variations in affect following d-amphetamine and placebo were examined in healthy young adults who subsequently preferred d-amphetamine (choosers; n = 61) or placebo (nonchoosers; n = 48) in a drug preference procedure. Affect was assessed before and 1, 3, and 6 hr after participants received the placebo and 10 mg d-amphetamine. Following amphetamine as compared with placebo, choosers' ratings increased on scales measuring energy, cognitive efficiency, and well-being, and decreased on scales measuring fatigue and sedation. Nonchoosers reported no effects, sedative effects, and dysphoric effects of amphetamine. Following placebo, ratings of energy, efficiency, and well-being decreased, and ratings of sedation increased in choosers but not in nonchoosers. Variations in affect following placebo and amphetamine may constitute markers of risk for drug use.