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NPJ Digital Medicine Apr 2023Positive adjustment to chronic diseases reduces psychiatric comorbidity and enhances quality of life. Very little is known about the benefit of internet-based and... (Review)
Review
Positive adjustment to chronic diseases reduces psychiatric comorbidity and enhances quality of life. Very little is known about the benefit of internet-based and mobile-based Cognitive Behavioral Therapy (IM-CBT) on physical outcomes and its reciprocal interactions with psychiatric outcomes, the active therapeutic elements, and effect moderators among people with major chronic medical conditions. In this systematic review and meta-analysis (PROSPERO: CRD42022265738), CINAHL of Systematic Reviews, MEDLINE, PsycINFO, PubMed, Web of Science are systematically searched up to 1 June 2022, for randomized controlled trials (RCTs) comparing IM-CBT against non-CBT control condition(s) among people with chronic disease(s). Primary outcomes include improvements in psychiatric symptoms (depressive, anxiety, PTSD symptoms, general psychological distress) from baseline to post-intervention and follow-ups. Secondary outcomes include improvements in physical distress (physical symptoms, functional impairment, self-rated ill health, objective physiological dysfunction). Among 44 RCTs (5077 patients with seven different chronic diseases), IM-CBT improves depressive symptoms, anxiety symptoms, and general psychological distress at post-intervention and across follow-ups, and improves physical distress and functional impairment at post-intervention. Preliminary evidence suggests that behavioral modification and problem-solving could be necessary components to reduce psychiatric symptoms in IM-CBT, whereas cognitive restructuring, psychoeducation, and mindfulness elements relate to reduced physical distress. IM-CBT shows stronger benefits in chronic pain, cancer, arthritis, and cardiovascular disease, relative to other conditions. Changes in psychiatric symptoms and physical distress prospectively predict each other over time. IM-CBT is an effective intervention for comprehensive symptom management among people with chronic diseases.
PubMed: 37117458
DOI: 10.1038/s41746-023-00809-8 -
The Lancet. Digital Health Mar 2023Digital health interventions are effective for hypertension self-management, but a comparison of the effectiveness and implementation of the different modes of... (Meta-Analysis)
Meta-Analysis
Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with hypertension: a systematic review and meta-analysis of randomised controlled trials.
BACKGROUND
Digital health interventions are effective for hypertension self-management, but a comparison of the effectiveness and implementation of the different modes of interventions is not currently available. This study aimed to compare the effectiveness of SMS, smartphone application, and website interventions on improving blood pressure in adults with hypertension, and to report on their reach, uptake, and feasibility.
METHODS
In this systematic review and meta-analysis we searched CINAHL Complete, Cochrane Central Register of Controlled Trials, Ovid Embase, Ovid MEDLINE, and APA PsycInfo on May 25, 2022, for randomised controlled trials (RCTs) published in English from Jan 1, 2009, that examined the effectiveness of digital health interventions on reducing blood pressure in adults with hypertension. Screening was carried out using Covidence, and data were extracted following Cochrane's guidelines. The primary endpoint was change in the mean of systolic blood pressure. Risk of bias was assessed with Cochrane Risk of Bias 2. Data on systolic and diastolic blood pressure reduction were synthesised in a meta-analysis, and data on reach, uptake and feasibility were summarised narratively. Grading of Recommendations, Assessment, Development, and Evaluation criteria were used to evaluate the level of evidence. The study was registered with PROSPERO CRD42021247845.
FINDINGS
Of the 3235 records identified, 29 RCTs from 13 regions (n=7592 participants) were included in the systematic review, and 28 of these RCTs (n=7092 participants) were included in the meta-analysis. 11 studies used SMS as the primary mode of delivery of the digital health intervention, 13 used smartphone applications, and five used websites. Overall, digital health intervention group participants had a -3·62 mm Hg (95% CI -5·22 to -2·02) greater reduction in systolic blood pressure, and a -2·45 mm Hg (-3·83 to -1·07) greater reduction in diastolic blood pressure, compared with control group participants. No statistically significant differences between the three different modes of delivery were observed for both the systolic (p=0·73) and the diastolic blood pressure (p=0·80) outcomes. Smartphone application interventions had a statistically significant reduction in diastolic blood pressure (-2·45 mm Hg [-4·15 to -0·74]); however, there were no statistically significant reductions for SMS interventions (-1·80 mm Hg [-4·60 to 1·00]) or website interventions (-3·43 mm Hg [-7·24 to 0·38]). Due to the considerable heterogeneity between included studies and the high risk of bias in some, the level of evidence was assigned a low overall score. Interventions were more effective among people with greater severity of hypertension at baseline. SMS interventions reported higher reach and smartphone application studies reported higher uptake, but differences were not statistically significant.
