Nevin Manimala

J Trauma Stress. 2022 Mar 8. doi: 10.1002/jts.22808. Online ahead of print.

ABSTRACT

The goal of this study was to create simple visual displays to help patients understand the benefits of evidence-based treatment for posttraumatic stress disorder (PTSD). We reviewed randomized trials of the most effective individual, trauma-focused psychotherapies and first-line antidepressants for adults with PTSD. The analytic sample included 65 treatment arms from 41 trials. We used binomial logistic regression to estimate the proportion of participants who lost their PTSD diagnosis at posttreatment and created a sample icon array to display these estimates. We provide a range of estimates (0-100) based on varying the percentage of the sample with a military affiliation. The percentage of participants who no longer met the diagnostic criteria for PTSD among civilian populations was 64.3% for trauma-focused treatment, 56.9% for SSRI/SNRI, and 16.7% for waitlist/minimal attention. For military populations, the proportions of participants who no longer met the diagnostic criteria were 44.2%, 36.7%, and 8.1%, respectively. We present icon arrays for 0%, 7%, 50%, and 100% military affiliation displaying 100 icons, a portion of which were shaded to indicate the number of participants that no longer met the PTSD criteria following treatment. After evidence-based treatment, between one third and two thirds of participants no longer met the PTSD criteria. Providers can use the icon array developed in this study with patients to facilitate communication regarding PTSD treatment effectiveness.

PMID:35261090 | DOI:10.1002/jts.22808

J Clin Lab Anal. 2022 Mar 9:e24291. doi: 10.1002/jcla.24291. Online ahead of print.

ABSTRACT

BACKGROUND: This study investigates in-hospital mortality amongst patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its relation to serum levels of gamma-glutamyl transferase (GGT).

METHODS: Patients were stratified according to serum levels of gamma-glutamyl transferase (GGT) (GGT<50 IU/L or GGT≥50 IU/L).

RESULTS: A total of 802 participants were considered, amongst whom 486 had GGT<50 IU/L and a mean age of 48.1 (16.5) years, whilst 316 had GGT≥50 IU/L and a mean age of 53.8 (14.7) years. The chief sources of SARS-CoV-2 transmission were contact (366, 45.7%) and community (320, 40%). Most patients with GGT≥50 IU/L had either pneumonia (247, 78.2%) or acute respiratory distress syndrome (ARDS) (85, 26.9%), whilst those with GGT<50 IU/L had hypertension (141, 29%) or diabetes mellitus (DM) (147, 30.2%). Mortality was higher amongst patients with GGT≥50 IU/L (54, 17.1%) than amongst those with GGT<50 IU/L (29, 5.9%). More patients with GGT≥50 required high (83, 27.6%) or low (104, 34.6%) levels of oxygen, whereas most of those with GGT<50 had no requirement of oxygen (306, 71.2%). Multivariable logistic regression analysis indicated that GGT≥50 IU/L (odds ratio [OR]: 2.02, 95% confidence interval [CI]: 1.20-3.45, p=0.009), age (OR: 1.05, 95% CI: 1.03-1.07, p<0.001), hypertension (OR: 2.06, 95% CI: 1.19-3.63, p=0.011), methylprednisolone (OR: 2.96, 95% CI: 1.74-5.01, p<0.001) and fever (OR: 2.03, 95% CI: 1.15-3.68, p=0.016) were significant predictors of all-cause cumulative mortality. A Cox proportional hazards regression model (B = -0.68, SE =0.24, HR =0.51, p = 0.004) showed that patients with GGT<50 IU/L had a 0.51-times lower risk of all-cause cumulative mortality than patients with GGT≥50 IU/L.

CONCLUSION: Higher levels of serum GGT were found to be an independent predictor of in-hospital mortality.

PMID:35261080 | DOI:10.1002/jcla.24291

J Med Virol. 2022 Mar 8. doi: 10.1002/jmv.27708. Online ahead of print.

ABSTRACT

BACKGROUND: Vaccines against COVID-19 provide immunity to deter severe morbidities associated with the infection. However, it does not prevent infection altogether in all exposed individuals. Further, emerging variants of SARS-CoV-2 impose a threat concerning the competency of the vaccines in combating the infection. This study aims to determine the variability in adverse events and the extent of breakthrough infections in the Indian population.

