Category: Statistics

JMIR Hum Factors. 2023 Jul 25;10:e42993. doi: 10.2196/42993.

ABSTRACT

BACKGROUND: Highly personalized care is substantially improved by technology platforms that assess and track patient outcomes. However, evidence regarding how to successfully implement technology in real-world mental health settings is limited.

OBJECTIVE: This study aimed to naturalistically monitor how a health information technology (HIT) platform was used within 2 real-world mental health service settings to gain practical insights into how HIT can be implemented and sustained to improve mental health service delivery.

METHODS: An HIT (The Innowell Platform) was naturally implemented in 2 youth mental health services in Sydney, Australia. Web-based surveys (n=19) and implementation logs were used to investigate staff attitudes toward technology before and after implementation. Descriptive statistics were used to track staff attitudes over time, whereas qualitative thematic analysis was used to explore implementation log data to gain practical insights into useful implementation strategies in real-world settings.

RESULTS: After the implementation, the staff were nearly 3 times more likely to agree that the HIT would improve care for their clients (3/12, 25% agreed before the implementation compared with 7/10, 70% after the implementation). Despite this, there was also an increase in the number of staff who disagreed that the HIT would improve care (from 1/12, 8% to 2/10, 20%). There was also decreased uncertainty (from 6/12, 50% to 3/10, 30%) about the willingness of the service to implement the technology for its intended purpose, with similar increases in the number of staff who agreed and disagreed with this statement. Staff were more likely to be uncertain about whether colleagues in my service are receptive to changes in clinical processes (not sure rose from 5/12, 42% to 7/10, 70%). They were also more likely to report that their service already provides the best mental health care (agreement rose from 7/12, 58% to 8/10, 80%). After the implementation, a greater proportion of participants reported that the HIT enabled shared or collaborative decision-making with young people (2/10, 20%, compared with 1/12, 8%), enabled clients to proactively work on their mental health care through digital technologies (3/10, 30%, compared with 2/12, 16%), and improved their response to suicidal risk (4/10, 40% compared with 3/12, 25%).

CONCLUSIONS: This study raises important questions about why clinicians, who have the same training and support in using technology, develop more polarized opinions on its usefulness after implementation. It seems that the uptake of HIT is heavily influenced by a clinician’s underlying beliefs and attitudes toward clinical practice in general as well as the role of technology, rather than their knowledge or the ease of use of the HIT in question.

PMID:37490321 | DOI:10.2196/42993

J Med Internet Res. 2023 Jul 25;25:e46026. doi: 10.2196/46026.

ABSTRACT

BACKGROUND: Some of the most vexing issues with the COVID-19 pandemic were the inability of facilities and events, such as schools and work areas, to track symptoms to mitigate the spread of the disease. To combat these challenges, many turned to the implementation of technology. Technology solutions to mitigate repercussions of the COVID-19 pandemic include tools that provide guidelines and interfaces to influence behavior, reduce exposure to the disease, and enable policy-driven avenues to return to a sense of normalcy. This paper presents the implementation and early evaluation of a return-to-work COVID-19 symptom and risk assessment tool. The system was implemented across 34 institutions of health and education in Alabama, including more than 174,000 users with over 4 million total uses and more than 86,000 reports of exposure risk between July 2020 and April 2021.

OBJECTIVE: This study aimed to explore the usage of technology, specifically a COVID-19 symptom and risk assessment tool, to mitigate exposure to COVID-19 within public spaces. More specifically, the objective was to assess the relationship between user-reported symptoms and exposure via a mobile health app, with confirmed COVID-19 cases reported by the Alabama Department of Public Health (ADPH).

METHODS: This cross-sectional study evaluated the relationship between confirmed COVID-19 cases and user-reported COVID-19 symptoms and exposure reported through the Healthcheck web-based mobile application. A dependent variable for confirmed COVID-19 cases in Alabama was obtained from ADPH. Independent variables (ie, health symptoms and exposure) were collected through Healthcheck survey data and included measures assessing COVID-19-related risk levels and symptoms. Multiple linear regression was used to examine the relationship between ADPH-confirmed diagnosis of COVID-19 and self-reported health symptoms and exposure via Healthcheck that were analyzed across the state population but not connected at the individual patient level.

