Can AI Answer My Questions? Utilizing Artificial Intelligence in the Perioperative Assessment for Abdominoplasty Patients.

BACKGROUND: Abdominoplasty is a common operation, used for a range of cosmetic and functional issues, often in the context of divarication of recti, significant weight loss, and after pregnancy. Despite this, patient-surgeon communication gaps can hinder informed decision-making. The integration of large language models (LLMs) in healthcare offers potential for enhancing patient information. This study evaluated the feasibility of using LLMs for answering perioperative queries. METHODS: This study assessed the efficacy of four leading LLMs-OpenAI's ChatGPT-3.5, Anthropic's Claude, Google's Gemini, and Bing's CoPilot-using fifteen unique prompts. All outputs were evaluated using the Flesch-Kincaid, Flesch Reading Ease score, and Coleman-Liau index for readability assessment. The DISCERN score and a Likert scale were utilized to evaluate quality. Scores were assigned by two plastic surgical residents and then reviewed and discussed until a consensus was reached by five plastic surgeon specialists. RESULTS: ChatGPT-3.5 required the highest level for comprehension, followed by Gemini, Claude, then CoPilot. Claude provided the most appropriate and actionable advice. In terms of patient-friendliness, CoPilot outperformed the rest, enhancing engagement and information comprehensiveness. ChatGPT-3.5 and Gemini offered adequate, though unremarkable, advice, employing more professional language. CoPilot uniquely included visual aids and was the only model to use hyperlinks, although they were not very helpful and acceptable, and it faced limitations in responding to certain queries. CONCLUSION: ChatGPT-3.5, Gemini, Claude, and Bing's CoPilot showcased differences in readability and reliability. LLMs offer unique advantages for patient care but require careful selection. Future research should integrate LLM strengths and address weaknesses for optimal patient education. LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Comparison of modified-release hydrocortisone capsules versus prednisolone in the treatment of congenital adrenal hyperplasia.

BACKGROUND: Prednisolone and prednisone are recommended treatment options for adults with Congenital Adrenal Hyperplasia (CAH); however, there is no randomised comparison of prednis(ol)one with hydrocortisone. OBJECTIVE: To assess 17-hydroxyprogesterone (17OHP) levels and glucocorticoid dose in CAH comparing prednis(ol)one versus modified-release hydrocortisone (MRHC). DESIGN: Six-month open-label randomised phase 3 study and interim analysis of a single-arm extension study. METHODS: Hydrocortisone dose equivalent and 09:00h 17OHP from 48 patients taking prednis(ol)one at baseline. RESULTS: At baseline, the median hydrocortisone dose equivalent was 30 mg /day and 17OHP was <36nmol/l (3X upper limit of normal) in 56% of patients. Patients were randomised to continue prednis(ol)one or switch to MRHC at the same hydrocortisone equivalent dose. At 4 weeks, 94% on MRHC and 71% on prednis(ol)one had 17OHP <36nmol/l. At 18 months in the extension study of MRHC, the median MRHC dose was 20 mg /day and 82% had 17OHP <36nmol/l. The percent of patients with 17OHP <36nmol/l on a hydrocortisone dose equivalent ≤25mg /day was greater at 18 months in the extension study on MRHC than while on prednis(ol)one at baseline: 57% vs 27%, P=0.04. In the randomised study, no patients had an adrenal crisis on MRHC and one on prednisolone. In the extension study (221 patient years), there were 12 adrenal crises in 5 patients (5.4/100 patient years). CONCLUSIONS: MRHC reduces 17OHP at 09:00h compared to prednis(ol)one and the dose of MRHC can be down-titrated over time in the majority of patients.

Evaluating Artificial Intelligence's Role in Teaching the Reporting and Interpretation of Computed Tomographic Angiography for Preoperative Planning of the Deep Inferior Epigastric Artery Perforator Flap.