INTERPRETATION
SMS, smartphone application, and website interventions were associated with statistically and clinically significant systolic and diastolic blood pressure reductions, compared with usual care, regardless of the mode of delivery of the intervention. This conclusion is tempered by the considerable heterogeneity of included studies and the high risk of bias in most. Future studies need to describe in detail the mediators and moderators of the effectiveness and implementation of these interventions, to both further improve their effectiveness as well as increase their reach, uptake, and feasibility.
FUNDING
European Union's Horizon 2020 Research and Innovation Programme.
Topics: Humans; Adult; Feasibility Studies; Hypertension; Blood Pressure; Randomized Controlled Trials as Topic
PubMed: 36828607
DOI: 10.1016/S2589-7500(23)00002-X -
Plastic and Reconstructive Surgery.... Dec 2023Children have been suggested to benefit from digit replantation due to a greater neurogenerative capacity. We aimed to conduct a systematic review on digit replantation...
BACKGROUND
Children have been suggested to benefit from digit replantation due to a greater neurogenerative capacity. We aimed to conduct a systematic review on digit replantation in children to provide a comprehensive overview of survival rates and functional outcomes.
METHODS
A systematic literature search was conducted on Ovid MEDLINE, Embase, and the Cochrane Controlled Register of Trials for studies published between 1980 and 2023. We included peer-reviewed studies reporting on digit survival rates in pediatric patients under the age of 18 years who underwent single or multiple digit replantations distal to the metacarpophalangeal joint. Preoperative, intraoperative, and postoperative outcomes were extracted, and pooled estimates were derived using univariable analysis.
RESULTS
Twenty-two studies reporting on 761 patients and 814 digit replantations were included in our study. Most replantations occurred in the index (n = 74), Tamai zone I (n = 168), and from clean-cut injuries (n = 190). The mean survival rate was 76% (n = 618/814), with a mean range of motion at the distal interphalangeal joint ranging from 64 degrees to 90 degrees and two-point discrimination ranging from 3.8 mm to 6.4 mm. Compared with clean-cut injuries, digit replantations from avulsion [odds ratio (OR), 0.81; 95% confidence interval (CI), 0.74-0.89] or crush (OR, 0.71; 95% CI, 0.59-0.82) injuries were associated with a lower odds of survival. Digit replantations performed with two venous (OR, 1.43, 95% CI; 1.28-1.59) or arterial anastomoses (OR, 1.65; 95% CI, 1.48-1.81) were associated with a higher odds of survival.
CONCLUSIONS
Our systematic review suggests that digit replantation may be a viable option in children. Further research is required to explore functionality after digit replantation in diverse pediatric populations.
PubMed: 38098954
DOI: 10.1097/GOX.0000000000005482 -
NPJ Digital Medicine Sep 2022Sexual dysfunctions are highly prevalent and undertreated. Internet- and mobile-based psychological interventions (IMIs) could be a promising addition to close this... (Review)
Review
Sexual dysfunctions are highly prevalent and undertreated. Internet- and mobile-based psychological interventions (IMIs) could be a promising addition to close this treatment gap, given their accessibility, anonymity, and scalability. This systematic review and meta-analysis investigated the efficacy of IMIs for sexual dysfunctions. A comprehensive literature search was conducted in August 2021 on randomized controlled trials investigating the effects of IMIs on sexual functioning and satisfaction compared to a control condition. Twelve RCTs with 14 comparisons were reviewed with six IMIs targeting female and six IMIs targeting male sexual dysfunctions and n = 952 participants were evaluated in the meta-analysis. IMIs were significantly more effective than control conditions (k = 11 waitlist control group, k = 3 online discussion board) at post-treatment for female sexual functioning (g = 0.59, CI: 0.28-0.90, I= 0%) and satisfaction (g = 0.90, CI: 0.02-1.79, I= 82%), and male sexual functioning (g = 0.18, CI: 0.02-0.34, I= 0%). No significant effect was found for male sexual satisfaction (g = 0.69, CI: -0.13-1.51, I= 88%) with substantial heterogeneity in studies. Most studies showed high dropout, with ten studies indicating some concern of risk of bias, and two studies showing high risk of bias. The results suggest that IMIs can be an effective treatment for sexual dysfunctions, although additional high-quality research is needed. Given the limited availability of specialized treatment for sexual dysfunctions and individual preferences for discrete treatment options, IMIs seem to be a valuable addition to routine care, empowering individuals to promote their sexual health on a guided self-help basis.
