Publications

OBJECTIVE

To review studies on structural pulmonary and cardiac changes in SUDEP cases as well as studies showing pulmonary or cardiac structural changes in living epilepsy patients.

METHODS

We conducted electronic literature searches using the PubMed database for articles published in English, regardless of publication year, that included data on cardiac and/or pulmonary structural abnormalities in SUDEP cases or in living epilepsy patients during the postictal period.

RESULTS

Fourteen postmortem studies reported pulmonary findings in SUDEP cases. Two focused mainly on assessing lung weights in SUDEP cases versus controls; no group difference was found. The other 12 reported descriptive autopsy findings. Among all SUDEP cases with available descriptive postmortem pulmonary examination, 72% had pulmonary changes, most often pulmonary edema/congestion, and, less frequently, intraalveolar hemorrhage. Eleven studies reported on cardiac pathology in SUDEP. Cardiac abnormalities were found in approximately one-fourth of cases. The most common findings were myocyte hypertrophy and myocardial fibrosis of various degrees. Among living epilepsy patients, postictal pulmonary pathology was the most commonly reported pulmonary abnormality and the most common postictal cardiac abnormality was transient left ventricular dysfunction - Takotsubo or neurogenic stunned myocardium.

SIGNIFICANCE

Cardiac and pulmonary pathological abnormalities are frequent among SUDEP cases, most commonly pulmonary edema/congestion and focal interstitial myocardial fibrosis. Most findings are not quantified, with subjective elements and undefined interobserver reliability, and lack of controls such as matched epilepsy patients who died from other causes. Further, studies have not systematically evaluated potential confounding factors, including postmortem interval to autopsy, paramedic resuscitation and IV fluids administration, underlying heart/lung disease, and risk factors for cardiac or pulmonary disease. Prospective studies with controls are needed to define the heart and lung changes in SUDEP and understand their potential relationship to mechanisms of death in SUDEP.

BACKGROUND

Telemedicine has emerged as an innovative platform to diagnose and treat psychiatric disorders in a cost-effective fashion. Previous studies have laid the functional framework for monitoring and treating child psychiatric disorders electronically using videoconferencing, mobile phones (smartphones), and Web-based apps. However, phone call and text message (short message service, SMS) interventions in adolescent psychiatry are less studied than other electronic platforms. Further investigations on the development of these interventions are needed.

OBJECTIVE

The aim of this paper was to explore the utility of text message interventions in adolescent psychiatry and describe a user feedback-driven iterative design process for text message systems.

METHODS

We developed automated text message interventions using a platform for both depression (EpxDepression) and autism spectrum disorder (ASD; EpxAutism) and conducted 2 pilot studies for each intervention (N=3 and N=6, respectively). The interventions were prescribed by and accessible to the patients' healthcare providers. EpxDepression and EpxAutism utilized an automated system to triage patients into 1 of 3 risk categories based on their text responses and alerted providers directly via phone and an online interface when patients met provider-specified risk criteria. Rapid text-based feedback from participants and interviews with providers allowed for quick iterative cycles to improve interventions.

RESULTS

Patients using EpxDepression had high weekly response rates (100% over 2 to 4 months), but exhibited message fatigue with daily prompts with mean (SD) overall response rates of 66.3% (21.6%) and 64.7% (8.2%) for mood and sleep questionnaires, respectively. In contrast, parents using EpxAutism displayed both high weekly and overall response rates (100% and 85%, respectively, over 1 to 4 months) that did not decay significantly with time. Monthly participant feedback surveys for EpxDepression (7 surveys) and EpxAutism (18 surveys) preliminarily indicated that for both interventions, daily messages constituted the "perfect amount" of contact and that EpxAutism, but not EpxDepression, improved patient communication with providers. Notably, EpxDepression detected thoughts of self-harm in patients before their case managers or caregivers were aware of such ideation.

CONCLUSIONS

Text-message interventions in adolescent psychiatry can provide a cost-effective and engaging method to track symptoms, behavior, and ideation over time. Following the collection of pilot data and feedback from providers and patients, larger studies are already underway to validate the clinical utility of EpxDepression and EpxAutism.

TRIAL REGISTRATION

Clinicaltrials.gov NCT03002311; https://clinicaltrials.gov/ct2/show/NCT03002311 (Archived by WebCite at http://www.webcitation.org/6qQtlCIS0).

BACKGROUND

Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course.

METHODS

We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index.

RESULTS

Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years.

CONCLUSIONS

The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD.