Nevin Manimala

J Med Internet Res. 2024 Mar 27;26:e49058. doi: 10.2196/49058.

ABSTRACT

BACKGROUND: During the first lockdown of the COVID-19 pandemic, an exponential increase in video consultations replacing in-person outpatient visits was observed in hospitals. Insight into patients’ experiences with this type of consultation is helpful for a broad, sustainable, and patient-centered implementation of video consultation.

OBJECTIVE: This study aims to examine patients’ experiences with video consultation during the COVID-19 pandemic and identify discriminative patient and consultation characteristics to determine when video consultation is most feasible.

METHODS: A cross-sectional survey study was conducted. Patients aged ≥18 years and scheduled for a video consultation at the outpatient clinic of a Dutch university medical center from August 2020 to December 2020 for all medical specialties were eligible. Patients’ experiences were explored through a study-specific survey using descriptive quantitative statistics. Open-ended questions were qualitatively analyzed and thematically categorized into appreciated aspects and aspects for improvement. Discriminative patient and consultation characteristics were identified using 3 distinctive survey items. Characteristics of patients who scored and those who did not score all 3 items positively were analyzed using binary logistic regression.

RESULTS: A total of 1054 patients were included in the analysis. Most patients (964/1054, 91.46%) were satisfied with their video consultation, with a mean overall grade of 8.6 (SD 1.3) of 10. In the qualitative analyses, 70.02% (738/1054) of the patients cited aspects they appreciated and 44.97% (474/1054) mentioned aspects for improvement during their consultation. Patients with better self-rated health reported a positive evaluation significantly more often (P=.001), which also held true for other medical specialties (vs surgical and nonsurgical specialties; P<.001).

CONCLUSIONS: Video consultation was perceived as highly satisfactory by patients during the COVID-19 pandemic, with the best experience reported by healthy participants and those undergoing their first consultation. Appreciated aspects are mainly at the individual professional level, organizational level, and innovation level itself. The aspects that were mentioned for improvement can be changed for the better.

PMID:38536236 | DOI:10.2196/49058

J Med Internet Res. 2024 Mar 27;26:e54287. doi: 10.2196/54287.

ABSTRACT

BACKGROUND: University attendance represents a transition period for students that often coincides with the emergence of mental health and substance use challenges. Digital interventions have been identified as a promising means of supporting students due to their scalability, adaptability, and acceptability. Minder is a mental health and substance use mobile app that was codeveloped with university students.

OBJECTIVE: This study aims to examine the effectiveness of the Minder mobile app in improving mental health and substance use outcomes in a general population of university students.

METHODS: A 2-arm, parallel-assignment, single-blinded, 30-day randomized controlled trial was used to evaluate Minder using intention-to-treat analysis. In total, 1489 participants were recruited and randomly assigned to the intervention (n=743, 49.9%) or waitlist control (n=746, 50.1%) condition. The Minder app delivers evidence-based content through an automated chatbot and connects participants with services and university social groups. Participants are also assigned a trained peer coach to support them. The primary outcomes were measured through in-app self-assessments and included changes in general anxiety symptomology, depressive symptomology, and alcohol consumption risk measured using the 7-item General Anxiety Disorder scale, 9-item Patient Health Questionnaire, and US Alcohol Use Disorders Identification Test-Consumption Scale, respectively, from baseline to 30-day follow-up. Secondary outcomes included measures related to changes in the frequency of substance use (cannabis, alcohol, opioids, and nonmedical stimulants) and mental well-being. Generalized linear mixed-effects models were used to examine each outcome.

RESULTS: In total, 79.3% (589/743) of participants in the intervention group and 83% (619/746) of participants in the control group completed the follow-up survey. The intervention group had significantly greater average reductions in anxiety symptoms measured using the 7-item General Anxiety Disorder scale (adjusted group mean difference=-0.85, 95% CI -1.27 to -0.42; P<.001; Cohen d=-0.17) and depressive symptoms measured using the 9-item Patient Health Questionnaire (adjusted group mean difference=-0.63, 95% CI -1.08 to -0.17; P=.007; Cohen d=-0.11). A reduction in the US Alcohol Use Disorders Identification Test-Consumption Scale score among intervention participants was also observed, but it was not significant (P=.23). Statistically significant differences in favor of the intervention group were found for mental well-being and reductions in the frequency of cannabis use and typical number of drinks consumed. A total of 77.1% (573/743) of participants in the intervention group accessed at least 1 app component during the study period.

CONCLUSIONS: In a general population sample of university students, the Minder app was effective in reducing symptoms of anxiety and depression, with provisional support for increasing mental well-being and reducing the frequency of cannabis and alcohol use. These findings highlight the potential ability of e-tools focused on prevention and early intervention to be integrated into existing university systems to support students’ needs.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05606601; https://clinicaltrials.gov/ct2/show/NCT05606601.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/49364.

PMID:38536225 | DOI:10.2196/54287

Microb Genom. 2024 Mar;10(3). doi: 10.1099/mgen.0.001214.

ABSTRACT

With emerging infectious disease outbreaks in human, domestic and wild animal populations on the rise, improvements in pathogen characterization and surveillance are paramount for the protection of human and animal health, as well as the conservation of ecologically and economically important wildlife. Genomics offers a range of suitable tools to meet these goals, with metagenomic sequencing facilitating the characterization of whole microbial communities associated with emerging and endemic disease outbreaks. Here, we use metagenomic sequencing in a case-control study to identify microbes in lung tissue associated with newly observed pneumonia-related fatalities in 34 white-tailed deer (Odocoileus virginianus) in Wisconsin, USA. We identified 20 bacterial species that occurred in more than a single individual. Of these, only Clostridium novyi was found to substantially differ (in number of detections) between case and control sample groups; however, this difference was not statistically significant. We also detected several bacterial species associated with pneumonia and/or other diseases in ruminants (Mycoplasma ovipneumoniae, Trueperella pyogenes, Pasteurella multocida, Anaplasma phagocytophilum, Fusobacterium necrophorum); however, these species did not substantially differ between case and control sample groups. On average, we detected a larger number of bacterial species in case samples than controls, supporting the potential role of polymicrobial infections in this system. Importantly, we did not detect DNA of viruses or fungi, suggesting that they are not significantly associated with pneumonia in this system. Together, these results highlight the utility of metagenomic sequencing for identifying disease-associated microbes. This preliminary list of microbes will help inform future research on pneumonia-associated fatalities of white-tailed deer.

PMID:38536208 | DOI:10.1099/mgen.0.001214

JMIR Infodemiology. 2024 Mar 27;4:e47770. doi: 10.2196/47770.

ABSTRACT

BACKGROUND: Social media posts by clinicians are not bound by the same rules as peer-reviewed publications, raising ethical concerns that have not been extensively characterized or quantified.

OBJECTIVE: We aim to develop a scale to assess ethical issues on medical social media (SoMe) and use it to determine the prevalence of these issues among posts with 3 different hashtags: #MedTwitter, #IRad, and #CardioTwitter.

METHODS: A scale was developed based on previous descriptions of professionalism and validated via semistructured cognitive interviewing with a sample of 11 clinicians and trainees, interrater agreement, and correlation of 100 posts. The final scale assessed social media posts in 6 domains. This was used to analyze 1500 Twitter posts, 500 each from the 3 hashtags. Analysis of posts was limited to original Twitter posts in English made by health care professionals in North America. The prevalence of potential issues was determined using descriptive statistics and compared across hashtags using the Fisher exact and χ² tests with Yates correction.

RESULTS: The final scale was considered reflective of potential ethical issues of SoMe by participants. There was good interrater agreement (Cohen κ=0.620, P<.01) and moderate to strong positive interrater correlation (=0.602, P<.001). The 6 scale domains showed minimal to no interrelation (Cronbach α=0.206). Ethical concerns across all hashtags had a prevalence of 1.5% or less except the conflict of interest concerns on #IRad, which had a prevalence of 3.6% (n=18). Compared to #MedTwitter, posts with specialty-specific hashtags had more patient privacy and conflict of interest concerns.

