Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review

Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre- and post-intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV-based interventions reduced the amount of moderate- and/or high-intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV-based training. Peak oxygen uptake () and submaximal running parameters (eg, LT1, LT2) improved following both HRV-based and predefined training, with no clear difference in the extent of improvement in . Submaximal running parameters tended to improve more following HRV-based training. Research findings to date have been limited and inconsistent. Both HRV-based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.     

HPLC-MS Method for Simultaneous Quantitative Determination of an Innovative Russian Gestagen and its Metabolites in Rat and Rabbit Blood Sera

Pharmaceutical Chemistry Journal - An HPLC-MS method for simultaneous quantitative determination of a novel gestagenic pharmaceutical and two of its metabolites in rat and rabbit blood sera was...     

Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Aims: In neuropsychological evaluations, it is often difficult to ascertain whether poor performance on measures of validity is due to poor effort or malingering, or whether there is genuine cognitive impairment. Dunham and Denney created an algorithm to assess this question using the Medical Symptom Validity Test (MSVT). We assessed the ability of their algorithm to detect poor validity versus probable impairment, and concordance of failure on the MSVT with other freestanding tests of performance validity.

Methods: Two previously published datasets (n?=?153 and n?=?641, respectively) from outpatient neuropsychological evaluations were used to test Dunham and Denney’s algorithm, and to assess concordance of failure rates with the Test of Memory Malingering and the forced choice measure of the California Verbal Learning Test, two commonly used performance validity tests.

Results: In both datasets, none of the four cutoff scores for failure on the MSVT (70%, 75%, 80%, or 85%) identified a poor validity group with proportionally aligned failure rates on other freestanding measures of performance validity. Additionally, the protocols with probable impairment did not differ from those with poor validity on cognitive measures.

Conclusions: Despite what appeared to be a promising approach to evaluating failure on the easy MSVT subtests when clinical data are unavailable (as recommended in the advanced interpretation program, or advanced interpretation [AI], of the MSVT), the current findings indicate the AI remains the gold standard for doing so. Future research should build on this effort to address shortcomings in measures of effort in neuropsychological evaluations.     

Polymerase Chain Reaction and Goldmann-Witmer Coefficient Testing in the Diagnosis of Infectious Uveitis in HIV-Positive and HIV-Negative Patients in South Africa

Purpose: To use polymerase chain reaction (PCR) and Goldmann-Witmer coefficient (GWC) calculation to diagnose infectious uveitis.

Methods: Prospective cross-sectional study.

Results: Twenty-seven of 106 patients had positive PCR and/or GWC results on aqueous humor (AH) sampling and 15 of 27 (55.6%) were HIV-positive. Patients with non-anterior uveitis (NAU) were more likely to be HIV+ (p = 0.005). More than 1 possible pathogen was identified in 9 of 27 patients of whom 7 were HIV+. The final clinical diagnosis was discordant with AH findings in 9 of 27 cases. A positive EBV PCR result was associated with a discordant diagnosis (p = 0.001). All cases of herpetic anterior uveitis (42.9% HIV+) tested PCR-/GWC+ while all cases of herpetic NAU tested PCR+/GWC- (83.3% HIV+). All rubella virus cases were PCR+/GWC+.

Conclusion: PCR is useful to diagnose herpetic NAU in HIV+ patients while GWC is useful to diagnose herpetic anterior uveitis.