Category: Nevin Manimala

Braz J Biol. 2022 May 9;84:e256132. doi: 10.1590/1519-6984.256132. eCollection 2022.

ABSTRACT

The aim of this study is to determine the association between environmental organic pollutants with type 2 diabetes. This prospective study was conducted in Federal Urdu University of Arts, Science and Technology (FUUAST) Gulshan-e-Iqbal Campus Karachi in duration from January 2016 to June 2017. This study was ethically approved from the Institutional Review Board of FUUAST. The study included 50 male and female convenient subjects with type 2 diabetes. Subject with other type of diabetes was excluded. Consent was obtained by each individual. Self-structured questionnaire was used for data collection. The comparative results suggest that the maximum level of summation polychlorinated biphenyls (PCBs) mean value was found in age group 27-33 as 0.695 mg/kg in 73% having total individual eleven. Median (interquartile range) of pesticides levels among subjects with normal weight, over weight and obesity were 0.49 (0.26-2.13), 1.53 (0.60-2.65), and 1.60 (1.23-2.05) respectively. It was observed that Organochlorine pesticides (OCS) levels of subjects with overweight and obesity were almost similar (P-value > 0.05) but significantly higher as compared to subjects with normal weight (P-value < 0.05). No significant differences were observed between PCB levels of subjects in terms of body mass index (BMI). In present study we trace the important elements involve in the deposition of persistent organic pollutants and established an association between pollutants with etiology of diabetes and associated disorders such as obesity.

PMID:35544786 | DOI:10.1590/1519-6984.256132

Wound Manag Prev. 2022 Apr;68(4):34-43.

ABSTRACT

BACKGROUND: Surgical site infections (SSIs) can occur after colorectal surgery. Ionic silver has been used to prevent the development of SSIs. New-generation dressings, defined as total occlusive ionic silver-containing dressings, have been shown to reduce bacterial colonization in SSIs.

PURPOSE: To evalute the effect of a silver hydrofiber dressing on the development of SSIs at the abdominal incision after ostomy closure.

METHODS: There was a total of 37 eligible patients who underwent temporary ostomy closure. Five patients required an associated intervention during ostomy closure and were excluded. One patient was lost to follow-up. Hence, 32 patients were included in the study. Silver-containing occlusive dressings and conventional dressings were used in patients who underwent ostomy closure. In the control group (n = 16), the wound area was covered with a standard sterile gauze dressing for 24 to 48 hours, and then wound cleansing was performed with 10% povidone iodine, followed by daily dressing replacement with sterile gauze for 5 days. The patients in the study group (n = 16) were treated with a silver-containing hydrofiber dressing, which was not changed for 5 days following application in the operating room.

RESULTS: At the end of the 30-day follow-up period, no SSIs were observed in the study group. When the dressing methods applied to the patient groups with and without SSIs were compared, SSIs developed at a higher rate in the control group (n = 4; 26.7%) compared with the study group (n = 0); this result was statistically significant (P = .043).

CONCLUSIONS: In this study, the use of a wound care product containing ionic silver reduced the rate of SSIs related to ostomy closure. Multicenter, randomized, clinical studies involving a larger number of patients are needed. In addition, occlusive wound dressings with and without silver should be investigated in further studies.

PMID:35544780

J Proteome Res. 2022 May 11. doi: 10.1021/acs.jproteome.2c00137. Online ahead of print.

ABSTRACT

The yeast, Saccharomyces cerevisiae, is a widely used model system for investigating conserved biological functions and pathways. Advancements in sample multiplexing have facilitated the study of the yeast proteome, yet many yeast proteins remain uncharacterized or only partially characterized. Yeast deletion strain collections are powerful resources for yeast proteome studies, uncovering the effects of gene function, genetic interactions, and cellular stresses. As complex biological systems cannot be understood by simply analyzing the individual components, a systems approach is often required in which a protein is represented as a component of large, interacting networks. Here, we evaluate the current state of yeast proteome analysis using isobaric tag-based sample multiplexing (TMTpro16) to profile the proteomes of 75 yeast deletion strains for which we measured the abundance of nearly 5000 proteins. Using statistical approaches, we highlighted covariance and regulation subnetworks and the enrichment of gene ontology classifications for covarying and coregulated proteins. This dataset presents a resource that is amenable to further data mining to study individual deletion strains, pathways, proteins, and/or interactions thereof while serving as a template for future network-based investigations using yeast deletion strain collections.

PMID:35544774 | DOI:10.1021/acs.jproteome.2c00137

Qual Manag Health Care. 2022 May 10. doi: 10.1097/QMH.0000000000000330. Online ahead of print.

ABSTRACT

BACKGROUND: Unanticipated adverse events could harm not only patients and families but also health care professionals. These people are defined as second victims. Second victim distress (SVD) refers to physical, emotional, and professional problems of health care professionals. While positive patient safety cultures (PSCs) are associated with reducing severity of SVD, there is a dearth of research on the association between PSCs and SVD and the mediation effects in those associations.

OBJECTIVES: The purpose of this study was to explore the associations between PSCs and SVD and verify the multiple mediation effects of colleague, supervisor, and institutional supports.

METHODS: A cross-sectional study using a self-report questionnaire was conducted among 296 nurses in South Korea. The participants were selected by quota sampling in 41 departments including general wards, intensive care units, etc. Descriptive statistics, Pearson’s correlation, multiple linear regression, and multiple mediation analysis were conducted using SPSS 25.0 and the PROCESS macros.

RESULTS: Nonpunitive response to errors, communication openness, and colleague, supervisor, and institutional supports had negative correlations with SVD (Ps < .05). In the multiple mediation model, a nonpunitive response to error showed a significant direct effect on SVD (direct effect β = -.26, P < .001). Colleague, supervisor, and institutional supports showed a significant indirect effect between nonpunitive response to error and SVD; colleague (indirect effect β [Boot LLCI-Boot ULCI] = -.03 [-0.06 to -0.00]), supervisor (.03[0.00 to 0.07]), and institutional support (-.04 [-0.07 to -0.01]).

CONCLUSION: The study suggests that establishing nonpunitive organizational cultures is an effective strategy to reduce SVD. The findings highlight the importance of promoting programs that strengthen PSCs in hospitals and prioritizing support resources to reduce SVD among nurses.

PMID:35544767 | DOI:10.1097/QMH.0000000000000330

JMIR Mhealth Uhealth. 2022 May 11;10(5):e15719. doi: 10.2196/15719.

ABSTRACT

BACKGROUND: The prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective.

OBJECTIVE: The aim of this study was to identify existing obesity-related mHealth apps in India and evaluate the potential of the apps’ contents to promote health behavior change. This study also aimed to discover the general quality of obesity-related mHealth apps.

METHODS: A systematic search for obesity-related mHealth apps was conducted in both the Google Play Store and the Apple App Store. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) and the potential of the sample apps’ contents to promote health behavior change was assessed using the PRECEDE-PROCEED Model (PPM).

RESULTS: A total of 13 apps (11 from the Google Play Store and 2 from the Apple App Store) were considered eligible for the study. The general quality of the 13 apps assessed using MARS resulted in mean scores ranging from 1.8 to 3.7. The bivariate Pearson correlation between the MARS rating and app user rating failed to establish statistically significant results. The multivariate regression analysis result indicated that the PPM factors are significant determinants of health behavior change (F_3,9=63.186; P<.001) and 95.5% of the variance (R²=0.955; P<.001) in the dependent variable (health behavior change) can be explained by the independent variables (PPM factors).

CONCLUSIONS: In general, mHealth apps are found to be more effective when they are based on theory. The presence of PPM factors in an mHealth app can greatly influence the likelihood of health behavior change among users. So, we suggest mHealth app developers consider this to develop efficient apps. Also, mHealth app developers should consider providing health information from credible sources and indicating the sources of the information, which will increase the perceived credibility of the apps among the users. We strongly recommend health professionals and health organizations be involved in the development of mHealth apps. Future research should include mHealth app users to understand better the apps’ effectiveness in bringing about health behavior change.

PMID:35544318 | DOI:10.2196/15719

J Adolesc Young Adult Oncol. 2022 May 11. doi: 10.1089/jayao.2021.0223. Online ahead of print.

ABSTRACT

Purpose: To describe the cancer incidence burden and trends among adolescent and young adults (AYAs) in Alberta, Canada over a 35-year period. Methods: We obtained data from the Alberta Cancer Registry on all first primary cancers, excluding non-melanoma skin cancer, diagnosed at ages 15-39 years among residents in Alberta from 1983 to 2017. Cancers were classified by using Barr’s AYA cancer classification system. Age-standardized incidence rates (ASIR) and the average annual percentage change (AAPC) in incidence rates were calculated. Statistically significant changes in the AAPC during the study period were assessed using Joinpoint regression. Results: Overall, 23,652 incident cases of AYA cancer were diagnosed in Alberta. Females accounted for ∼60% of the diagnoses. AYA cancer increased significantly over the study period overall (AAPC: 0.5%; 95%CI: 0.3%-0.7%), for each sex (AAPC_male: 0.7%; 95%CI: 0.4%-0.9%; AAPC_female: 0.4%; 95%CI: 0.2%-0.6%), and among male and female 20-39 year-olds. Although statistically significant increases were observed in 11 out of 29 cancer sites for at least a portion of the study period, with significant AAPCs ranging from 0.8% (95%CI: 0.01%-1.5%) to 6.6% (95%CI: 4.6%-8.5%), the main driver was thyroid cancer (AAPC: 3.7%; 95%CI: 3.2%-4.2%). Statistically significant decreases were observed for six cancer sites, with AAPCs ranging from -6.4% (95%CI: -8.7% to -4.1%) to -1.1% (95%CI: -1.8% to -0.5%). Conclusions: There is a growing cancer burden among AYAs in Alberta, which is driven primarily by thyroid cancer and early-onset cancers in males. These results highlight the need for etiological studies and tertiary strategies to prevent and mitigate morbidity and mortality in the AYA population.

PMID:35544316 | DOI:10.1089/jayao.2021.0223

JMIR Form Res. 2022 May 11;6(5):e37737. doi: 10.2196/37737.

ABSTRACT

BACKGROUND: Chinese immigrants bear a high diabetes burden and face significant barriers to accessing diabetes self-management education (DSME) and counseling programs.

OBJECTIVE: The goal of this study was to examine the feasibility and acceptability and to pilot test the potential efficacy of a social media-based DSME intervention among low-income Chinese immigrants with type 2 diabetes (T2D) in New York City.

METHODS: This was a single group pretest and posttest study in 30 Chinese immigrants with T2D. The intervention included 24 culturally and linguistically tailored DSME videos, focusing on diabetes education and behavioral counseling techniques. Over 12 weeks, participants received 2 brief videos each week via WeChat, a free social media app popular among Chinese immigrants. Primary outcomes included the feasibility and acceptability of the intervention. Feasibility was evaluated by recruitment processes, retention rates, and the video watch rate. Acceptability was assessed via a satisfaction survey at 3 months. Secondary outcomes, that is, hemoglobin A_1c (HbA_1c), self-efficacy, dietary intake, and physical activity, were measured at baseline, 3 months, and 6 months. Descriptive statistics and paired 2-sided t tests were used to summarize the baseline characteristics and changes before and after the intervention.

RESULTS: The sample population (N=30) consisted of mostly females (21/30, 70%) who were married (19/30, 63%), with limited English proficiency (30/30, 100%), and the mean age was 61 (SD 7) years. Most reported an annual household income of <US $25,000 (24/30, 80%) and a high school education or less (19/30, 63%). Thirty participants were recruited within 2 months (January and February 2020), and 97% (29/30) of the participants were retained at 6 months. A video watch rate of 92% (28/30) was achieved. The mean baseline HbA_1c level was 7.3% (SD 1.3%), and this level declined by 0.5% (95% CI -0.8% to -0.2%; P=.003) at 6 months. The mean satisfaction score was 9.9 (SD 0.6) out of 10, indicating a high level of satisfaction with the program. All strongly agreed or agreed that they preferred this video-based DSME over face-to-face visits. Compared to baseline, there were significant improvements in self-efficacy, dietary, and physical activity behaviors at 6 months.

CONCLUSIONS: This pilot study demonstrated that a social media-based DSME intervention is feasible, acceptable, and potentially efficacious in a low-income Chinese immigrant population with T2D. Future studies need to examine the efficacy in an adequately powered clinical trial.

PMID:35544298 | DOI:10.2196/37737

JAMA Psychiatry. 2022 May 11. doi: 10.1001/jamapsychiatry.2022.1067. Online ahead of print.

ABSTRACT

IMPORTANCE: Individuals surviving severe COVID-19 may be at increased risk of neuropsychiatric sequelae. Robust assessment of these risks may help improve clinical understanding of the post-COVID syndrome, aid clinical care during the ongoing pandemic, and inform postpandemic planning.

OBJECTIVE: To quantify the risks of new-onset neuropsychiatric conditions and new neuropsychiatric medication prescriptions after discharge from a COVID-19-related hospitalization, and to compare these with risks after discharge from hospitalization for other severe acute respiratory infections (SARI) during the COVID-19 pandemic.

DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, adults (≥18 years of age) were identified from QResearch primary care and linked electronic health record databases, including national SARS-CoV-2 testing, hospital episode statistics, intensive care admissions data, and mortality registers in England, from January 24, 2020, to July 7, 2021.

EXPOSURES: COVID-19-related or SARI-related hospital admission (including intensive care admission).

MAIN OUTCOMES AND MEASURES: New-onset diagnoses of neuropsychiatric conditions (anxiety, dementia, psychosis, depression, bipolar disorder) or first prescription for relevant medications (antidepressants, hypnotics/anxiolytics, antipsychotics) during 12 months of follow-up from hospital discharge. Maximally adjusted hazard ratios (HR) with 95% CIs were estimated using flexible parametric survival models.

RESULTS: In this cohort study of data from 8.38 million adults (4.18 million women, 4.20 million men; mean [SD] age 49.18 [18.45] years); 16 679 (0.02%) survived a hospital admission for SARI, and 32 525 (0.03%) survived a hospital admission for COVID-19. Compared with the remaining population, survivors of SARI and COVID-19 hospitalization had higher risks of subsequent neuropsychiatric diagnoses. For example, the HR for anxiety in survivors of SARI was 1.86 (95% CI, 1.56-2.21) and for survivors of COVID-19 infection was 2.36 (95% CI, 2.03-2.74); the HR for dementia for survivors of SARI was 2.55 (95% CI, 2.17-3.00) and for survivors of COVID-19 infection was 2.63 (95% CI, 2.21-3.14). Similar findings were observed for all medications analyzed; for example, the HR for first prescriptions of antidepressants in survivors of SARI was 2.55 (95% CI, 2.24-2.90) and for survivors of COVID-19 infection was 3.24 (95% CI, 2.91-3.61). There were no significant differences observed when directly comparing the COVID-19 group with the SARI group apart from a lower risk of antipsychotic prescriptions in the former (HR, 0.80; 95% CI, 0.69-0.92).

CONCLUSIONS AND RELEVANCE: In this cohort study, the neuropsychiatric sequelae of severe COVID-19 infection were found to be similar to those for other SARI. This finding may inform postdischarge support for people surviving SARI.

PMID:35544272 | DOI:10.1001/jamapsychiatry.2022.1067

JMIR Res Protoc. 2022 May 11;11(5):e37092. doi: 10.2196/37092.

ABSTRACT

BACKGROUND: Hip and knee osteoarthritis is substantially prevalent worldwide, with large numbers of older adults undergoing joint replacement (arthroplasty) every year. A backlog of elective surgery due to the COVID-19 pandemic, and an aging population, has led to substantial issues with access to timely arthroplasty surgery. A potential method to improve the efficiency of arthroplasty services is by increasing the percentage of patients who are listed for surgery from primary care referrals. The use of artificial intelligence (AI) techniques, specifically machine learning, provides a potential unexplored solution to correctly and rapidly select suitable patients for arthroplasty surgery.

