Crosswalking Four Pain Impact Measures in a Nationally Representative Sample of Adults with Back Pain.

OBJECTIVE: To generate crosswalk equations and tables for four pain impact measures: the Impact Stratification Score (ISS), Oswestry Disability Index (ODI), Roland-Morris Disability Questionnaire (RMDQ), and the Pain, Enjoyment of Life and General Activity Scale (PEG). DESIGN: Cross-sectional survey assessing demographics and pain impact. Crosswalks were developed using item response theory (IRT) co-calibrations and linear regressions between the ISS, ODI, RMDQ, and PEG. SETTING: Online panel. PARTICIPANTS: Population-based sample of U.S. adults aged 18 and older. Eligibility criteria were reporting currentback pain, not reporting two fake health conditions, and having data for two or more pain measures (N = 1,530; 37% of sample). Crosswalks were developed (n = 1,030) and cross-validated in a sub-sample of 500 participants (n = 125 randomly sampled from each ISS quartile). INTERVENTIONS: Not Applicable. MAIN OUTCOME MEASURES: ISS, ODI, RMDQ, and the PEG. RESULTS: Associations of the ISS with the PEG and ODI met the criteria for IRT co-calibration. Other measure pairs were cross-walked using regression. Associations were strongest between the PEG and the ISS (r = 0.87, Normalized Mean Absolute Error [NMAE] = 0.38) and between the ODI and the ISS (r = 0.85, NMAE = 0.39). Associations were weakest between the PEG and the RMDQ (r = 0.69, R2 = 0.48, NMAE: 0.55-0.58). Regression equations and IRT accounted for between 48% to 64% of the variance (NMAE: 0.38-0.58) in corresponding pain measures in the cross-validation sample. CONCLUSION: The crosswalks between the ISS and common legacy pain measures created in this study of a nationally representative sample of U.S. adults with back pain can be used to estimate one pain impact measure from another. Further evaluation in clinical samples is recommended.

Comparing patient-reported outcomes measurement information system® (PROMIS®)-16 domain scores with the PROMIS-29 and 5-item PROMIS cognitive function scores.

PURPOSE: This study evaluates the interpretability of Patient-Reported Outcomes Measurement Information System® (PROMIS®)-16 profile domain scores (physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function - abilities, and fatigue) compared to the PROMIS-29 scores and a 5-item PROMIS cognitive function score. The study aims to provide insights into using these measures in clinical and research settings. METHODS: Analyses were conducted using data from 4130 adults from a nationally representative, probability-based internet panel between September and October 2022. A subset of 1256 individuals with back pain was followed up at six months. We compared the PROMIS-16 profile with the corresponding domain scores from the PROMIS-29 and a custom five-item cognitive function measure. We evaluated (1) reliability through inter-item correlations within each domain and (2) criterion validity by comparing PROMIS-16 profile with the corresponding longer PROMIS measures: (a) standardized mean differences in domain scores, (b) correlations, and (c) concordance of change (i.e., got worse, stayed the same, got better) among those with back pain from baseline to six months later using the reliable change index. We report the Kappa coefficient of agreement and the frequency and percentage of participants with concordant classifications. RESULTS: Inter-item correlations for the PROMIS-16 domains ranged from 0.65 in cognitive function to 0.92 in pain interference. Standardized mean differences between PROMIS-16 and the scores for the corresponding longer PROMIS domains were minimal (< 0.2). Correlations among the corresponding domain scores ranged from 0.82 for sleep disturbance to 0.98 for pain interference. The percentage of concordance in change groups ranged from 63% for sleep disturbance to 88% for pain interference. Except for sleep disturbance, the change groups derived from the PROMIS-16 showed moderate to substantial agreement with scores estimated from the longer PROMIS measures (Kappa coefficients ≥ 0.41). CONCLUSION: The PROMIS-16 domain scores perform similarly to the longer PROMIS measures and can be interpreted in the same way. This similarity indicates that PROMIS-16 can be useful for research as a brief health-related quality-of-life profile measure.

The Patient-Reported Outcomes Measurement Information System^® (PROMIS^®)-16 Profile assesses eight health-related quality of life domains (physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function ­ abilities, and fatigue) using two items per domain. We evaluated the PROMIS-16 profile in a sample drawn from a nationally representative, probability-based internet panel. The study supports the reliability and criterion validity of the PROMIS-16, showing that the domain scores closely align with and have high concordance in change with the PROMIS-29 scores and a custom five-item cognitive function score. The PROMIS-16 has the potential to be a brief health-related quality-of-life profile measure in research and clinical settings.