RESULTS: Regression analysis showed that the self-reported information collected by Healthcheck significantly affects the number of COVID-19-confirmed cases. The results demonstrate that the average number of confirmed COVID-19 cases increased by 5 (high risk: β=5.10; P=.001), decreased by 24 (sore throat: β=-24.03; P=.001), and increased by 21 (nausea or vomiting: β=21.67; P=.02) per day for every additional self-report of symptoms by Healthcheck survey respondents. Congestion or runny nose was the most frequently reported symptom. Sore throat, low risk, high risk, nausea, or vomiting were all statistically significant factors.

CONCLUSIONS: The use of technology allowed organizations to remotely track a population as it is related to COVID-19. Healthcheck was a platform that aided in symptom tracking, risk assessment, and evaluation of status for admitting individuals into public spaces for people in the Alabama area. The confirmed relationship between symptom and exposure self-reporting using an app and population-wide confirmed cases suggests that further investigation is needed to determine the opportunity for such apps to mitigate disease spread at a community and individual level.

PMID:37490320 | DOI:10.2196/46026

JMIR Hum Factors. 2023 Jul 25;10:e46044. doi: 10.2196/46044.

ABSTRACT

BACKGROUND: Patient portals can facilitate patient engagement in care management. Driven by national efforts over the past decade, patient portals are being implemented by hospitals and clinics nationwide. Continuous evaluation of patient portals and reflection of feedback from end users across care settings are needed to make patient portals more user-centered after the implementation.

OBJECTIVE: The aim of this study was to investigate the lived experience of using a patient portal in adult patients recruited from a variety of care settings, focusing on their perceived benefits and difficulties of using the patient portal, and trust and concerns about privacy and security.

METHODS: This qualitative descriptive study was part of a cross-sectional digital survey research to examine the comprehensive experience of using a patient portal in adult patients recruited from 20 care settings from hospitals and clinics of a large integrated health care system in the mid-Atlantic area of the United States. Those who had used a patient portal offered by the health care system in the past 12 months were eligible to participate in the survey. Data collected from 734 patients were subjected to descriptive statistics and content analysis.

RESULTS: The majority of the participants were female and non-Hispanic White with a mean age of 53.1 (SD 15.34) years. Content analysis of 1589 qualitative comments identified 22 themes across 4 topics: beneficial aspects (6 themes) and difficulties (7 themes) in using the patient portal; trust (5 themes) and concerns (4 themes) about privacy and security of the patient portal. Most of the participants perceived the patient portal functions as beneficial for communicating with health care teams and monitoring health status and care activities. At the same time, about a quarter of them shared difficulties they experienced while using those functions, including not getting eMessage responses timely and difficulty finding information in the portal. Protected log-in process and trust in health care providers were the most mentioned reasons for trusting privacy and security of the patient portal. The most mentioned reason for concerns about privacy and security was the risk of data breaches such as hacking attacks and identity theft.

CONCLUSIONS: This study provides an empirical understanding of the lived experience of using a patient portal in adult patient users across care settings with a focus on the beneficial aspects and difficulties in using the patient portal, and trust and concerns about privacy and security. Our study findings can serve as a valuable reference for health care institutions and software companies to implement more user-centered, secure, and private patient portals. Future studies may consider targeting other patient portal programs and patients with infrequent or nonuse of patient portals.

PMID:37490316 | DOI:10.2196/46044

JAMA Netw Open. 2023 Jul 3;6(7):e2325658. doi: 10.1001/jamanetworkopen.2023.25658.

ABSTRACT

IMPORTANCE: Plant-based diets are known to improve cardiometabolic risk in the general population, but their effects on people at high risk of cardiovascular diseases (CVDs) remain inconclusive.

OBJECTIVE: To assess the association of vegetarian diets with major cardiometabolic risk factors, including low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c (HbA1c), systolic blood pressure (SBP), and body weight in people with or at high risk of CVDs.