OBJECTIVE: This study has 2 objectives: (1) develop a cohort of patients with referrals by general practitioners regarding assessment of suitability for hip or knee replacement from National Health Service (NHS) Grampian data via the Grampian Data Safe Haven and (2) determine the demographic, clinical, and imaging characteristics that influence the selection of patients to undergo hip or knee arthroplasty, and develop a tested and validated patient-specific predictive model to guide arthroplasty referral pathways.

METHODS: The AI to Revolutionise the Patient Care Pathway in Hip and Knee Arthroplasty (ARCHERY) project will be delivered through 2 linked work packages conducted within the Grampian Data Safe Haven and Safe Haven Artificial Intelligence Platform. The data set will include a cohort of individuals aged ≥16 years with referrals for the consideration of elective primary hip or knee replacement from January 2015 to January 2022. Linked pseudo-anonymized NHS Grampian health care data will be acquired including patient demographics, medication records, laboratory data, theatre records, text from clinical letters, and radiological images and reports. Following the creation of the data set, machine learning techniques will be used to develop pattern classification and probabilistic prediction models based on radiological images. Supplemental demographic and clinical data will be used to improve the predictive capabilities of the models. The sample size is predicted to be approximately 2000 patients-a sufficient size for satisfactory assessment of the primary outcome. Cross-validation will be used for development, testing, and internal validation. Evaluation will be performed through standard techniques, such as the C statistic (area under curve) metric, calibration characteristics (Brier score), and a confusion matrix.

RESULTS: The study was funded by the Chief Scientist Office Scotland as part of a Clinical Research Fellowship that runs from August 2021 to August 2024. Approval from the North Node Privacy Advisory Committee was confirmed on October 13, 2021. Data collection started in May 2022, with the results expected to be published in the first quarter of 2024. ISRCTN registration has been completed.

CONCLUSIONS: This project provides a first step toward delivering an automated solution for arthroplasty selection using routinely collected health care data. Following appropriate external validation and clinical testing, this project could substantially improve the proportion of referred patients that are selected to undergo surgery, with a subsequent reduction in waiting time for arthroplasty appointments.

TRIAL REGISTRATION: ISRCTN Registry ISRCTN18398037; https://www.isrctn.com/ISRCTN18398037.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37092.

PMID:35544289 | DOI:10.2196/37092

Turk J Anaesthesiol Reanim. 2022 Apr;50(2):135-141. doi: 10.5152/TJAR.2021.1356.

ABSTRACT

OBJECTIVE: Arterial pulse-derived cardiac output monitors are routinely employed to guide hemodynamic management during liver transplant surgery. In this study, we sought to assess the reliability by evaluating the agreement of the cardiac output measured by the FloTrac Vigileo versus pulmonary artery catheter (continuous cardiac output) at specified times during liver transplant.

METHODS: Liver transplant database with cardiac output values measured by FloTrac Vigileo and continuous cardiac output was analyzed retrospectively at a tertiary care hospital. Data were compared at T0: baseline, T1: 1 hour in dissection phase, T2: anhepatic phase, T3: portosystemic shunt, T4: reperfusion, T5: 1 hour after reperfusion, and T6: skin closure. Statistical analysis was done using Bland-Altman analysis and percentage error (<30%) to assess the agreement between cardiac output measured by 2 techniques, Lin’s concordance correlation coefficient for quantifying the agreement and 4-quadrant plots to compare the trends of cardiac output.

RESULTS: Bland-Altman analysis showed mean cardiac output ± standard deviation L min-1 (95% CI) at T0: 0.2 ± 2.09 (-3.9 to 4.3), T1: 0.53 ± 3.0 (-5.4 to 6.4), T2: 0.47 ± 2.1(-3.7 to 4.6), T3: 0.31 ± 1.9 (-3.4 to 4.0), T4: 0.44 ± 2.15 (-3.8 to 4.7), T 5:0.69 ± 1.9. (-2.9 to 4.3), and at T6: 0.43 ± 2.25 (-4.0 to 4.8). Percentage error was 44%-72% and concordance correlation coefficient was poor (<0.65) at all points.

CONCLUSIONS: There is poor agreement between the cardiac output measured by FloTrac and pulmonary artery catheter among liver transplant recipients. The need for superior hemodynamic monitoring is mandated in liver transplant.

PMID:35544253 | DOI:10.5152/TJAR.2021.1356