Sleep and Sleep-Wake Disturbances in Care Recipient-Caregiver Dyads in the Context of a Chronic Illness: A Critical Review of the Literature

ContextAlterations in sleep-wake patterns of care recipients and their informal caregivers are common in the context of a chronic illness. Given the current notion that sleep may be regulated within and affected by close human relationships, concurrent and interrelated sleep problems may be present in care recipient-caregiver dyads.ObjectivesTo critically analyze evidence regarding concurrent sleep patterns or changes in care recipient-caregiver dyads in the context of a chronic illness and address methodological and research gaps.MethodsUsing a wide range of key terms and synonyms, three electronic databases (Medline, CINAHL, and Embase) were systematically searched for the period between January 1990 and July 2011.ResultsTen studies met prespecified selection criteria and were included for analysis. Study quality was fair to good on average. Seven studies were conducted in the context of dementia or Parkinson's disease, two in the context of cancer, and one study included a group of community elders with mixed related comorbidities and their informal caregivers. Bidirectional associations in the sleep of care recipient-caregiver dyads seem to exist. Concurrent and comparable nocturnal sleep disruptions also may be evident. Yet, inconsistencies in the methods implemented, and the samples included, as well as uncertainty regarding factors coaffecting sleep, still preclude safe conclusions to be drawn on.ConclusionThe dyadic investigation of sleep is a promising approach to the development of truly effective interventions to improve sleep quality of care recipients and their caregivers. Nevertheless, more systematic, longitudinal dyadic research is warranted to augment our understanding of co-occurrence and over time changes of sleep problems in care recipient-caregiver dyads, as well as to clarify covariates/factors that appear to contribute to these problems within the dyad and across time and context of illness.     

Estimating the mediating effect of different biomarkers on the relation of alcohol consumption with the risk of type 2 diabetes

PurposeModerate alcohol consumption is associated with a reduced type 2 diabetes risk, but the biomarkers that explain this relation are unknown. The most commonly used method to estimate the proportion explained by a biomarker is the difference method. However, influence of alcohol–biomarker interaction on its results is unclear. G-estimation method is proposed to accurately assess proportion explained, but how this method compares with the difference method is unknown.MethodsIn a case–cohort study of 2498 controls and 919 incident diabetes cases, we estimated the proportion explained by different biomarkers on the relation between alcohol consumption and diabetes using the difference method and sequential G-estimation method.ResultsUsing the difference method, high-density lipoprotein cholesterol explained the relation between alcohol and diabetes by 78% (95% confidence interval [CI], 41–243), whereas high-sensitivity C-reactive protein (?7.5%; ?36.4 to 1.8) or blood pressure (?6.9; ?26.3 to ?0.6) did not explain the relation. Interaction between alcohol and liver enzymes led to bias in proportion explained with different outcomes for different levels of liver enzymes. G-estimation method showed comparable results, but proportions explained were lower.ConclusionsThe relation between alcohol consumption and diabetes may be largely explained by increased high-density lipoprotein cholesterol but not by other biomarkers. Ignoring exposure–mediator interactions may result in bias. The difference and G-estimation methods provide similar results.     

Waterborne parasites and physico-chemical assessment of selected lakes in Malaysia