PubMed: 36085306
DOI: 10.1038/s41746-022-00670-1 -
Hand (New York, N.Y.) Mar 2023Metastatic lesions to the hand or wrist are rare and can mimic inflammatory and benign processes such as gout and infections. This often leads to misdiagnosis,... (Review)
Review
BACKGROUND
Metastatic lesions to the hand or wrist are rare and can mimic inflammatory and benign processes such as gout and infections. This often leads to misdiagnosis, underreporting, and delays in treatment. The purpose of this study was to examine all known cases of metastasis to the hand or wrist available in the literature and to analyze demographic trends, metastasis characteristics, and clinical course, and provide recommendations for management.
METHODS
An online systematic review of MEDLINE, Embase, PubMed, and the Cochrane Library from inception to January 7, 2022, was completed. Studies outlining the care of a patient with acrometastases of the hand were included. Data extracted included age, sex, site of primary tumor and metastasis, presence of other metastases, time from primary diagnosis to acrometastasis diagnosis, misdiagnosis, treatment, and survival.
RESULTS
Between 1889 and present, 871 lesions were described in 676 patients who met the inclusion criteria. There was no predilection for hand dominance or site of previous trauma. The mean age among patients was 59.5 (1.5-91) years, and male sex was more common (64.6%). The most common primary cancer source was the lung (39.2%), followed by the kidney (10.8%). The distal phalanx was the most frequently cited tumor location (33.7%). Mean survival after diagnosis of acrometastasis was 6.3 months (0.25-50) ± 11.5 months.
CONCLUSION
Acrometastasis remains an uncommon presentation of metastatic disease with poor prognosis. Treatment currently focuses on pain management and optimizing functional outcomes. Our review led to the development of 7 treatment recommendations when managing these patients.
PubMed: 36856295
DOI: 10.1177/15589447231153175 -
NPJ Digital Medicine Dec 2023Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage,... (Review)
Review
Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. Twelve databases were searched for experimental studies of AI-based CAs' effects on mental illnesses and psychological well-being published before May 26, 2023. Out of 7834 records, 35 eligible studies were identified for systematic review, out of which 15 randomized controlled trials were included for meta-analysis. The meta-analysis revealed that AI-based CAs significantly reduce symptoms of depression (Hedge's g 0.64 [95% CI 0.17-1.12]) and distress (Hedge's g 0.7 [95% CI 0.18-1.22]). These effects were more pronounced in CAs that are multimodal, generative AI-based, integrated with mobile/instant messaging apps, and targeting clinical/subclinical and elderly populations. However, CA-based interventions showed no significant improvement in overall psychological well-being (Hedge's g 0.32 [95% CI -0.13 to 0.78]). User experience with AI-based CAs was largely shaped by the quality of human-AI therapeutic relationships, content engagement, and effective communication. These findings underscore the potential of AI-based CAs in addressing mental health issues. Future research should investigate the underlying mechanisms of their effectiveness, assess long-term effects across various mental health outcomes, and evaluate the safe integration of large language models (LLMs) in mental health care.
PubMed: 38114588
DOI: 10.1038/s41746-023-00979-5 -
The Lancet. Digital Health Dec 2023Machine learning and deep learning models have been increasingly used to predict long-term disease progression in patients with chronic obstructive pulmonary disease... (Meta-Analysis)
Meta-Analysis
Machine learning and deep learning predictive models for long-term prognosis in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis.
BACKGROUND
Machine learning and deep learning models have been increasingly used to predict long-term disease progression in patients with chronic obstructive pulmonary disease (COPD). We aimed to summarise the performance of such prognostic models for COPD, compare their relative performances, and identify key research gaps.
