Routine diagnostics for neural antibodies,clinical correlates,treatment and functional outcome

Objective

To determine frequencies, interlaboratory reproducibility, clinical ratings, and prognostic implications of neural antibodies in a routine laboratory setting in patients with suspected neuropsychiatric autoimmune conditions.

Methods

Earliest available samples from 10,919 patients were tested for a broad panel of neural antibodies. Sera that reacted with leucine-rich glioma-inactivated protein 1 (LGI1), contactin-associated protein-2 (CASPR2), or the voltage-gated potassium channel (VGKC) complex were retested for LGI1 and CASPR2 antibodies by another laboratory. Physicians in charge of patients with positive antibody results retrospectively reported on clinical, treatment, and outcome parameters.

Results

Positive results were obtained for 576 patients (5.3%). Median disease duration was 6 months (interquartile range 0.6–46 months). In most patients, antibodies were detected both in CSF and serum. However, in 16 (28%) patients with N-methyl-d-aspartate receptor (NMDAR) antibodies, this diagnosis could be made only in cerebrospinal fluid (CSF). The two laboratories agreed largely on LGI1 and CASPR2 antibody diagnoses (κ = 0.95). The clinicians (413 responses, 71.7%) rated two-thirds of the antibody-positive patients as autoimmune. Antibodies against the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR), NMDAR (CSF or high serum titer), γ-aminobutyric acid-B receptor (GABABR), and LGI1 had ≥ 90% positive ratings, whereas antibodies against the glycine receptor, VGKC complex, or otherwise unspecified neuropil had ≤ 40% positive ratings. Of the patients with surface antibodies, 64% improved after ≥ 3 months, mostly with ≥ 1 immunotherapy intervention.

Conclusions

This novel approach starting from routine diagnostics in a dedicated laboratory provides reliable and useful results with therapeutic implications. Counseling should consider clinical presentation, demographic features, and antibody titers of the individual patient.

     

Near-infrared spectroscopy monitoring during immediate transition after birth: time to obtain cerebral tissue oxygenation

Feasibility of cerebral tissue oxygenation measurements immediately after birth has been published starting with first values 2 min after birth. Aim of this study was to evaluate, the time periods from birth and from arrival at the resuscitation table to obtain the first cerebral tissue oxygenation values with two different near infrared spectroscopy (NIRS) devices. The present study is an analysis of exploratory parameters of two prospective observational studies. Cerebral tissue oxygen saturation was measured by the NIRO 200NX measuring “cerebral-tissue-oxygenation-index” (cTOI) or the INVOS5100C measuring “cerebral-regional-oxygen-saturation” (crSO₂). Four time periods (T) were defined: T1 birth to arrival at resuscitation table, T2 arrival to application of NIRS sensor, T3 application to first displayed cTOI or crSO₂ value, and T4 from arrival at resuscitation table to first displayed values. Additionally, we compared first displayed values of cTOI and crSO₂. Thirty neonates were included. Twenty-four were term and six late-preterm neonates. Fifteen neonates measured with NIRO were compared to 15 measured with INVOS. T1 was 49 (6–163) s with NIRO versus 59 (15–87) s with INVOS, T2 14 (4–20) s versus 12 (15–18) s, T3 33 (13–138) s versus 17 (6–290) s and T4 46 (20–153) s and 34 (14–300) s. The first displayed value tended to be higher for cTOI [54% (18–80)] compared to crSO₂ [35% (15–87)]. There were no significant differences between devices in time periods and first values displayed. Cerebral tissue oxygenation can be measured within 1 min after arriving at the resuscitation table in term and preterm neonates after birth without difference between devices.     

Establishing a Research Agenda on Mobile Health Technologies and Later-Life Pain Using an Evidence-Based Consensus Workshop Approach

The rapid growth of mobile health (mHealth) devices holds substantial potential for improving care and care outcomes in all patient populations, including older adults with pain. However, existing research reflects a substantial gap in knowledge about how to design, evaluate, and disseminate devices to optimally address the many challenges associated with managing pain in older persons. Given these knowledge gaps, we sought to develop a set of practice-based research priorities to facilitate innovation in this field. We employed the Cornell Research-Practice Consensus Workshop Model, an evidence-based approach to generating research priorities. Sixty participants attended the conference, where stakeholder groups included older adults with pain and their caregivers, behavioral and social scientists, healthcare providers, pain experts, and specialists in mHealth and health policy. Participants generated 13 recommendations classified into 2 categories: 1) implications for designing research on mHealth among older adults (eg, conduct research on ways to enhance accessibility of mHealth tools among diverse groups of older adults with pain, expand research on mHealth sensing applications), and 2) implementation of mHealth technology into practice and associated regulatory issues (eg, promote research on ways to initiate/sustain patient behavior change, expand research on mHealth cybersecurity and privacy issues).