Background: Artificial intelligence (AI) has the potential to transform preoperative planning for breast reconstruction by enhancing the efficiency, accuracy, and reliability of radiology reporting through automatic interpretation and perforator identification. Large language models (LLMs) have recently advanced significantly in medicine. This study aimed to evaluate the proficiency of contemporary LLMs in interpreting computed tomography angiography (CTA) scans for deep inferior epigastric perforator (DIEP) flap preoperative planning. Methods: Four prominent LLMs, ChatGPT-4, BARD, Perplexity, and BingAI, answered six questions on CTA scan reporting. A panel of expert plastic surgeons with extensive experience in breast reconstruction assessed the responses using a Likert scale. In contrast, the responses' readability was evaluated using the Flesch Reading Ease score, the Flesch-Kincaid Grade level, and the Coleman-Liau Index. The DISCERN score was utilized to determine the responses' suitability. Statistical significance was identified through a t-test, and P-values < 0.05 were considered significant. Results: BingAI provided the most accurate and useful responses to prompts, followed by Perplexity, ChatGPT, and then BARD. BingAI had the greatest Flesh Reading Ease (34.7±5.5) and DISCERN (60.5±3.9) scores. Perplexity had higher Flesch-Kincaid Grade level (20.5±2.7) and Coleman-Liau Index (17.8±1.6) scores than other LLMs. Conclusion: LLMs exhibit limitations in their capabilities of reporting CTA for preoperative planning of breast reconstruction, yet the rapid advancements in technology hint at a promising future. AI stands poised to enhance the education of CTA reporting and aid preoperative planning. In the future, AI technology could provide automatic CTA interpretation, enhancing the efficiency, accuracy, and reliability of CTA reports.

Use of artificial intelligence in breast surgery: a narrative review.

Background and Objective: We have witnessed tremendous advances in artificial intelligence (AI) technologies. Breast surgery, a subspecialty of general surgery, has notably benefited from AI technologies. This review aims to evaluate how AI has been integrated into breast surgery practices, to assess its effectiveness in improving surgical outcomes and operational efficiency, and to identify potential areas for future research and application. Methods: Two authors independently conducted a comprehensive search of PubMed, Google Scholar, EMBASE, and Cochrane CENTRAL databases from January 1, 1950, to September 4, 2023, employing keywords pertinent to AI in conjunction with breast surgery or cancer. The search focused on English language publications, where relevance was determined through meticulous screening of titles, abstracts, and full-texts, followed by an additional review of references within these articles. The review covered a range of studies illustrating the applications of AI in breast surgery encompassing lesion diagnosis to postoperative follow-up. Publications focusing specifically on breast reconstruction were excluded. Key Content and Findings: AI models have preoperative, intraoperative, and postoperative applications in the field of breast surgery. Using breast imaging scans and patient data, AI models have been designed to predict the risk of breast cancer and determine the need for breast cancer surgery. In addition, using breast imaging scans and histopathological slides, models were used for detecting, classifying, segmenting, grading, and staging breast tumors. Preoperative applications included patient education and the display of expected aesthetic outcomes. Models were also designed to provide intraoperative assistance for precise tumor resection and margin status assessment. As well, AI was used to predict postoperative complications, survival, and cancer recurrence. Conclusions: Extra research is required to move AI models from the experimental stage to actual implementation in healthcare. With the rapid evolution of AI, further applications are expected in the coming years including direct performance of breast surgery. Breast surgeons should be updated with the advances in AI applications in breast surgery to provide the best care for their patients.

Artificial Intelligence Language Model Performance for Rapid Intraoperative Queries in Plastic Surgery: ChatGPT and the Deep Inferior Epigastric Perforator Flap.

Background: The integration of artificial intelligence in healthcare has led to the development of large language models that can address various medical queries, including intraoperatively. This study investigates the potential of ChatGPT in addressing intraoperative questions during the deep inferior epigastric perforator flap procedure. Methods: A series of six intraoperative questions specific to the DIEP flap procedure, derived from real-world clinical scenarios, were proposed to ChatGPT. A panel of four experienced board-certified plastic surgeons evaluated ChatGPT's performance in providing accurate, relevant, and comprehensible responses. Results: The Likert scale demonstrated to be medically accurate, systematic in presentation, and logical when providing alternative solutions. The mean readability score of the Flesch Reading Ease Score was 28.7 (±0.8), the Flesch-Kincaid Grade Level was 12.4 (±0.5), and the Coleman-Liau Index was 14.5 (±0.5). Suitability-wise, the DISCERN score of ChatGPT was 48 (±2.5) indicating suitable and comprehensible language for experts. Conclusions: Generative AI tools such as ChatGPT can serve as a supplementary tool for surgeons to offer valuable insights and foster intraoperative problem-solving abilities. However, it lacks consideration of individual patient factors and surgical nuances. Nevertheless, further refinement of its training data and rigorous scrutiny under experts to ensure the accuracy and up-to-date nature of the information holds the potential for it to be utilized in the surgical field.