METHODS
We conducted a systematic review and meta-analysis to compare the performance of machine learning and deep learning prognostic models and identify pathways for future research. We searched PubMed, Embase, the Cochrane Library, ProQuest, Scopus, and Web of Science from database inception to April 6, 2023, for studies in English using machine learning or deep learning to predict patient outcomes at least 6 months after initial clinical presentation in those with COPD. We included studies comprising human adults aged 18-90 years and allowed for any input modalities. We reported area under the receiver operator characteristic curve (AUC) with 95% CI for predictions of mortality, exacerbation, and decline in forced expiratory volume in 1 s (FEV). We reported the degree of interstudy heterogeneity using Cochran's Q test (significant heterogeneity was defined as p≤0·10 or I>50%). Reporting quality was assessed using the TRIPOD checklist and a risk-of-bias assessment was done using the PROBAST checklist. This study was registered with PROSPERO (CRD42022323052).
FINDINGS
We identified 3620 studies in the initial search. 18 studies were eligible, and, of these, 12 used conventional machine learning and six used deep learning models. Seven models analysed exacerbation risk, with only six reporting AUC and 95% CI on internal validation datasets (pooled AUC 0·77 [95% CI 0·69-0·85]) and there was significant heterogeneity (I 97%, p<0·0001). 11 models analysed mortality risk, with only six reporting AUC and 95% CI on internal validation datasets (pooled AUC 0·77 [95% CI 0·74-0·80]) with significant degrees of heterogeneity (I 60%, p=0·027). Two studies assessed decline in lung function and were unable to be pooled. Machine learning and deep learning models did not show significant improvement over pre-existing disease severity scores in predicting exacerbations (p=0·24). Three studies directly compared machine learning models against pre-existing severity scores for predicting mortality and pooled performance did not differ (p=0·57). Of the five studies that performed external validation, performance was worse than or equal to regression models. Incorrect handling of missing data, not reporting model uncertainty, and use of datasets that were too small relative to the number of predictive features included provided the largest risks of bias.
INTERPRETATION
There is limited evidence that conventional machine learning and deep learning prognostic models demonstrate superior performance to pre-existing disease severity scores. More rigorous adherence to reporting guidelines would reduce the risk of bias in future studies and aid study reproducibility.
FUNDING
None.
Topics: Adult; Humans; Reproducibility of Results; Deep Learning; Quality of Life; Pulmonary Disease, Chronic Obstructive; Prognosis
PubMed: 38000872
DOI: 10.1016/S2589-7500(23)00177-2 -
Journal of Hand and Microsurgery Aug 2020There is a lack of consensus on what the critical outcomes in replantation are and how best to measure them. This review aims to identify all reported outcomes and... (Review)
Review
There is a lack of consensus on what the critical outcomes in replantation are and how best to measure them. This review aims to identify all reported outcomes and respective outcome measures used in digital replantation. Randomized controlled trials, cohort studies, and single-arm observational studies of adults undergoing replantation with at least one well-described outcome or outcome measure were identified. Primary outcomes were classified into six domains, and outcome measures were classified into eight domains. The clinimetric properties were identified and reported. A total of 56 observational studies met the inclusion criteria. In total, 29 continuous and 29 categorical outcomes were identified, and 87 scales and instruments were identified. The most frequently used outcomes were survival of replanted digit, sensation, and time in hospital. Outcomes and measures were most variable in domains of viability, quality of life, and motor function. Only eight measures used across these domains were validated and proven reliable. Lack of consensus creates an obstacle to reporting, understanding, and comparing the effectiveness of various replantation strategies.
PubMed: 33335363
DOI: 10.1055/s-0040-1701324 -
Sleep Medicine: X Dec 2023Insomnia is a common disease, and the application of various types of sleeping pills for cognitive impairment is controversial, especially as different doses can lead to... (Review)
Review
BACKGROUND
Insomnia is a common disease, and the application of various types of sleeping pills for cognitive impairment is controversial, especially as different doses can lead to different effects. Therefore, it is necessary to evaluate the cognitive impairment caused by different sleeping pills to provide a theoretical basis for guiding clinicians in the selection of medication regimens.
OBJECTIVE
To evaluate whether various different doses (low, medium and high) of anti-insomnia drugs, such as the dual-orexin receptor antagonist (DORA), zopiclone, eszopiclone and zolpidem, induce cognitive impairment.
METHODS
The PubMed, Embase, Scopus, Cochrane Library, and Google Scholar databases were searched from inception to September 20th, 2022 for keywords in randomized controlled trials (RCTs) to evaluate the therapeutic effects of DORA, eszopiclone, zopiclone and zolpidem on sleep and cognitive function. The primary outcomes were indicators related to cognitive characteristics, including scores on the Digit Symbol Substitution Test (DSST) and daytime alertness. The secondary outcomes were the indicators associated with sleep and adverse events. Continuous variables were expressed as the standard mean difference (SMD). Data were obtained through GetData 2.26 and analyzed by Stata v.15.0.