DATA SOURCES: This meta-analysis was registered before the study was conducted. Systematic searches performed included Embase, MEDLINE, CINAHL, and CENTRAL from inception until July 31, 2021.

STUDY SELECTION: Eligible randomized clinical trials (RCTs) that delivered vegetarian diets in adults with or at high risk of CVDs and measured LDL-C, HbA1c or SBP were included. Of the 7871 records screened, 29 (0.4%; 20 studies) met inclusion criteria.

DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data including demographics, study design, sample size, and diet description, and performed risk of bias assessment. A random-effects model was used to assess mean changes in LDL-C, HbA1c, SBP, and body weight. The overall certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool.

MAIN OUTCOMES AND MEASURES: Mean differences between groups in changes (preintervention vs postintervention) of LDL-C, HbA1c, and SBP; secondary outcomes were changes in body weight and energy intake.

RESULTS: Twenty RCTs involving 1878 participants (range of mean age, 28-64 years) were included, and mean duration of intervention was 25.4 weeks (range, 2 to 24 months). Four studies targeted people with CVDs, 7 focused on diabetes, and 9 included people with at least 2 CVD risk factors. Overall, relative to all comparison diets, meta-analyses showed that consuming vegetarian diets for an average of 6 months was associated with decreased LDL-C, HbA1c, and body weight by 6.6 mg/dL (95% CI, -10.1 to -3.1), 0.24% (95% CI, -0.40 to -0.07), and 3.4 kg (95% CI, -4.9 to -2.0), respectively, but the association with SBP was not significant (-0.1 mm Hg; 95% CI, -2.8 to 2.6). The GRADE assessment showed a moderate level of evidence for LDL-C and HbA1c reduction.

CONCLUSIONS AND RELEVANCE: In this study, consuming a vegetarian diet was associated with significant improvements in LDL-C, HbA1c and body weight beyond standard therapy in individuals at high risk of CVDs. Additional high-quality trials are warranted to further elucidate the effects of healthy plant-based diets in people with CVDs.

PMID:37490288 | DOI:10.1001/jamanetworkopen.2023.25658

Cancer Epidemiol Biomarkers Prev. 2023 Jul 25:EPI-23-0340. doi: 10.1158/1055-9965.EPI-23-0340. Online ahead of print.

ABSTRACT

BACKGROUND: Antibiotics use is associated with higher colorectal cancer risk, but little is known regarding any potential effects on survival.

METHODS: We conducted a nationwide cohort study, using complete-population data from Swedish national registers between 2005 and 2020, to investigate prediagnostic prescription antibiotics use in relation to survival in colorectal cancer patients.

RESULTS: We identified 36 061 stage I-III and 11 242 stage IV colorectal cancer cases diagnosed between 2010 and 2019. For stage I-III, any antibiotics use (binary yes/no variable) was not associated with overall or cancer-specific survival. Compared to no use, moderate antibiotics use (total 11-60 days) was associated with slightly better cancer-specific survival (adjusted hazard ratio (aHR) = 0.93, 95% confidence interval (CI) 0.86-0.99), whereas very high use (>180 days) was associated with worse survival (overall survival aHR = 1.42, 95% CI 1.26-1.60, cancer-specific survival aHR =1.31, 95% CI 1.10-1.55). In analyses by different antibiotic types, although not statistically significant, worse survival outcomes were generally observed across several antibiotics, particularly macrolides and/or lincosamides. In stage IV colorectal cancer, inverse relationships between antibiotics use and survival were noted.

CONCLUSIONS: Overall, our findings do not support any substantial detrimental effects of prediagnostic prescription antibiotics use on cancer-specific survival after colorectal cancer diagnosis, with the possible exception of very high use in stage I-III colorectal cancer. Further investigation is warranted to confirm and understand these results.

IMPACT: Although the study findings require confirmation, physicians probably do not need to factor in prediagnostic prescription antibiotics use in prognosticating colorectal cancer patients.