METHODS: A retrospective study was conducted using a pre-validated questionnaire encompassing social, demographic, general health, the status of SARS-CoV-2 infection, vaccination, associated adverse events, and breakthrough infections in the Indian population. Informed consent and ethical approval were obtained as per Indian Council of Medical Research (ICMR) guidelines. Participants who provided the complete information, were Indian citizens, above 18 years, and if vaccinated, administered with either Covishield or Covaxin were, considered for the study. Data has been compiled in Microsoft Excel and analysed for statistical differences using STATA 11.

RESULTS: The responses from 2051 individuals fulfilling the inclusion criteria were analysed. Among 2051, 1119 respondents were vaccinated, and 932 respondents were non-vaccinated. Among 1119 vaccinated respondents, 7 were excluded because of missing data. Therefore, out of 1112 vaccinated, 413 experienced adverse events with a major fraction of younger individuals, age 18-40 years, getting affected (74.82%; 309/413). Furthermore, considerably more females than males encountered adverse consequences to vaccination (P value <0.05). Among vaccinated participants, breakthrough infections were observed in 7.91% (88/1112; 57.96% males and 42.04% females) with the older age group, 61 years and above (odd ratio, 3.25 {1.32-8.03}; P value =0.011), and males were found to be at higher risk.

CONCLUSION: Further research is needed to find out the age and sex-related factors in determining vaccine effectiveness and adverse events. This article is protected by copyright. All rights reserved.

PMID:35261064 | DOI:10.1002/jmv.27708

Stat Med. 2022 Mar 8. doi: 10.1002/sim.9372. Online ahead of print.

ABSTRACT

Network meta-analysis can synthesize evidence from studies comparing multiple treatments for the same disease. Sometimes the treatments of a network are complex interventions, comprising several independent components in different combinations. A component network meta-analysis (CNMA) can be used to analyze such data and can in principle disentangle the individual effect of each component. However, components may interact with each other, either synergistically or antagonistically. Deciding which interactions, if any, to include in a CNMA model may be difficult, especially for large networks with many components. In this article, we present two Bayesian CNMA models that can be used to identify prominent interactions between components. Our models utilize Bayesian variable selection methods, namely the stochastic search variable selection and the Bayesian LASSO, and can benefit from the inclusion of prior information about important interactions. Moreover, we extend these models to combine data from studies providing aggregate information and studies providing individual patient data (IPD). We illustrate our models in practice using three real datasets, from studies in panic disorder, depression, and multiple myeloma. Finally, we describe methods for developing web-applications that can utilize results from an IPD-CNMA, to allow for personalized estimates of relative treatment effects given a patient’s characteristics.

PMID:35261053 | DOI:10.1002/sim.9372

J Clin Ultrasound. 2022 Mar 8. doi: 10.1002/jcu.23188. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate left atrial function in patients with triple-vessel disease (TVD) without myocardial infarction by real-time three-dimensional echocardiography (RT-3DE) and two-dimensional speckle tracking imaging (2D-STE).

METHODS: Sixty patients with coronary artery disease (CAD) without myocardial infarction were classified into two groups in accordance with the coronary angiography results: group B (all triple-vessel stenosis ≥ 50% and < 75%) and group C (all triple-vessel stenosis ≥ 75%). Thirty healthy individuals were selected as group A. LA volume related parameters including left atrial maximum volume index (LAVImax), LA passive and active ejection fraction (LAPEF, LAAEF) and LA total ejection fraction (LATEF) were measured by RT-3DE. The global peak atrial longitudinal systolic strain (LASRs), early and late diastolic LA strain (LASRe and LASRa) rates were measured by 2D-STE.

RESULTS: We found statistically significant differences between 2D-STE and RT-3DE related parameters of these three groups. Furthermore, in groups B and C, N-terminal fragment brain natriuretic peptides (NT-pro-BNP) and left ventricular end-diastolic pressure (LVEDP) were found to be significantly correlated with LASRs and LASRa. And NT-pro-BNP had a moderate correlation with LVEDP.