The importance of REM sleep fragmentation in the effects of stress on sleep: Perspectives from preclinical studies.

Psychological stress poses a risk for sleep disturbances. Importantly, trauma-exposed individuals who develop posttraumatic stress disorder (PTSD) frequently report insomnia and recurrent nightmares. Clinical studies have provided insight into the mechanisms of these sleep disturbances. We review polysomnographic findings in PTSD and identify analogous measures that have been made in animal models of PTSD. There is a rich empirical and theoretical literature on rapid eye movement sleep (REMS) substrates of insomnia and nightmares, with an emphasis on REMS fragmentation. For future investigations of stress-induced sleep changes, we recommend a focus on tonic, phasic and other microarchitectural REMS measures. Power spectral density analysis of the sleep EEG should also be utilized. Animal models with high construct validity can provide insight into gender and time following stressor exposure as moderating variables. Ultimately, preclinical studies with translational potential will lead to improved treatment for stress-related sleep disturbances.

Multivariable Model to Predict an ACTH Stimulation Test to Diagnose Adrenal Insufficiency Using Previous Test Results.

Context: The adrenocorticotropin hormone stimulation test (AST) is used to diagnose adrenal insufficiency, and is often repeated in patients when monitoring recovery of the hypothalamo-pituitary-adrenal axis. Objective: To develop and validate a prediction model that uses previous AST results with new baseline cortisol to predict the result of a new AST. Methods: This was a retrospective, longitudinal cohort study in patients who had undergone at least 2 ASTs, using polynomial regression with backwards variable selection, at a Tertiary UK adult endocrinology center. Model was developed from 258 paired ASTs over 5 years in 175 adults (mean age 52.4 years, SD 16.4), then validated on data from 111 patients over 1 year (51.8, 17.5) from the same center, data collected after model development. Candidate prediction variables included previous test baseline adrenocorticotropin hormone (ACTH), previous test baseline and 30-minute cortisol, days between tests, and new baseline ACTH and cortisol used with calculated cortisol/ACTH ratios to assess 8 candidate predictors. The main outcome measure was a new test cortisol measured 30 minutes after Synacthen administration. Results: Using 258 sequential ASTs from 175 patients for model development and 111 patient tests for model validation, previous baseline cortisol, previous 30-minute cortisol and new baseline cortisol were superior at predicting new 30-minute cortisol (R2 = 0.71 [0.49-0.93], area under the curve [AUC] = 0.97 [0.94-1.0]) than new baseline cortisol alone (R2 = 0.53 [0.22-0.84], AUC = 0.88 [0.81-0.95]). Conclusion: Results of a previous AST can be objectively combined with new early-morning cortisol to predict the results of a new AST better than new early-morning cortisol alone. An online calculator is available at https://endocrinology.shinyapps.io/sheffield_sst_calculator/ for external validation.

Symptomatic benefits of testosterone treatment in patient subgroups: a systematic review, individual participant data meta-analysis, and aggregate data meta-analysis.

BACKGROUND: Testosterone replacement therapy is known to improve sexual function in men younger than 40 years with pathological hypogonadism. However, the extent to which testosterone alleviates sexual dysfunction in older men and men with obesity is unclear, despite the fact that testosterone is being increasingly prescribed to these patient populations. We aimed to evaluate whether subgroups of men with low testosterone derive any symptomatic benefit from testosterone treatment. METHODS: We did a systematic review and meta-analysis to evaluate characteristics associated with symptomatic benefit of testosterone treatment versus placebo in men aged 18 years and older with a baseline serum total testosterone concentration of less than 12 nmol/L. We searched major electronic databases (MEDLINE, Embase, Science Citation Index, and the Cochrane Central Register of Controlled Trials) and clinical trial registries for reports published in English between Jan 1, 1992, and Aug 27, 2018. Anonymised individual participant data were requested from the investigators of all identified trials. Primary (cardiovascular) outcomes from this analysis have been published previously. In this report, we present the secondary outcomes of sexual function, quality of life, and psychological outcomes at 12 months. We did a one-stage individual participant data meta-analysis with a random-effects linear regression model, and a two-stage meta-analysis integrating individual participant data with aggregated data from studies that did not provide individual participant data. This study is registered with PROSPERO, CRD42018111005. FINDINGS: 9871 citations were identified through database searches. After exclusion of duplicates and publications not meeting inclusion criteria, 225 full texts were assessed for inclusion, of which 109 publications reporting 35 primary studies (with a total 5601 participants) were included. Of these, 17 trials provided individual participant data (3431 participants; median age 67 years [IQR 60-72]; 3281 [97%] of 3380 aged ≥40 years) Compared with placebo, testosterone treatment increased 15-item International Index of Erectile Function (IIEF-15) total score (mean difference 5·52 [95% CI 3·95-7·10]; τ2=1·17; n=1412) and IIEF-15 erectile function subscore (2·14 [1·40-2·89]; τ2=0·64; n=1436), reaching the minimal clinically important difference for mild erectile dysfunction. These effects were not found to be dependent on participant age, obesity, presence of diabetes, or baseline serum total testosterone. However, absolute IIEF-15 scores reached during testosterone treatment were subject to thresholds in patient age and baseline serum total testosterone. Testosterone significantly improved Aging Males' Symptoms score, and some 12-item or 36-item Short Form Survey quality of life subscores compared with placebo, but it did not significantly improve psychological symptoms (measured by Beck Depression Inventory). INTERPRETATION: In men aged 40 years or older with baseline serum testosterone of less than 12 nmol/L, short-to-medium-term testosterone treatment could provide clinically meaningful treatment for mild erectile dysfunction, irrespective of patient age, obesity, or degree of low testosterone. However, due to more severe baseline symptoms, the absolute level of sexual function reached during testosterone treatment might be lower in older men and men with obesity. FUNDING: National Institute for Health and Care Research Health Technology Assessment Programme.

Comparing the Efficacy of Large Language Models ChatGPT, BARD, and Bing AI in Providing Information on Rhinoplasty: An Observational Study.

Background: Large language models (LLMs) are emerging artificial intelligence (AI) technologies refining research and healthcare. However, the impact of these models on presurgical planning and education remains under-explored. Objectives: This study aims to assess 3 prominent LLMs-Google's AI BARD (Mountain View, CA), Bing AI (Microsoft, Redmond, WA), and ChatGPT-3.5 (Open AI, San Francisco, CA) in providing safe medical information for rhinoplasty. Methods: Six questions regarding rhinoplasty were prompted to ChatGPT, BARD, and Bing AI. A Likert scale was used to evaluate these responses by a panel of Specialist Plastic and Reconstructive Surgeons with extensive experience in rhinoplasty. To measure reliability, the Flesch Reading Ease Score, the Flesch-Kincaid Grade Level, and the Coleman-Liau Index were used. The modified DISCERN score was chosen as the criterion for assessing suitability and reliability. A t test was performed to calculate the difference between the LLMs, and a double-sided P-value <.05 was considered statistically significant. Results: In terms of reliability, BARD and ChatGPT demonstrated a significantly (P < .05) greater Flesch Reading Ease Score of 47.47 (±15.32) and 37.68 (±12.96), Flesch-Kincaid Grade Level of 9.7 (±3.12) and 10.15 (±1.84), and a Coleman-Liau Index of 10.83 (±2.14) and 12.17 (±1.17) than Bing AI. In terms of suitability, BARD (46.3 ± 2.8) demonstrated a significantly greater DISCERN score than ChatGPT and Bing AI. In terms of Likert score, ChatGPT and BARD demonstrated similar scores and were greater than Bing AI. Conclusions: BARD delivered the most succinct and comprehensible information, followed by ChatGPT and Bing AI. Although these models demonstrate potential, challenges regarding their depth and specificity remain. Therefore, future research should aim to augment LLM performance through the integration of specialized databases and expert knowledge, while also refining their algorithms.

Using Generative Artificial Intelligence Tools in Cosmetic Surgery: A Study on Rhinoplasty, Facelifts, and Blepharoplasty Procedures.

