ObjectivesThere is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.MethodsThis paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.ResultsResults are presented at family and genus level. The Kullback-Leibler divergence (DKL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average DKL while the V4 gave the lowest (best) average DKL. In addition to having a high DKL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.ConclusionsThe results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.

Background No standard oral assessment tools are available for determining frequency of oral care in critical care patients, and the method of providing oral care is controversial. Objectives To examine the effects of a systematic program of oral care on oral assessment scores in critically ill intubated and nonintubated, patients. Methods Clinical data were collected 3 times during critical care admissions before and after institution of a systematic program of oral care in 3 different medical centers. The oral care education program consisted of instruction from a dentist or dental hygienist and a clear procedure outlining systematic oral care. The Beck Oral Assessment Scale and the mucosal-plaque score were used to assess the oral cavity. Data were analyzed by using linear mixed modeling with controls for severity of illness. Results Scores on the Beck Scale differed significantly (F = 4.79, P = .01) in the pattern of scores across the 3 days and between the control group (before oral education) and the systematic oral care group. Unlike the control group, the treatment group had decreasing scores on the Beck Scale from day 1 to day 5. The mucosal-plaque score and the Beck Scale scores had strong correlations throughout the study; the highest correlation was on day 5 (r = 0.798, P < .001, n = 43). Conclusions Oral assessment scores improved after nurses implemented a protocol for systematic oral care. Use of the Beck Scale and the mucosal-plaque score could standardize oral assessment and guide nurses in providing oral interventions.

Purpose To prospectively compare outcomes and processes of hospital-based early palliative care with standard care in surgical oncology patients (N = 152). Methods A randomized, mixed methods, longitudinal study evaluated the effectiveness of a hospital-based Pain and Palliative Care Service (PPCS). Interviews were conducted presurgically and at follow-up visits up to 1 year. Primary outcome measures included the Gracely Pain Intensity and Unpleasantness Scales and the Symptom Distress Scale. Qualitative interviews assessed social support, satisfaction with care, and communication with providers. Survival analysis methods explored factors related to treatment crossover and study discontinuation. Models for repeated measures within subjects over time explored treatment and covariate effects on patient-reported pain and symptom distress. Results None of the estimated differences achieved statistical significance; however, for those who remained on study for 12 months, the PPCS group performed better than their standard of care counterparts. Patients identified consistent communication, emotional support, and pain and symptom management as positive contributions delivered by the PPCS. Conclusions It is unclear whether lower pain perceptions despite greater symptom distress were clinically meaningful; however, when coupled with the patients’ perceptions of their increased resources and alternatives for pain control, one begins to see the value of an integrated PPCS.

Tooth brushing in critically ill patients has been advocated by many as a standard of care despite the limited evidence to support this practice. Attention has been focused on oral care as the evidence accumulates to support an association between the bacteria in the oral microbiome and those respiratory pathogens that cause pneumonia. It is plausible to assume that respiratory pathogens originating in the oral cavity are aspirated into the lungs, causing infection. A recent study of the effects of a powered toothbrush on the incidence of ventilator-associated pneumonia was stopped early because of a lack of effect in the treatment group. This review summarizes the evidence that supports the effectiveness of tooth brushing in critically ill adults and children receiving mechanical ventilation. Possible reasons for the lack of benefit of tooth brushing demonstrated in clinical trials are discussed. Recommendations for future trials in critically ill patients are suggested. With increased emphasis being placed on oral care, the evidence that supports this intervention must be evaluated carefully.

Purpose/Objectives To identify factors associated with oncology nurses’ use of hazardous drug (HD) safe-handling precautions in inpatient clinical research units. Design Descriptive, cross-sectional. Setting The National Institutes of Health Clinical Center in Bethesda, Maryland. Sample 115 RNs working on high-volume HD administration units. Methods Survey data were collected online using the Hazardous Drug Handling Questionnaire. Data were analyzed using descriptive statistics and multiple regression analysis. Main Research Variables Exposure knowledge, self-efficacy, barriers to personal protective equipment use, perceived risk, conflict of interest, interpersonal influences, workplace safety climate, and total mean HD precaution use. Findings Participants demonstrated high exposure knowledge, self-efficacy, perceived risk, interpersonal influences, and workplace safety climate. Participants demonstrated moderate barriers and conflict of interest. Total mean HD precaution use proved highest during HD administration and lowest for handling excreta at 48 hours. Average patients per day significantly influenced total HD precaution: nurses exhibited more HD precaution use when assigned fewer patients. Conclusions Despite high exposure knowledge, barriers to personal protective equipment use and conflict of interest may contribute to reduced adoption of personal protective practices among oncology nurses. Implications for Nursing Hospital and unit-specific factors captured by the predictor variables could contribute to institutional HD policy.

Background:Music listening may reduce the physiological, emotional, and mental effects of distress and anxiety. It is unclear whether music listening may reduce the amount of opioids used for pain management in critical care, postoperative patients or whether music may improve patient experience in the intensive care unit (ICU).Methods:A total of 41 surgical patients were randomized to either music listening or controlled non-music listening groups on ICU admission. Approximately 50-minute music listening interventions were offered 4 times per day (every 4-6 hours) during the 48 hours of patients’ ICU stays. Pain, distress, and anxiety scores were measured immediately before and after music listening or controlled resting periods. Total opioid intake was recorded every 24 hours and during each intervention.Results:There was no significant difference in pain, opioid intake, distress, or anxiety scores between the control and music listening groups during the first 4 time points of the study. However, a mixed modeling analysis examining the pre- and post-intervention scores at the first time point revealed a significant interaction in the Numeric Rating Scale (NRS) for pain between the music and the control groups (P = .037). The Numeric Rating Score decreased in the music group but remained stable in the control group. Following discharge from the ICU, the music group’s interviews were analyzed for themes.Conclusions:Despite the limited sample size, this study identified music listening as an appropriate intervention that improved patients’ post-intervention experience, according to patients’ self-report. Future mixed methods studies are needed to examine both qualitative patient perspectives and methodology to improve music listening in critical care units.

Background: The oral cavity is associated with local and systemic diseases, although oral samples are not as commonly studied as fecal samples in microbiome research. There is a gap in understanding between the similarities and differences in oral and gut microbiomes and how they may influence each other. Methods: A scoping literature review was conducted comparing oral and gut microbiome communities in healthy humans. Results: Ten manuscripts met inclusion criteria and were examined. The oral microbiome sites demonstrated great variance in differential bacterial abundance and the oral microbiome had higher alpha diversity as compared to the gut microbiome. Studies using 16S rRNA sequencing analysis resulted in overall community differences between the oral and gut microbiomes when beta diversity was analyzed. Shotgun metagenomics sequencing increased taxonomic resolution to strain level (intraspecies) and demonstrated a greater percentage of shared taxonomy and oral bacterial translocation to the gut microbiome community. Discussion: The oral and gut microbiome bacterial communities may be more similar than earlier research has suggested, when species strain is analyzed through shotgun metagenomics sequencing. The association between oral health and systemic diseases has been widely reported but many mechanisms underlying this relationship are unknown. Although future research is needed, the oral microbiome may be a novel interventional target through its downstream effects on the gut microbiome. As nurse scientists are experts in symptom characterization and phenotyping of patients, they are also well posed to lead research on the connection of the oral microbiome to the gut microbiome in health and disease.

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