Patterns of Social Needs Predict Quality-of-Life and Healthcare Utilization Outcomes in Patients from a Large Hospital System.

BACKGROUND: Unmet social needs (SNs) often coexist in distinct patterns within specific population subgroups, yet these patterns are understudied. OBJECTIVE: To identify patterns of social needs (PSNs) and characterize their associations with health-related quality-of-life (HRQoL) and healthcare utilization (HCU). DESIGN: Observational study using data on SNs screening, HRQoL (i.e., low mental and physical health), and 90-day HCU (i.e., emergency visits and hospital admission). Among patients with any SNs, latent class analysis was conducted to identify unique PSNs. For all patients and by race and age subgroups, compared with no SNs, we calculated the risks of poor HRQoL and time to first HCU following SNs screening for each PSN. PATIENTS: Adult patients undergoing SNs screening at the Mass General Brigham healthcare system in Massachusetts, United States, between March 2018 and January 2023. MAIN MEASURES: SNs included: education, employment, family care, food, housing, medication, transportation, and ability to pay for household utilities. HRQoL was assessed using the Patient-Reported Outcomes Measurement Information System Global-10. KEY RESULTS: Six unique PSNs were identified: "high number of social needs," "food and utility access," "employment needs," "interested in education," "housing instability," and "transportation barriers." In 14,230 patients with HRQoL data, PSNs increased the risks of poor mental health, with risk ratios ranging from 1.07(95%CI:1.01-1.13) to 1.80(95%CI:1.74-1.86). Analysis of poor physical health yielded similar findings, except that the "interested in education" showed a mild protective effect (0.97[95%CI:0.94-1.00]). In 105,110 patients, PSNs increased the risk of 90-day HCU, with hazard ratios ranging from 1.09(95%CI:0.99-1.21) to 1.70(95%CI:1.52-1.90). Findings were generally consistent in subgroup analyses by race and age. CONCLUSIONS: Certain SNs coexist in distinct patterns and result in poorer HRQoL and more HCU. Understanding PSNs allows policymakers, public health practitioners, and social workers to identify at-risk patients and implement integrated, system-wide, and community-based interventions.

The PROMIS-16 reproduces the PROMIS-29 physical and mental health summary scores accurately in a probability-based internet panel.

PURPOSE: The Patient-Reported Outcomes Measurement Information System® (PROMIS)-16 assesses the same multi-item domains but does not include the pain intensity item in the PROMIS-29. We evaluate how well physical and mental health summary scores estimated from the PROMIS-16 reproduce those estimated using the PROMIS-29. METHODS: An evaluation of data collected from 4130 respondents from the KnowledgePanel. Analyses include confirmatory factor analysis to assess physical and mental health latent variables based on PROMIS-16 scores, reliability estimates for the PROMIS measures, mean differences and correlations of scores estimated by the PROMIS-16 with those estimated by the PROMIS-29, and associations between differences in corresponding PROMIS-16 and PROMIS-29 scores by sociodemographic characteristics. RESULTS: A two-factor (physical and mental health) model adequately fits the PROMIS-16 scores. Reliability estimates for the PROMIS-16 measures were slightly lower than for the PROMIS-29 measures. There were minimal differences between PROMIS physical and mental health summary scores estimated using the PROMIS-16 or the PROMIS-29. PROMIS-16 and PROMIS-29 score differences by sociodemographic characteristics were small. Using the PROMIS pain intensity item when scoring the PROMIS-16 produced similar estimates of physical and mental health summary scores. CONCLUSION: The PROMIS-16 provides similar estimates of the PROMIS-29 physical and mental health summary scores. The high reliability of these scores indicates they are accurate enough for use with individual patients.

The Edmonton Symptom Assessment System is a valid, reliable, and responsive tool to assess symptom burden in decompensated cirrhosis.