Artificial intelligence (AI), notably Generative Adversarial Networks, has the potential to transform medical and patient education. Leveraging GANs in medical fields, especially cosmetic surgery, provides a plethora of benefits, including upholding patient confidentiality, ensuring broad exposure to diverse patient scenarios, and democratizing medical education. This study investigated the capacity of AI models, DALL-E 2, Midjourney, and Blue Willow, to generate realistic images pertinent to cosmetic surgery. We combined the generative powers of ChatGPT-4 and Google's BARD with these GANs to produce images of various noses, faces, and eyelids. Four board-certified plastic surgeons evaluated the generated images, eliminating the need for real patient photographs. Notably, generated images predominantly showcased female faces with lighter skin tones, lacking representation of males, older women, and those with a body mass index above 20. The integration of AI in cosmetic surgery offers enhanced patient education and training but demands careful and ethical incorporation to ensure comprehensive representation and uphold medical standards.

Developing oral chronotherapy for cortisol replacement in congenital adrenal hyperplasia.

The sun imposes a 24-h periodicity to life and circadian rhythms have evolved to maintain homoeostasis through the day/night cycle. In humans, there is a central clock that controls the sleep/wake cycle which is paralleled metabolically by a fast/feed cycle. The clock maintains homoeostasis by synchronising metabolism to the time of feeding. Loss of synchrony between the clock and hormonal rhythms results in loss of homoeostasis as evidenced by obesity, depression, and diabetes in people undertaking shift work. Cortisol has a distinct circadian rhythm; peaking on waking and low at sleep onset. Loss of this rhythm in adrenal insufficiency is associated with a poor quality of life and increased mortality. To replace the cortisol rhythm requires chronotherapy and for this you need to define the key parameters of the target rhythm, create a formulation to replicate that rhythm, and then prove clinical benefit. The physiology of hormones is more complex than that of nonnative drugs. Hormones are secreted with varied rhythms, bound to multiple cognate binding proteins, and actively transported and cleared through enzymatic pathways in multiple organs. We have examined the diurnal rhythm of cortisol in healthy volunteers, created physiologically-based pharmacokinetic models, and tested various oral delayed and sustained formulations of hydrocortisone (development name, Chronocort) in clinical trials. The outcome from this work was the manufacture of modified-release hydrocortisone hard capsules (tradename Efmody, Diurnal Ltd), that replicate the cortisol diurnal rhythm and improve the disease control of congenital adrenal hyperplasia the commonest hereditary form of adrenal insufficiency.

Evaluating Chatbot Efficacy for Answering Frequently Asked Questions in Plastic Surgery: A ChatGPT Case Study Focused on Breast Augmentation.

BACKGROUND: The integration of artificial intelligence (AI) and machine learning (ML) technologies into healthcare is transforming patient-practitioner interaction and could offer an additional platform for patient education and support. OBJECTIVES: This study investigated whether ChatGPT-4 could provide safe and up-to-date medical information about breast augmentation that is comparable to other patient information sources. METHODS: ChatGPT-4 was asked to generate 6 commonly asked questions regarding breast augmentation and respond to them. Its responses were qualitatively evaluated by a panel of specialist plastic and reconstructive surgeons and reconciled with a literature search of 2 large medical databases for accuracy, informativeness, and accessibility. RESULTS: ChatGPT-4 provided well-structured, grammatically accurate, and comprehensive responses to the questions posed; however, it was limited in providing personalized advice and sometimes generated inappropriate or outdated references. ChatGPT consistently encouraged engagement with a specialist for specific information. CONCLUSIONS: Although ChatGPT-4 showed promise as an adjunct tool in patient education regarding breast augmentation, there are areas requiring improvement. Additional advancements and software engineering are needed to enhance the reliability and applicability of AI-driven chatbots in patient education and support systems.

Long-term cardiometabolic morbidity in young adults with classic 21-hydroxylase deficiency congenital adrenal hyperplasia.