CONCLUSIONS: The SoMe professionalism scale we developed reliably reflects potential ethical issues. Ethical issues on SoMe are rare but important and vary in prevalence across medical communities.

PMID:38536206 | DOI:10.2196/47770

Hematol Oncol. 2024 Mar;42(2):e3253. doi: 10.1002/hon.3253.

ABSTRACT

Examination of central nervous system (CNS) involvement is not routine diagnostic practice in adult patients with acute myeloid leukemia (AML). Therefore, many asymptomatic patients with CNS involvement might go undetected. The effect of CNS involvement on the AML disease course is not well defined, with conflicting results regarding clinical outcome. This study aimed to determine the incidence of asymptomatic CNS involvement in AML estimated by multiparametric flow cytometry of cerebrospinal fluid (MFC-CSF) at diagnosis, the related potential risk factors, and prognosis. In total, 645 patients with de novo AML were screened; 183 (28.4%) of them fulfilled institutional practice for MFC-CSF analysis based on presence of CNS symptoms and/or clinical features. CNS symptoms and signs were observed in 8/183 (4.4%) patients, but most patients (175/183, 95.6%) were asymptomatic. In the asymptomatic group, 73/175 (41.7%) patients had positive or suspicious cerebrospinal fluid (CSF) findings categorized as CNS positive (CNS^pos) and 102/175 (58.3%) had normal CNS findings categorized as CNS negative (CNS^neg). The presence of leukemic blasts was confirmed in 81/183 (44.3%) patients; the total incidence of CNS involvement in the whole AML group was 12.6% (81/645). Compared with asymptomatic patients with CNS^neg, those with CNS^pos had a significantly higher frequency of lymphadenopathy, white blood cell count ≥30 × 10⁹/L, presence of the monocytic phenotype, and a high percentage of bone marrow (BM) blasts. The multivariate logistic regression model identified monocytic phenotype (p = 0.047) and high percentage of BM blasts (p = 0.042) as predictors for CNS^pos. CNS^pos did not affect overall survival in patients with AML. There was a higher incidence of CNS involvement in asymptomatic adult patients with de novo AML, emphasizing possible undervalued rates of CNS disease at diagnosis. Prospective studies should determine whether diagnostic lumbar puncture for MFC-CSF analysis and CNS prophylaxis could contribute to better selection and prognosis in this patient population.

PMID:38536200 | DOI:10.1002/hon.3253

JAMA Surg. 2024 Mar 27. doi: 10.1001/jamasurg.2024.0235. Online ahead of print.

ABSTRACT

IMPORTANCE: When considering nonoperative treatment in a patient with acute appendicitis, it is crucial to accurately rule out complicated appendicitis. The Atema score, also referred to as the Scoring System of Appendicitis Severity (SAS), has been designed to differentiate between uncomplicated and complicated appendicitis but has not been prospectively externally validated.

OBJECTIVE: To externally validate the SAS and, in case of failure, to develop an improved SAS (2.0) for estimating the probability of complicated appendicitis.

DESIGN, SETTING, AND PARTICIPANTS: This prospective study included adult patients who underwent operations for suspected acute appendicitis at 11 hospitals in the Netherlands between January 2020 and August 2021.

MAIN OUTCOMES AND MEASURES: Appendicitis severity was predicted according to the SAS in 795 patients and its sensitivity and negative predictive value (NPV) for complicated appendicitis were calculated. Since the predefined targets of 95% for both were not met, the SAS 2.0 was developed using the same cohort. This clinical prediction model was developed with multivariable regression using clinical, biochemical, and imaging findings. The SAS 2.0 was externally validated in a temporal validation cohort consisting of 565 patients.