BACKGROUND: While there is a growing need for interventions addressing symptom burden in patients with decompensated cirrhosis (DC), the lack of validated symptom assessment tools is a critical barrier. We investigated the psychometric properties of the revised Edmonton Symptom Assessment System (ESAS-r) in a longitudinal cohort of patients with DC. METHODS: Adult outpatients with DC were prospectively recruited from a liver transplant center and completed ESAS-r at baseline and week 12. We examined reliability, floor/ceiling effects, structural validity, and known-groups validity. We examined the convergent and predictive validity of ESAS-r with health-related quality of life using the Short Form Liver Disease Quality of Life (SF-LDQOL) and responsiveness to changes in anxiety and depression using the Hospital Anxiety and Depression Scale and Patient Health Questionnaire-9 from baseline to week 12. RESULTS: From August 2018 to September 2022, 218 patients (9% Child-Pugh A, 59% Child-Pugh B, and 32% Child-Pugh C) were prospectively recruited and completed the ESAS-r, SF-LDQOL, Patient Health Questionnaire-9, and Hospital Anxiety and Depression Scale at baseline and week 12 (n = 135). ESAS-r had strong reliability (Cronbach's alpha 0.86), structural validity (comparative fit index 0.95), known-groups validity (Child-Pugh A: 25.1 vs. B: 37.5 vs. C: 41.4, p = 0.006), and convergent validity (r = -0.67 with SF-LDQOL). Floor effects were 9% and ceiling effects were 0.5%. Changes in ESAS-r scores from baseline to week 12 significantly predicted changes in SF-LDQOL (ß = -0.36, p < 0.001), accounting for 30% of the variation. ESAS-r was strongly responsive to clinically meaningful changes in SF-LDQOL, Patient Health Questionnaire-9, and Hospital Anxiety and Depression Scale. CONCLUSIONS: ESAS-r is a reliable, valid, and responsive tool for assessing symptom burden in patients with DC and can predict changes in health-related quality of life. Future directions include its implementation as a key outcome measure in cirrhosis care and clinical trials.

Low body mass index as a predictor of sputum culture conversion and treatment outcomes among patients receiving treatment for multidrug-resistant tuberculosis in Lesotho.

BACKGROUND: A low body mass index (BMI) at the start of treatment for rifampicin- or multidrug-resistant tuberculosis (MDR/RR-TB) is associated with poor treatment outcomes and may contribute to delayed sputum culture conversion, thereby prolonging the period of potential transmission to others. Whether the relative importance of low BMI in predicting treatment outcomes differs by HIV status is unclear. OBJECTIVES: We evaluated the association between low BMI and two dependent variables, sputum culture conversion and end-of-treatment outcome, among patients receiving treatment for MDR/RR-TB in Lesotho, a setting with a high prevalence of HIV infection. METHODS: Secondary data from a prospective cohort of patients initiating a longer (18-20 months) treatment containing bedaquiline and/or delamanid under routine programmatic conditions in Lesotho were analysed. Risk ratios and differences were adjusted for potential confounders using multivariable logistic regression, and estimates were stratified by HIV status. RESULTS: Of 264 patients, 105 and 250 were eligible for culture conversion and end-of-treatment analyses, respectively. Seventy-one per cent of patients (74/105) experienced culture conversion within six months, while 74% (184/250) experienced a favourable end-of-treatment outcome. Low BMI was associated with a lower frequency of culture conversion at six months among those who were not living with HIV (relative risk [RR]: 0.50 [95% CI: 0.21, 0.79]); this association was attenuated among those living with HIV (RR: 0.88 [95% CI: 0.68, 1.23]). A low BMI was moderately associated with a lower frequency of treatment success (RR = 0.89 [95% CI: 0.77, 1.03]), regardless of HIV status. CONCLUSIONS: Low BMI was common and associated with the frequency of six-month culture conversion and end-of-treatment outcomes. The association with culture conversion was more pronounced among those not living with HIV. Addressing the myriad factors that drive low BMI in this setting could hasten culture conversion and improve end-of-treatment outcomes. This will require a multipronged approach focused on alleviating food insecurity and enabling prompt diagnosis and treatment of HIV and TB.

Development of an ultra-short measure of eight domains of health-related quality of life for research and clinical care: the patient-reported outcomes measurement information system® PROMIS®-16 profile.