PMID:37490284 | DOI:10.1158/1055-9965.EPI-23-0340

J Nephrol. 2023 Jul 25. doi: 10.1007/s40620-023-01708-7. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of this study was to evaluate the efficacy and safety of COVID-19 vaccines in patients undergoing haemodialysis in Italy compared to the general population.

METHODS: In this cohort study, 118 dialysis centres from 18 Italian Regions participated. Individuals older than 16 years on dialysis treatment for at least 3 months, who provided informed consent were included. We collected demographic and clinical information, as well as data on vaccination status, hospitalisations, access to intensive care units and adverse events. We calculated the incidence, hospitalisation, mortality, and fatality rates in the vaccinated dialysis cohort, adjusted for several covariates. The incidence rates of infection in the dialysis cohort and the general population were compared through Standardised Incidence Rate Ratio.

RESULTS: The study included 6555 patients vaccinated against SARS-CoV-2 infection according to the schedule recommended in Italy. Between March 2021 and May 2022, there were 1096 cases of SARS-CoV-2 infection, with an incidence rate after completion of the three-dose vaccination cycle of 37.7 cases per 100 person-years. Compared to the general population, we observed a 14% reduction in the risk of infection for patients who received three vaccine doses (Standardised Incidence Rate Ratio: 0.86; 95% Confidence Interval: 0.81-0.91), whereas no statistically significant differences were found for COVID-19-related hospitalisations, intensive care unit admissions or death. No safety signals emerged from the reported adverse events.

CONCLUSIONS: The vaccination program against SARS-CoV-2 in the haemodialysis population showed an effectiveness and safety profile comparable to that seen in the general population.

PMID:37490271 | DOI:10.1007/s40620-023-01708-7

Endocrine. 2023 Jul 25. doi: 10.1007/s12020-023-03455-y. Online ahead of print.

ABSTRACT

BACKGROUND: Familial papillary thyroid microcarcinoma (FPTMC) appears to be more aggressive than sporadic papillary thyroid microcarcinoma (SPTMC). However, there are authors who indicate that unicentric FPTMC has a similar prognosis to SPTMC. The objective is to analyze whether unicentric FPTMC has a better prognosis than multicentric FPTMC.

DESIGN AND METHODS: Type of study: National multicenter longitudinal analytical observational study.

STUDY POPULATION: Patients with FPTMC.

STUDY GROUPS: Two groups were compared: Group A (unicentric FPTMC) vs. Group B (multicentric FPTMC).

STUDY VARIABLES: It is analyzed whether between the groups there are: a) differentiating characteristics; and b) prognostic differences.

STATISTICAL ANALYSIS: Cox regression analysis and survival analysis.

RESULTS: Ninety-four patients were included, 44% (n = 41) with unicentric FPTMC and 56% (n = 53) with multicentric FPTMC. No differences were observed between the groups according to socio-familial, clinical or histological variables. In the group B a more aggressive treatment was performed, with higher frequency of total thyroidectomy (99 vs. 78%; p = 0.003), lymph node dissection (41 vs. 15%; p = 0.005) and therapy with radioactive iodine (96 vs. 73%; p = 0.002). Tumor stage was similar in both groups (p = 0.237), with a higher number of T3 cases in the group B (24 vs. 5%; p = 0.009). After a mean follow-up of 90 ± 68.95 months, the oncological results were similar, with a similar disease persistence rate (9 vs. 5%; p = 0.337), disease recurrence rate (21 vs. 8%; p = 0.159) and disease-free survival (p = 0.075).

CONCLUSIONS: Unicentric FPTMC should not be considered as a SPTMC due to its prognosis is similar to multicentric FPTMC.

PMID:37490266 | DOI:10.1007/s12020-023-03455-y

Psychiatr Q. 2023 Jul 25. doi: 10.1007/s11126-023-10044-9. Online ahead of print.