RESULTS: In total, 1360 patients were included, 463 of whom (34.5%) had complicated appendicitis. Validation of the SAS resulted in a sensitivity of 83.6% (95% CI, 78.8-87.6) and an NPV of 85.0% (95% CI, 80.6-88.8), meaning that the predefined targets were not achieved. Therefore, the SAS 2.0 was developed, internally validated (C statistic, 0.87; 95% CI, 0.84-0.89), and subsequently externally validated (C statistic, 0.86; 95% CI, 0.82-0.89). The SAS 2.0 was designed to calculate a patient’s individual probability of having complicated appendicitis along with a 95% CI.

CONCLUSIONS AND RELEVANCE: In this study, external validation of the SAS fell short in accurately distinguishing complicated from uncomplicated appendicitis. The newly developed and externally validated SAS 2.0 was able to assess an individual patient’s probability of having complicated appendicitis with high accuracy in patients with acute appendicitis. Use of this patient-specific risk assessment tool can be helpful when considering and discussing nonoperative treatment of acute appendicitis with patients.

PMID:38536188 | DOI:10.1001/jamasurg.2024.0235

JAMA Netw Open. 2024 Mar 4;7(3):e243854. doi: 10.1001/jamanetworkopen.2024.3854.

ABSTRACT

IMPORTANCE: There is substantial interest in capturing cancer treatment tolerability from the patient’s perspective using patient-reported outcomes (PROs).

OBJECTIVE: To examine whether a PRO question, item 5 from the Functional Assessment of Cancer Therapy-General General Physical Wellbeing Scale (GP5), was associated with early treatment discontinuation (ETD) due to adverse events.

DESIGN, SETTING, AND PARTICIPANTS: This prospective survey study was conducted from February to April 2023. Among participants in the ECOG-ACRIN E1A11 trial (a phase 3, parallel design trial conducted between 2013 and 2019), patients with newly diagnosed multiple myeloma were randomized to receive bortezomib (VRd) or carfilzomib (KRd) plus lenalidomide and dexamethasone as induction therapy. The GP5 item was administered at baseline (pretreatment) and at 1 month, 2.8 months, and 5.5 months postbaseline. Eligible participants included patients with newly diagnosed multiple myeloma treated at community oncology practices or academic medical centers in the US.

EXPOSURES: GP5 response options were “very much,” “quite a bit,” “somewhat,” “a little bit,” and “not at all.” Responses at each assessment while undergoing treatment (1 month, 2.8 months, and 5.5 months) were categorized as high adverse event bother (ie, “very much,” and “quite a bit”) and low adverse event bother (ie, “somewhat,” “a little bit,” or “not at all”). In addition, change from baseline to each assessment while undergoing treatment was calculated and categorized as worsening by 1 response category and 2 or more response categories.

MAIN OUTCOME AND MEASURE: ETD due to adverse events (yes vs no) was analyzed using logistic regression adjusting for treatment group, performance status, gender, race, and disease stage.

RESULTS: Of the 1087 participants in the original trial, 1058 (mean [SD] age 64 [9] years; 531 receiving VrD [50.2%]; 527 receiving KRd [49.8%]) responded to item GP5 and were included in the secondary analysis. A small proportion (142 patients [13.4%]) discontinued treatment early due to AEs. For those with high adverse-effect bother, GP5 while undergoing treatment was associated with ETD at 1 month (adjusted odds ratio [aOR], 2.20; 95% CI, 1.25-3.89), 2.8 months (aOR, 3.41; 95% CI, 2.01-5.80), and 5.5 months (aOR, 4.66; 95% CI, 1.69-12.83). Worsening by 2 or more response categories on the GP5 was associated with ETD at 2.8 months (aOR, 3.02; 95% CI, 1.64-5.54) and 5.5 months (aOR, 5.49; 95% CI, 1.45-20.76).

CONCLUSIONS AND RELEVANCE: In this survey study of the E1A11 trial, worse GP5 response was associated with ETD. These findings suggest that simple assessment of adverse-effect bother while receiving treatment is an efficient way to indicate treatment tolerability and ETD risk.

PMID:38536173 | DOI:10.1001/jamanetworkopen.2024.3854

JAMA Dermatol. 2024 Mar 27. doi: 10.1001/jamadermatol.2024.0091. Online ahead of print.