The objective of this study was to assess the physico-chemical parameters and waterborne parasites in selected recreational lakes from Malaysia. Samples were collected from seven stations of Recreational Lake A (RL-A) and six stations of Recreational Lake B (RL-B). The samples were processed to detect the presence of Giardia spp. and Cryptosporidium spp. using immunomagnetic separation kit, helminth eggs or ova by bright field microscopy and Acanthamoeba spp. by cultivation in non-nutrient agar. Chemical parameters such as ammonia, chlorine, fluoride, nitrate and nitrite and physical parameters such as dissolved oxygen, electrical conductivity, pH, salinity, temperature and total dissolved solid were also measured. Both lakes were freshwater with salinity ranging from 0.05 to 0.09 ppt. Most stations of these lakes were contaminated with Cryptosporidium spp., Giardia spp., Ascaris spp. and hookworm. Schistosoma spp. was found in RL-B only, while Acanthamoeba spp. was found in all stations. Of all sampling sites, station 5 of RL-B is the most contaminated. Linear regression and correlation analysis revealed that Giardia spp. and Schistosoma spp. showed a significant negative correlation with turbidity (p?<?0.01). Based on the preliminary data obtained, it is clearly shown that there is a necessity to implement the detection of waterborne parasites and physico-chemical analysis in Malaysia. Future work on heavy metals (chromium, copper, mercury and zinc) is recommended to enhance the overall water quality monitoring and to take appropriate safety measures to ensure maintenance of good water standards.     

Recommended Immunological Strategies to Screen for Botulinum Neurotoxin-Containing Samples

Botulinum neurotoxins (BoNTs) cause the life-threatening neurological illness botulism in humans and animals and are divided into seven serotypes (BoNT/A–G), of which serotypes A, B, E, and F cause the disease in humans. BoNTs are classified as “category A” bioterrorism threat agents and are relevant in the context of the Biological Weapons Convention. An international proficiency test (PT) was conducted to evaluate detection, quantification and discrimination capabilities of 23 expert laboratories from the health, food and security areas. Here we describe three immunological strategies that proved to be successful for the detection and quantification of BoNT/A, B, and E considering the restricted sample volume (1 mL) distributed. To analyze the samples qualitatively and quantitatively, the first strategy was based on sensitive immunoenzymatic and immunochromatographic assays for fast qualitative and quantitative analyses. In the second approach, a bead-based suspension array was used for screening followed by conventional ELISA for quantification. In the third approach, an ELISA plate format assay was used for serotype specific immunodetection of BoNT-cleaved substrates, detecting the activity of the light chain, rather than the toxin protein. The results provide guidance for further steps in quality assurance and highlight problems to address in the future.     

Automated whole‐brain N‐acetylaspartate proton MRS quantification

Concentration of the neuronal marker, N‐acetylaspartate (NAA), a quantitative metric for the health and density of neurons, is currently obtained by integration of the manually defined peak in whole‐head proton (¹H)‐MRS. Our goal was to develop a full spectral modeling approach for the automatic estimation of the whole‐brain NAA concentration (WBNAA) and to compare the performance of this approach with a manual frequency‐range peak integration approach previously employed. MRI and whole‐head ¹H‐MRS from 18 healthy young adults were examined. Non‐localized, whole‐head ¹H‐MRS obtained at 3 T yielded the NAA peak area through both manually defined frequency‐range integration and the new, full spectral simulation. The NAA peak area was converted into an absolute amount with phantom replacement and normalized for brain volume (segmented from T₁‐weighted MRI) to yield WBNAA. A paired‐sample t test was used to compare the means of the WBNAA paradigms and a likelihood ratio test used to compare their coefficients of variation. While the between‐subject WBNAA means were nearly identical (12.8 ± 2.5 mm for integration, 12.8 ± 1.4 mm for spectral modeling), the latter's standard deviation was significantly smaller (by ~50%, p = 0.026). The within‐subject variability was 11.7% (±1.3 mm ) for integration versus 7.0% (±0.8 mm ) for spectral modeling, i.e., a 40% improvement. The (quantifiable) quality of the modeling approach was high, as reflected by Cramer–Rao lower bounds below 0.1% and vanishingly small (experimental ‐ fitted) residuals. Modeling of the whole‐head ¹H‐MRS increases WBNAA quantification reliability by reducing its variability, its susceptibility to operator bias and baseline roll, and by providing quality‐control feedback. Together, these enhance the usefulness of the technique for monitoring the diffuse progression and treatment response of neurological disorders. Copyright © 2014 John Wiley & Sons, Ltd.