PURPOSE: To study the current practice for assessing comorbidity in adults with 21-hydroxylase CAH and to assess the prevalence of comorbidity in these adults. METHODS: A structured questionnaire was sent to 46 expert centres managing adults with CAH. Information collected included current therapy and surveillance practice with a particular focus on osteoporosis/osteopaenia, hyperlipidaemia, type 2 diabetes/hyperinsulinaemia, hypertension, CV disease, obesity. RESULTS: Of the 31 (67%) centres from 15 countries that completed the survey, 30 (97%) screened for hypertension by measuring blood pressure, 30 (97%) screened for obesity, 26 (84%) screened for abnormal glucose homoeostasis mainly by using Hb1Ac (73%), 25 (81%) screened for osteoporosis mainly by DXA (92%), 20 (65%) screened for hyperlipidaemia and 6 (19%) screened for additional CV disease. Of the 31 centres, 13 provided further information on the six co-morbidities in 244 patients with a median age of 33 yrs (range 19, 94). Of these, 126 (52%) were females and 174 (71%) received fludrocortisone in addition to glucocorticoids. Of the 244 adults, 73 (30%) were treated for at least one comorbidity and 15 (21%) for more than 2 co-morbidities. Of 73, the patients who were treated for osteoporosis/osteopaenia, hyperlipidaemia, type 2 diabetes/hyperinsulinaemia, hypertension, CV disease, obesity were 43 (59%), 17 (23%), 16 (22%), 10 (14%), 8 (11), 3 (4%) respectively. CONCLUSION: Cardiometabolic and bone morbidities are not uncommon in adults with CAH. There is a need to standardise the screening for these morbidities from early adulthood and to explore optimal therapy through routine collection of standardised data.

Model-Informed Target Morning 17α-Hydroxyprogesterone Concentrations in Dried Blood Spots for Pediatric Congenital Adrenal Hyperplasia Patients.

Monitoring cortisol replacement therapy in congenital adrenal hyperplasia (CAH) patients is vital to avoid serious adverse events such as adrenal crises due to cortisol underexposure or metabolic consequences due to cortisol overexposure. The less invasive dried blood spot (DBS) sampling is an advantageous alternative to traditional plasma sampling, especially in pediatric patients. However, target concentrations for important disease biomarkers such as 17α-hydroxyprogesterone (17-OHP) are unknown using DBS. Therefore, a modeling and simulation framework, including a pharmacokinetic/pharmacodynamic model linking plasma cortisol concentrations to DBS 17-OHP concentrations, was used to derive a target morning DBS 17-OHP concentration range of 2-8 nmol/L in pediatric CAH patients. Since either capillary or venous DBS sampling is becoming more common in the clinics, the clinical applicability of this work was shown by demonstrating the comparability of capillary and venous cortisol and 17-OHP concentrations collected by DBS sampling, using a Bland-Altman and Passing-Bablok analysis. The derived target morning DBS 17-OHP concentration range is a first step towards providing improved therapy monitoring using DBS sampling and adjusting hydrocortisone (synthetic cortisol) dosing in children with CAH. In the future, this framework can be used to assess further research questions, e.g., target replacement ranges for the entire day.

Chronotherapy based on modified-release hydrocortisone to restore the physiological cortisol diurnal rhythm.

In this inspirational note, we describe the development of an endocrine chronotherapy to restore the physiological rhythm of the essential adrenal stress hormone, cortisol. The challenges included demonstrating the circadian rhythm of the drug target, creating a drug formulation that replicated that rhythm and then proving benefit in clinical trials. The physiological cortisol circadian rhythm is well defined with cortisol levels high on waking and low on going to sleep. We experimented with different formulation technologies including modified-release tablets and multi-particulates to replicate the cortisol rhythm where absent through disease. We describe the development of Efmody®, a modified-release formulation of hydrocortisone, which replicates the cortisol diurnal rhythm and improves the disease control of congenital adrenal hyperplasia, the commonest hereditary form of adrenal insufficiency. This program shows it is possible, through modified-release technology, to treat chronic endocrine diseases with physiological replacement to preserve health for life.

Home Waking Salivary Cortisone to Screen for Adrenal Insufficiency.

BACKGROUND: Worldwide, adults and children are at risk of adrenal insufficiency as a result of adrenal suppression from use of anti-inflammatory glucocorticoids and opiates, as well as infectious diseases. The adrenocorticotropin (ACTH) stimulation test is the reference standard for diagnosis of adrenal insufficiency but requires clinic attendance and venesection. Salivary cortisone reflects free serum cortisol, and samples can be collected at home and posted to a laboratory. We tested whether home waking salivary cortisone level could be used to screen for adrenal insufficiency. METHODS: A prospective, diagnostic accuracy study was performed in patients at high risk of adrenal insufficiency. Patients collected a home salivary sample on waking and then attended the clinical facility for an ACTH stimulation test. Salivary cortisone was measured by liquid chromatography­tandem mass spectrometry. Receiver-operating characteristic curves were computed, and positive and negative predictive values were calculated. RESULTS: Two hundred twenty patients were recruited. As measured by an ACTH stimulation test, the prevalence of adrenal insufficiency was 44%. The area under the receiver-operating characteristic curve for waking salivary cortisone as a predictor of adrenal insufficiency was 0.95 (95% confidence interval [CI], 0.92 to 0.97). Cutoffs to ensure a minimum of 95% sensitivity and specificity gave a negative predictive value of 96% (95% CI, 90 to 99) and a positive predictive value of 95% (95% CI, 87 to 99) to exclude and confirm adrenal insufficiency, respectively. Waking salivary cortisone data provided information similar to that of an ACTH stimulation test in 70% of participants. Eighty-three percent of patients preferred home salivary collection to clinic attendance. CONCLUSIONS: Home waking salivary cortisone sampling has accuracy for the diagnosis of adrenal insufficiency similar to that of a standard ACTH stimulation test. Patients found the at-home test to be more convenient than the hospital-based test. (Funded by the National Institute for Health Research.)