PURPOSE: We describe development of a short health-related quality of life measure, the patient-reported outcomes measurement information system® (PROMIS®)-16 Profile, which generates domain-specific scores for physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function, and fatigue. METHODS: An empirical evaluation of 50 candidate PROMIS items and item pairs was conducted using data from a sample of 5775 respondents from Amazon's Mechanical Turk (MTurk). Results and item response theory information curves for a subset of item pairs were presented and discussed in a stakeholder meeting to narrow the candidate item sets. A survey of the stakeholders and 124 MTurk adults was conducted to solicit preferences among remaining candidate items and finalize the measure. RESULTS: Empirical evaluation showed minimal differences in basic descriptive statistics (e.g., means, correlations) and associations with the PROMIS-29 + 2 Profile, thus item pairs were further considered primarily based on item properties and content. Stakeholders discussed and identified subsets of candidate item pairs for six domains, and final item pairs were agreed upon for two domains. Final items were selected based on stakeholder and MTurk-respondent preferences. The PROMIS-16 profile generates eight domain scores with strong psychometric properties. CONCLUSION: The PROMIS-16 Profile provides an attractive brief measure of eight distinct domains of health-related quality of life, representing an ideal screening tool for clinical care, which can help clinicians quickly identify distinct areas of concern that may require further assessment and follow-up. Further research is needed to confirm and extend these findings.

Effectiveness of a bedaquiline, linezolid, clofazimine "core" for multidrug-resistant tuberculosis.

Rationale: Treatment outcomes may be compromised among patients with multidrug- or rifampicin-resistant tuberculosis with additional fluoroquinolone resistance. Evidence is needed to inform optimal treatment for these patients. Objectives: We compared the effectiveness of longer individualized regimens comprised of bedaquiline for 5 to 8 months, linezolid, and clofazimine to those reinforced with at least 1 third-tier drug and/or longer duration of bedaquiline. Methods: We emulated a target trial to compare the effectiveness of initiating and remaining on the core regimen to one of five regimens reinforced with (1) bedaquiline for ≥9 months, (2) bedaquiline for ≥9 months and delamanid, (3) imipenem, (4) a second-line injectable, or (5) delamanid and imipenem. We included patients in whom a fluoroquinolone was unlikely to be effective based on drug susceptibility testing and/or prior exposure. Our analysis consisted of cloning, censoring, and inverse-probability weighting to estimate the probability of successful treatment. Measurements and Main Results: Adjusted probabilities of successful treatment were high across regimens, ranging from 0.75 (95%CI:0.61, 0.89) to 0.84 (95%CI:0.76, 0.91). We found no substantial evidence that any of the reinforced regimens improved effectiveness of the core regimen, with ratios of treatment success ranging from 1.01 for regimens reinforced with bedaquiline ≥9 months (95%CI:0.79, 1.28) and bedaquiline ≥9 months plus delamanid (95%CI:0.81, 1.31) to 1.11 for regimens reinforced by a second-line injectable (95%CI:0.92, 1.39) and delamanid and imipenem (95%CI:0.90, 1.41). Conclusions: High treatment success underscores the effectiveness of regimens comprised of bedaquiline, linezolid, and clofazimine, highlighting the need for expanded access to these drugs.

Social Determinants of Health Needs and Health-related Quality of Life Among Surgical Patients: A Retrospective Analysis of 8512 Patients.

OBJECTIVE: To assess associations between social determinants of health (SDOH) needs and health-related quality of life (HRQOL) among surgical patients. BACKGROUND: Despite the profound impact of SDOH on health outcomes, studies examining the effect of SDOH needs on HRQOL among surgical patients are limited. METHODS: A retrospective study was conducted using responses from the SDOH needs assessment and the Patient-Reported Outcomes Measurement Information Systems Global Health instrument of adults seen in surgical clinics at a single institution. Patient characteristics including socioeconomic status (insurance type, education level, and employment status) were extracted. Stepwise multivariable logistic regression analyses were performed to identify independent predictors of global health scores. RESULTS: A total of 8512 surgical patients (mean age: 55.6±15.8 years) were included. 25.2% of patients reported one or more SDOH needs. The likelihood of reporting at least one SDOH need varied by patient characteristics and socioeconomic status variables. In fully adjusted regression models, food insecurity [odds ratio (OR), 1.53; 95% CI, 1.38-1.70 and OR, 1.49; 95% CI, 1.22-1.81, respectively], housing instability (OR, 1.27; 95% CI, 1.12-1.43 and OR, 1.39; 95% CI, 1.13-1.70, respectively) lack of transportation (OR, 1.46; 95% CI, 1.27-1.68 and OR, 1.25; 95% CI, 1.00-1.57, respectively), and unmet medication needs (OR, 1.31; 95% CI, 1.13-1.52 and OR, 1.61; 95% CI, 1.28-2.03, respectively) were independent predictors of poor physical and mental health. CONCLUSIONS: SDOH needs are independent predictors of poor patient-reported physical and mental health among surgical patients. Assessing and addressing SDOH needs should be prioritized in health care settings and by policymakers to improve HRQOL.