ABSTRACT

IMPORTANCE: Cellulitis is misdiagnosed in up to 30% of cases due to mimic conditions termed pseudocellulitis. The resulting overuse of antibiotics is a threat to patient safety and public health. Surface thermal imaging and the ALT-70 (asymmetry, leukocytosis, tachycardia, and age ≥70 years) prediction model have been proposed as tools to help differentiate cellulitis from pseudocellulitis.

OBJECTIVES: To validate differences in skin surface temperatures between patients with cellulitis and patients with pseudocellulitis, assess the optimal temperature measure and cut point for differentiating cellulitis from pseudocellulitis, and compare the performance of skin surface temperature and the ALT-70 prediction model in differentiating cellulitis from pseudocellulitis.

DESIGN, SETTING, AND PARTICIPANTS: This prospective diagnostic validation study was conducted among patients who presented to the emergency department with acute dermatologic lower extremity symptoms from October 11, 2018, through March 11, 2020. Statistical analysis was performed from July 2020 to March 2021 with additional work conducted in September 2023.

MAIN OUTCOMES AND MEASURES: Temperature measures for affected and unaffected skin were obtained. Cellulitis vs pseudocellulitis was assessed by a 6-physician, independent consensus review. Differences in temperature measures were compared using the t test. Logistic regression was used to identify the temperature measure and associated cut point with the optimal performance for discriminating between cellulitis and pseudocellulitis. Diagnostic performance characteristics for the ALT-70 prediction model, surface skin temperature, and both combined were also assessed.

RESULTS: The final sample included 204 participants (mean [SD] age, 56.6 [16.5] years; 121 men [59.3%]), 92 (45.1%) of whom had a consensus diagnosis of cellulitis. There were statistically significant differences in all skin surface temperature measures (mean temperature, maximum temperature, and gradients) between cellulitis and pseudocellulitis. The maximum temperature of the affected limb for patients with cellulitis was 33.2 °C compared with 31.2 °C for those with pseudocellulitis (difference, 2.0 °C [95% CI, 1.3-2.7 °C]; P < .001). The maximum temperature was the optimal temperature measure with a cut point of 31.2 °C in the affected skin, yielding a mean (SD) negative predictive value of 93.5% (4.7%) and a sensitivity of 96.8% (2.3%). The sensitivity of all 3 measures remained above 90%, while specificity varied considerably (ALT-70, 22.0% [95% CI, 15.8%-28.1%]; maximum temperature of the affected limb, 38.4% [95% CI, 31.7%-45.1%]; combination measure, 53.9% [95% CI, 46.5%-61.2%]).

CONCLUSIONS AND RELEVANCE: In this large diagnostic validation study, significant differences in skin surface temperature measures were observed between cases of cellulitis and cases of pseudocellulitis. Thermal imaging and the ALT-70 both demonstrated high sensitivity, but specificity was improved by combining the 2 measures. These findings support the potential of thermal imaging, alone or in combination with the ALT-70 prediction model, as a diagnostic adjunct that may reduce overdiagnosis of cellulitis.

PMID:38536160 | DOI:10.1001/jamadermatol.2024.0091

JAMA Cardiol. 2024 Mar 27. doi: 10.1001/jamacardio.2024.0284. Online ahead of print.

ABSTRACT

IMPORTANCE: Accurate risk prediction of morbidity and mortality in patients with heart failure with preserved ejection fraction (HFpEF) may help clinicians risk stratify and inform care decisions.

OBJECTIVE: To develop and validate a novel prediction model for clinical outcomes in patients with HFpEF using routinely collected variables and to compare it with a biomarker-driven approach.