The association of polysomnographic sleep on posttraumatic stress disorder symptom clusters in trauma-exposed civilians and veterans.

Study Objectives: Self-reported sleep disturbance has been established as a risk factor and predictor for posttraumatic stress disorder (PTSD); however, less is known about the relationship between objective sleep and PTSD symptom clusters, and the specific role of hyperarousal. The present study examined the relationships between sleep continuity and architecture on PTSD symptom clusters. Methods: Participants underwent two in-laboratory sleep studies to assess sleep continuity and architecture. They also completed the Clinician-Administered PTSD-IV scale and the Structured Clinical Interview for the DSM-IV to assess for PTSD diagnosis and other psychiatric disorders. Results: Sleep continuity (i.e. total sleep time, sleep efficiency percent, wake after sleep onset, sleep latency) was significantly related to PTSD Cluster B (reexperiencing) symptom severity (R 2 = .27, p < .001). Sleep architecture, specifically Stage N1 sleep, was significantly associated with PTSD Cluster B (t = 2.98, p = .004), C (Avoidance; t = 3.11, p = .003), and D (Hyperarosual; t = 3.79, p < .001) symptom severity independently of Stages N2, N3, and REM sleep. REM sleep variables (i.e. REM latency, number of REM periods) significantly predicted Cluster D symptoms (R 2 = .17, p = .002). Conclusions: These data provide evidence for a relationship between objective sleep and PTSD clusters, showing that processes active during Stage N1 sleep may contribute to PTSD symptomatology in civilians and veterans. Further, these data suggest that arousal mechanisms active during REM sleep may also contribute to PTSD hyperarousal symptoms.This paper is part of the War, Trauma, and Sleep Across the Lifespan Collection. This collection is sponsored by the Sleep Research Society.

Salivary Steroid Collection in Children Under Conditions Replicating Home Sampling.

CONTEXT: Measurement of salivary glucocorticoids is an accepted method for testing adrenal function but there are few data on stability during home collection. Current salivary collection techniques require active participation or present a choking hazard and are unsuitable for young children. OBJECTIVE: We sought to compare different salivary collection methods; assess the stability of salivary glucocorticoids under conditions replicating home collection; and assess patient tolerability and caregiver acceptability of a salivary collection device for young children, a swab encased in an infant pacifier (SaliPac). METHODS: Six healthy adults collected salivary samples using a Salivette Cortisol, passive drool, and SalivaBio at night, waking, and 3 Pm for five days. Time to collect 1-mL saliva using the SalivaBio and SaliPac and caregiver acceptability were assessed in 30 children younger than 6 years. Saliva was stored at 4 °C, room temperature (RT), and 50 °C for 24, 48, 72 hours and 1 week to replicate potential postage conditions. Salivary cortisol and cortisone concentrations were measured by mass spectrometry. RESULTS: There was no difference in salivary glucocorticoid concentrations using the 3 collection methods. Salivary cortisol and cortisone were stable for 72 hours at RT and 4 °C, and repeated freeze-thaw cycles did not cause significant degradation. In children younger than 6 years the SalivaBio and SaliPac were well tolerated and collected sufficient saliva for salivary steroid analysis in less than 4 minutes. CONCLUSION: Salivette, passive drool, and SalivaBio collect samples with comparable salivary cortisol and cortisone concentrations, which are stable under conditions replicating home collection. SaliPac is an acceptable device for salivary sampling in young children.