Residential Segregation and County-Level COVID-19 Booster Coverage in the Deep South: Surveillance Report and Ecological Study.

BACKGROUND: COVID-19 had a greater impact in the Deep South compared with other regions in the United States. While vaccination remains a top priority for all eligible individuals, data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age are sparse. Despite existing evidence of racial and ethnic disparities in COVID-19 vaccinations at the individual level, there is an urgent need for evidence at the population level. Such information could highlight vulnerable communities and guide future health care policy-making and resource allocation. OBJECTIVE: We aimed to evaluate county-level COVID-19 booster coverage by age group in the Deep South and explore its association with residential segregation. METHODS: An ecological study was conducted at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of 5 Deep South states from December 15, 2021, to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster uptake by age group (eg, 12 to 17 years, 18 to 64 years, and at least 65 years) by the end of the study period. The longitudinal relationships were examined between residential segregation, the interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson model. RESULTS: As of October 19, 2022, among the 418 counties, the median of booster uptake was 40% (IQR 37.8%-43%). Compared with older adults (ie, at least 65 years; median 63.1%, IQR 59.5%-66.5%), youth (ie, 12 to 17 years; median 14.1%, IQR 11.3%-17.4%) and adults (ie, 18 to 64 years; median 33.4%, IQR 30.5%-36.5%) had lower percentages of booster uptake. There was geospatial heterogeneity in the county-level COVID-19 booster coverage. We found that higher segregated counties had lower percentages of booster coverage. Such relationships attenuated as time increased. The findings were consistent across the age groups. CONCLUSIONS: The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccination strategies should focus on youth and adults. Health care facilities and resources are needed in racial and ethnic minority communities.

County-level variations in linkage to care among people newly diagnosed with HIV in South Carolina: A longitudinal analysis from 2010 to 2018.

BACKGROUND: Timely linkage to care (LTC) is key in the HIV care continuum, as it enables people newly diagnosed with HIV (PNWH) to benefit from HIV treatment at the earliest stage. Previous studies have found LTC disparities by individual factors, but data are limited beyond the individual level, especially at the county level. This study examined the temporal and geographic variations of county-level LTC status across 46 counties in South Carolina (SC) from 2010 to 2018 and the association of county-level characteristics with LTC status. METHODS: All adults newly diagnosed with HIV from 2010 to 2018 in SC were included in this study. County-level LTC status was defined as 1 = "high LTC (≥ yearly national LTC percentage)" and 0 = "low LTC (< yearly national LTC percentage)". A generalized estimating equation model with stepwise selection was employed to examine the relationship between 29 county-level characteristics and LTC status. RESULTS: The number of counties with high LTC in SC decreased from 34 to 21 from 2010 to 2018. In the generalized estimating equation model, six out of 29 factors were significantly associated with LTC status. Counties with a higher percentage of males (OR = 0.07, 95%CI: 0.02~0.29) and persons with at least four years of college (OR = 0.07, 95%CI: 0.02~0.34) were less likely to have high LTC. However, counties with more mental health centers per PNWH (OR = 45.09, 95%CI: 6.81~298.55) were more likely to have high LTC. CONCLUSIONS: Factors associated with demographic characteristics and healthcare resources contributed to the variations of LTC status at the county level. Interventions targeting increasing the accessibility to mental health facilities could help improve LTC.

Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A case study of South Carolina.

Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has emerged as a valuable data source for revealing fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate the second wave spreading of COVID-19 in January 2021 in three major metropolitan statistical areas (Columbia, Greenville, and Charleston) in South Carolina, United States. Based on the simulation, the number of historical county-level COVID-19 cases was allocated to neighborhoods (Census block groups) and points of interest (POIs), and the transmission rate of each allocated place was estimated. The result reveals that the COVID-19 infections during the study period mainly occurred in neighborhoods (86%), and the number is approximately proportional to the neighborhood's population. Restaurants and elementary and secondary schools contributed more COVID-19 infections than other POI categories. The simulation results for the coastal tourism Charleston area show high transmission rates in POIs related to travel and leisure activities. The results suggest that neighborhood-level infectious controlling measures are critical in reducing COVID-19 infections. We also found that households of lower socioeconomic status may be an umbrella against infection due to fewer visits to places such as malls and restaurants associated with their low financial status. Control measures should be tailored to different geographic locations since transmission rates and infection counts of POI categories vary among metropolitan areas.