ABSTRACT

Major depression is a frequent condition which variably responds to treatment. In view of its high prevalence, the presence of treatment resistance in major depression significantly impacts on quality of life. Tailoring pharmacological treatment based on genetic polymorphisms is a current trend to personalizing pharmacological treatment in patients with major depressive disorders. Current guidelines for the use of genetic tests in major depression issued by the Clinical Pharmacogenomics Implementation Consortium (CPIC) are based on CYP2D6 and CYP2C19 polymorphisms which constitute the strongest evidence for pharmacogenomic guided treatment. There is evidence of increased clinical response to pharmacological treatment in major depression although largely in non-treatment resistant patients from Western countries. In this study, well characterised participants (N = 15) with complex, largely treatment resistant unipolar major depression were investigated, and clinical improvement was measured at baseline and at week-8 after the pharmacogenomics-guided treatment with the Montgomery Åsberg Depression Rating Scale (MÅDRS). Results suggested a statistically significant improvement (p = 0.01) of 16% at endpoint in the whole group and a larger effect in case of changes in medication regime (28%, p = 0.004). This small but appreciable effect can be understood in the context of the level of treatment resistance in the group. To our knowledge, this is the first study from the Middle East demonstrating the feasibility of this approach in the treatment of complex major depressive disorders.

PMID:37490261 | DOI:10.1007/s11126-023-10044-9

Mycopathologia. 2023 Jul 25. doi: 10.1007/s11046-023-00770-w. Online ahead of print.

ABSTRACT

BACKGROUND: Sudden upsurge in cases of COVID-19 Associated Mucormycosis (CAM) following the second wave of the COVID-19 pandemic was recorded in India. This study describes the clinical characteristics, management and outcomes of CAM cases, and factors associated with mortality.

METHODS: Microbiologically confirmed CAM cases were enrolled from April 2021 to September 2021 from ten diverse geographical locations in India. Data were collected using a structured questionnaire and entered into a web portal designed specifically for this investigation. Bivariate analyses and logistic regression were conducted using R version 4.0.2.

RESULTS: A total of 336 CAM patients were enrolled; the majority were male (n = 232, 69.1%), literate (n = 261, 77.7%), and employed (n = 224, 66.7%). The commonest presenting symptoms in our cohort of patients were oro-facial and ophthalmological in nature. The median (Interquartile Range; IQR) interval between COVID diagnosis and admission due to mucormycosis was 31 (18, 47) days, whereas the median duration of symptoms of CAM before hospitalization was 10 (5, 20) days. All CAM cases received antifungal treatment, and debridement (either surgical or endoscopic or both) was carried out in the majority of them (326, 97.02%). Twenty-three (6.9%) of the enrolled CAM cases expired. The odds of death in CAM patients increased with an increase in HbA1c level (aOR: 1.34, 95%CI: 1.05, 1.72) following adjustment for age, gender, education and employment status.

CONCLUSION: A longer vigil of around 4-6 weeks post-COVID-19 diagnosis is suggested for earlier diagnosis of CAM. Better glycemic control may avert mortality in admitted CAM cases.

PMID:37490256 | DOI:10.1007/s11046-023-00770-w

Environ Sci Pollut Res Int. 2023 Jul 25. doi: 10.1007/s11356-023-28877-z. Online ahead of print.

ABSTRACT

The development of industry has led to serious air pollution problems. It is very important to establish high-precision and high-performance air quality prediction models and take corresponding control measures. In this paper, based on 4 years of air quality and meteorological data from Tianjin, China, the relationships between various meteorological factors and air pollutant concentrations are analyzed. A hybrid deep learning model consisting of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) is proposed to predict pollutant concentrations. In addition, a Bayesian optimization algorithm is applied to obtain the optimal combination of hyperparameters for the proposed deep learning model, which enhances the generalization ability of the model. Furthermore, based on air quality data from multiple stations in the region, a multistation collaborative prediction method is designed, and the concept of a strongly correlated station (SCS) is defined. The predictive model is modified using the idea of SCS and is used to predict the pollutant concentration in Tianjin. The coefficient of determination R² of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ are 0.89, 0.84, 0.69, 0.83, 0.92, and 0.84, respectively. The results show that our model is capable of dealing with air pollutant prediction with satisfactory accuracy.

PMID:37490250 | DOI:10.1007/s11356-023-28877-z