DESIGN, SETTING, AND PARTICIPANTS: Data were used from the Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure (DELIVER) trial to derive the prediction model, and data from the Angiotensin Receptor Neprilysin Inhibition in Heart Failure With Preserved Ejection Fraction (PARAGON-HF) and the Irbesartan in Heart Failure With Preserved Ejection Fraction Study (I-PRESERVE) trials were used to validate it. The outcomes were the composite of HF hospitalization (HFH) or cardiovascular death, cardiovascular death, and all-cause death. A total of 30 baseline candidate variables were selected in a stepwise fashion using multivariable analyses to create the models. Data were analyzed from January 2023 to June 2023.

EXPOSURES: Models to estimate the 1-year and 2-year risk of cardiovascular death or hospitalization for heart failure, cardiovascular death, and all-cause death.

RESULTS: Data from 6263 individuals in the DELIVER trial were used to derive the prediction model and data from 4796 individuals in the PARAGON-HF trial and 4128 individuals in the I-PRESERVE trial were used to validate it. The final prediction model for the composite outcome included 11 variables: N-terminal pro-brain natriuretic peptide (NT-proBNP) level, HFH within the past 6 months, creatinine level, diabetes, geographic region, HF duration, treatment with a sodium-glucose cotransporter 2 inhibitor, chronic obstructive pulmonary disease, transient ischemic attack/stroke, any previous HFH, and heart rate. This model showed good discrimination (C statistic at 1 year, 0.73; 95% CI, 0.71-0.75) in both validation cohorts (C statistic at 1 year, 0.71; 95% CI, 0.69-0.74 in PARAGON-HF and 0.75; 95% CI, 0.73-0.78 in I-PRESERVE) and calibration. The model showed similar discrimination to a biomarker-driven model including high-sensitivity cardiac troponin T and significantly better discrimination than the Meta-Analysis Global Group in Chronic (MAGGIC) risk score (C statistic at 1 year, 0.60; 95% CI, 0.58-0.63; delta C statistic, 0.13; 95% CI, 0.10-0.15; P < .001) and NT-proBNP level alone (C statistic at 1 year, 0.66; 95% CI, 0.64-0.68; delta C statistic, 0.07; 95% CI, 0.05-0.08; P < .001). Models derived for the prediction of all-cause and cardiovascular death also performed well. An online calculator was created to allow calculation of an individual’s risk.

CONCLUSIONS AND RELEVANCE: In this prognostic study, a robust prediction model for clinical outcomes in HFpEF was developed and validated using routinely collected variables. The model performed better than NT-proBNP level alone. The model may help clinicians to identify high-risk patients and guide treatment decisions in HFpEF.

PMID:38536153 | DOI:10.1001/jamacardio.2024.0284

Int J Prosthodont. 2024 Mar 22;0(0):1-19. doi: 10.11607/ijp.8843. Online ahead of print.

ABSTRACT

PURPOSE: To update data on the transfer accuracy of digital implant impressions by using a coordinate-based analysis, latest intraoral scanners (IOSs) were investigated in an established clinical close model set-up.

MATERIALS AND METHODS: An implant master model (IMM) of the maxilla with four implants in the posterior area (#14/#24 and #16/#26) and a reference cube was scanned with four different IOS (i700 (Medit), Primescan (Dentsply Sirona), Trios 4 and Trios 5 (3Shape) ten times each. Datasets were compared with a reference dataset of IMM that was generated with x-ray computed tomography in advance. 3D deviations for the implant-abutment-interface points (IAIPs) were calculated. Statistical analysis was performed by multifactorial ANOVA (p < .05).

RESULTS: Overall deviations for trueness (mean) ± precision (SD) of the IAIPs ranged from 88±47 μm for the Primescan, followed by 112±57 μm for the i700, 121±42 μm for the Trios 4 and 124±43 μm for the Trios 5 with decreasing accuracy along the scan path. For trueness, one significant difference between the Primescan and the T4 was detected for one implant position. For precision, no significant differences were noticed.

CONCLUSIONS: Although the latest IOS showed a significant improvement in transfer accuracy, the accumulating deviation along the scan path is not yet resolved. Considering the Trios system, the innovation seems to be limited as no improvement could be detected between Trios 4 and 5.

PMID:38536148 | DOI:10.11607/ijp.8843