CONCLUSIONS: 2D-STE and RT-3DE can assess the LA function in patients with TVD without myocardial infarction. And LA strain values may provide additional information for predicting increased LVEDP and NT-pro-BNP.

PMID:35261038 | DOI:10.1002/jcu.23188

Biometrics. 2022 Mar 9. doi: 10.1111/biom.13657. Online ahead of print.

ABSTRACT

Zero-inflated count data arise frequently from genomics studies. Analysis of such data is often based on a mixture model which facilitates excess zeros in combination with a Poisson distribution, and various inference methods have been proposed under such a model. Those analysis procedures, however, are challenged by the presence of measurement error in count responses. In this article, we propose a new measurement error model to describe error-contaminated count data. We show that ignoring the measurement error effects in the analysis may generally lead to invalid inference results, and meanwhile, we identify situations where ignoring measurement error can still yield consistent estimators. Furthermore, we propose a Bayesian method to address the effects of measurement error under the zero-inflated Poisson model and discuss the identifiability issues. We develop a data-augmentation algorithm that is easy to implement. Simulation studies are conducted to evaluate the performance of the proposed method. We apply our method to analyze the data arising from a prostate adenocarcinoma genomics study. This article is protected by copyright. All rights reserved.

PMID:35261029 | DOI:10.1111/biom.13657

Health Serv Res. 2022 Mar 8. doi: 10.1111/1475-6773.13958. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the effectiveness of feedback reports and feedback reports + external facilitation on completion of life-sustaining treatment (LST) note the template and durable medical orders. This quality improvement program supported the national roll-out of the Veterans Health Administration (VA) LST Decisions Initiative (LSTDI), which aims to ensure that seriously-ill veterans have care goals and LST decisions elicited and documented.

DATA SOURCES: Primary data from national databases for VA nursing homes (called Community Living Centers [CLCs]) from 2018 to 2020.

STUDY DESIGN: In one project, we distributed monthly feedback reports summarizing LST template completion rates to 12 sites as the sole implementation strategy. In the second involving five sites, we distributed similar feedback reports and provided robust external facilitation, which included coaching, education, and learning collaboratives. For each project, principal component analyses matched intervention to comparison sites, and interrupted time series/segmented regression analyses evaluated the differences in LSTDI template completion rates between intervention and comparison sites.

DATA COLLECTION METHODS: Data were extracted from national databases in addition to interviews and surveys in a mixed-methods process evaluation.

PRINCIPAL FINDINGS: LSTDI template completion rose from 0% to about 80% throughout the study period in both projects’ intervention and comparison CLCs. There were small but statistically significant differences for feedback reports alone (comparison sites performed better, coefficient estimate 3.48, standard error 0.99 for the difference between groups in change in trend) and feedback reports + external facilitation (intervention sites performed better, coefficient estimate -2.38, standard error 0.72).

CONCLUSIONS: Feedback reports + external facilitation was associated with a small but statistically significant improvement in outcomes compared with comparison sites. The large increases in completion rates are likely due to the well-planned national roll-out of the LSTDI. This finding suggests that when dissemination and support for widespread implementation are present and system-mandated, significant enhancements in the adoption of evidence-based practices may require more intensive support.

PMID:35261022 | DOI:10.1111/1475-6773.13958

Drugs Aging. 2022 Mar 9. doi: 10.1007/s40266-022-00927-0. Online ahead of print.

ABSTRACT

BACKGROUND: Estimating life expectancy of older adults informs whether to pursue future investigation and therapy. Several models to predict mortality have been developed but often require data not immediately available during routine clinical care. The HOSPITAL score and the LACE index were previously validated to predict 30-day readmissions but may also help to assess mortality risk. We assessed their performance to predict 1-year and 30-day mortality in hospitalized older multimorbid patients with polypharmacy.

METHODS: We calculated the HOSPITAL score and LACE index in patients from the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly) trial (patients aged ≥ 70 years with multimorbidity and polypharmacy, admitted to hospital across four European countries in 2016-2018). Our primary and secondary outcomes were 1-year and 30-day mortality. We assessed the overall accuracy (scaled Brier score, the lower the better), calibration (predicted/observed proportions), and discrimination (C-statistic) of the models.