RESULTS
A total of 8702 subjects were included in 29 studies. Eszopiclone significantly increased the daytime alertness score (SMD = 3.00, 95 % CI: 1.86 to 4.13) compared with the placebo, and eszopiclone significantly increased the daytime alertness score (SMD = 4.21, 95 % CI: 1.65 to 6.77; SMD = 3.95, 95 % CI: 1.38 to 6.51; SMD = 3.26, 95 % CI: 0.38 to 6.15; and SMD = 3.23, 95 % CI: 0.34 to 6.11) compared with zolpidem, zolpidem, DORA, and eszopiclone, respectively. Compared with the placebo, zopiclone, zolpidem, and eszopiclone, DORA significantly increased the TST (SMD = 2.39, 95 % CI: 1.11 to 3.67; SMD = 6.00, 95 % CI: 2.73 to 9.27; SMD = 1.89, 95 % CI: 0.90 to 2.88; and SMD = 1.70, 95 % CI: 0.42 to 2.99, respectively).
CONCLUSION
We recommend DORA as the best intervention for insomnia because it was highly effective in inducing and maintaining sleep without impairing cognition. Although zolpidem had a more pronounced effect on sleep maintenance, this drug is better for short-term use. Eszopiclone and zopiclone improved sleep, but their cognitive effects have yet to be verified.
PubMed: 38149178
DOI: 10.1016/j.sleepx.2023.100094 -
Frontiers in Digital Health 2022Pain is a silent global epidemic impacting approximately a third of the population. Pharmacological and surgical interventions are primary modes of treatment.... (Review)
Review
IMPORTANCE
Pain is a silent global epidemic impacting approximately a third of the population. Pharmacological and surgical interventions are primary modes of treatment. Cognitive/behavioural management approaches and interventional pain management strategies are approaches that have been used to assist with the management of chronic pain. Accurate data collection and reporting treatment outcomes are vital to addressing the challenges faced. In light of this, we conducted a systematic evaluation of the current digital application landscape within chronic pain medicine.
OBJECTIVE
The primary objective was to consider the prevalence of digital application usage for chronic pain management. These digital applications included mobile apps, web apps, and chatbots.
DATA SOURCES
We conducted searches on PubMed and ScienceDirect for studies that were published between 1st January 1990 and 1st January 2021.
STUDY SELECTION
Our review included studies that involved the use of digital applications for chronic pain conditions. There were no restrictions on the country in which the study was conducted. Only studies that were peer-reviewed and published in English were included. Four reviewers had assessed the eligibility of each study against the inclusion/exclusion criteria. Out of the 84 studies that were initially identified, 38 were included in the systematic review.
DATA EXTRACTION AND SYNTHESIS
The AMSTAR guidelines were used to assess data quality. This assessment was carried out by 3 reviewers. The data were pooled using a random-effects model.
MAIN OUTCOMES AND MEASURES
Before data collection began, the primary outcome was to report on the standard mean difference of digital application usage for chronic pain conditions. We also recorded the type of digital application studied (e.g., mobile application, web application) and, where the data was available, the standard mean difference of pain intensity, pain inferences, depression, anxiety, and fatigue.
RESULTS
38 studies were included in the systematic review and 22 studies were included in the meta-analysis. The digital interventions were categorised to web and mobile applications and chatbots, with pooled standard mean difference of 0.22 (95% CI: -0.16, 0.60), 0.30 (95% CI: 0.00, 0.60) and -0.02 (95% CI: -0.47, 0.42) respectively. Pooled standard mean differences for symptomatologies of pain intensity, depression, and anxiety symptoms were 0.25 (95% CI: 0.03, 0.46), 0.30 (95% CI: 0.17, 0.43) and 0.37 (95% CI: 0.05, 0.69), respectively. A sub-group analysis was conducted on pain intensity due to the heterogeneity of the results ( = 82.86%; = 0.02). After stratifying by country, we found that digital applications were more likely to be effective in some countries (e.g., United States, China) than others (e.g., Ireland, Norway).
CONCLUSIONS AND RELEVANCE
The use of digital applications in improving pain-related symptoms shows promise, but further clinical studies would be needed to develop more robust applications.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier: CRD42021228343.
PubMed: 36405414
DOI: 10.3389/fdgth.2022.850601