RESULTS: Within 1 year, 375/1879 (20.0%) patients had died, including 94 deaths within 30 days. The overall accuracy was good and similar for both models (scaled Brier score 0.01-0.08). The C-statistics were identical for both models (0.69 for 1-year mortality, p = 0.81; 0.66 for 30-day mortality, p = 0.94). Calibration showed well-matching predicted/observed proportions.

CONCLUSION: The HOSPITAL score and LACE index showed similar performance to predict 1-year and 30-day mortality in older multimorbid patients with polypharmacy. Their overall accuracy was good, their discrimination low to moderate, and the calibration good. These simple tools may help predict older multimorbid patients’ mortality after hospitalization, which may inform post-hospitalization intensity of care.

PMID:35260994 | DOI:10.1007/s40266-022-00927-0

Sports Med. 2022 Mar 9. doi: 10.1007/s40279-022-01665-4. Online ahead of print.

ABSTRACT

BACKGROUND: Consumer wearables and smartphone devices commonly offer an estimate of energy expenditure (EE) to assist in the objective monitoring of physical activity to the general population. Alongside consumers, healthcare professionals and researchers are seeking to utilise these devices for the monitoring of training and improving human health. However, the methods of validation and reporting of EE estimation in these devices lacks rigour, negatively impacting on the ability to make comparisons between devices and provide transparent accuracy.

OBJECTIVES: The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The network was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables and smartphones in the estimation of EE.

METHODS: The recommendations were developed through (1) a systematic literature review; (2) an unstructured review of the wider literature discussing the potential factors that may introduce bias during validation studies; and (3) evidence-informed expert opinions from members of the INTERLIVE network.

RESULTS: The systematic literature review process identified 1645 potential articles, of which 62 were deemed eligible for the final dataset. Based on these studies and the wider literature search, a validation framework is proposed encompassing six key domains for validation: the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis.

CONCLUSIONS: The INTERLIVE network recommends that the proposed protocol, and checklists provided, are used to standardise the testing and reporting of the validation of any consumer wearable or smartphone device to estimate EE. This in turn will maximise the potential utility of these technologies for clinicians, researchers, consumers, and manufacturers/developers, while ensuring transparency, comparability, and replicability in validation.

TRIAL REGISTRATION: PROSPERO ID: CRD42021223508.

PMID:35260991 | DOI:10.1007/s40279-022-01665-4

J Clin Monit Comput. 2022 Mar 8. doi: 10.1007/s10877-022-00835-z. Online ahead of print.

ABSTRACT

The nociception level index (NOL) is a multi-parameter index that incorporates changes in autonomic parameters to evaluate nociception, with more painful stimuli causing more pronounced index variations. How this nociception monitor relates to the pain experience is uncertain, and patients with chronic pain may respond differently to acute pain due to alterations in pain processing. The goal of this pilot study was to evaluate NOL index variations after a painful physiotherapy exercise in patients with upper limb complex regional pain syndrome. Baseline NOL indexes were recorded using a finger probe (PMD-200™ Monitor, Medasense, Israel) and patient reported baseline pain scores using an 11-point numeric rating scale (NRS). Patients then performed a painful physiotherapy exercise and NOL index and pain scores were again recorded. The same procedure and recordings were repeated after a stellate ganglion block. Data were analyzed using a paired Student T test and a P value < 0.05 was considered statistically significant. Twenty patients (12/20 female, 10/20 right-sided) were included in this study. Patients reported moderate baseline pain (4.0 ± 2.7) despite having a low baseline NOL index (7.66 ± 5.76 out of 100). NRS and NOL index scores increased significantly during exercise, both before and after the block. The NOL index increased significantly when patients reported increased pain, indicating that it could eventually be useful in the objective assessment of acute pain in the chronic pain patients. However, NOL index was not able to reflect pain levels at rest, before the painful stimulation, in this chronic pain population. Further studies are needed to better assess NOL index utility at rest and to confirm these findings in this specific chronic pain population.

PMID:35260985 | DOI:10.1007/s10877-022-00835-z