Associations between HIV disclosure and HIV care continuum outcomes among men who have sex with men living with HIV: systematic review and meta-analysis.

ABSTRACTThe objective of this study is to synthesize the existing empirical literature and perform a systematic review and meta-analysis on the relationship between HIV disclosure and engagement in the HIV care continuum among men who have sex with men living with HIV. Twenty-three studies were included, with thirteen quantitative studies and ten qualitative studies. Meta-analytic techniques were used to compute and aggregate effect sizes (odds ratio [OR] and their confidence intervals [95%CI]) for the quantitative studies and a thematic analysis was employed for qualitative studies. Given the small number of eligible studies, meta-analysis was only conducted for the linkage to care outcome, where a positive association was observed from the pooled estimation (OR = 1.51, 95%CI [1.15, 1.99]). Regarding ART initiation, retention in care, and viral suppression outcomes, most of the individual studies revealed a positive association between HIV disclosure and these outcomes. Thematic analysis from qualitative studies complemented the quantitative findings by incorporating the approaching and avoidance motivations underlying the relationship between non-HIV disclosure and the participation in HIV care continuum. The small number of available studies limits the definitive conclusions, and more research is needed to ascertain the magnitude of effect sizes.

Using Twitter Data to Estimate the Prevalence of Symptoms of Mental Disorders in the United States During the COVID-19 Pandemic: Ecological Cohort Study.

BACKGROUND: Existing research and national surveillance data suggest an increase of the prevalence of mental disorders during the COVID-19 pandemic. Social media platforms, such as Twitter, could be a source of data for estimation owing to its real-time nature, high availability, and large geographical coverage. However, there is a dearth of studies validating the accuracy of the prevalence of mental disorders on Twitter compared to that reported by the Centers for Disease Control and Prevention (CDC). OBJECTIVE: This study aims to verify the feasibility of Twitter-based prevalence of mental disorders symptoms being an instrument for prevalence estimation, where feasibility is gauged via correlations between Twitter-based prevalence of mental disorder symptoms (ie, anxiety and depressive symptoms) and that based on national surveillance data. In addition, this study aims to identify how the correlations changed over time (ie, the temporal trend). METHODS: State-level prevalence of anxiety and depressive symptoms was retrieved from the national Household Pulse Survey (HPS) of the CDC from April 2020 to July 2021. Tweets were retrieved from the Twitter streaming application programming interface during the same period and were used to estimate the prevalence of symptoms of mental disorders for each state using keyword analysis. Stratified linear mixed models were used to evaluate the correlations between the Twitter-based prevalence of symptoms of mental disorders and those reported by the CDC. The magnitude and significance of model parameters were considered to evaluate the correlations. Temporal trends of correlations were tested after adding the time variable to the model. Geospatial differences were compared on the basis of random effects. RESULTS: Pearson correlation coefficients between the overall prevalence reported by the CDC and that on Twitter for anxiety and depressive symptoms were 0.587 (P<.001) and 0.368 (P<.001), respectively. Stratified by 4 phases (ie, April 2020, August 2020, October 2020, and April 2021) defined by the HPS, linear mixed models showed that Twitter-based prevalence for anxiety symptoms had a positive and significant correlation with CDC-reported prevalence in phases 2 and 3, while a significant correlation for depressive symptoms was identified in phases 1 and 3. CONCLUSIONS: Positive correlations were identified between Twitter-based and CDC-reported prevalence, and temporal trends of these correlations were found. Geospatial differences in the prevalence of symptoms of mental disorders were found between the northern and southern United States. Findings from this study could inform future investigation on leveraging social media platforms to estimate symptoms of mental disorders and the provision of immediate prevention measures to improve health outcomes.

Perioperative Risk Factors Associated With Unplanned Reoperation Following Vascularized Free Flaps Reconstruction of the Oral Squamous Cell Carcinoma.

OBJECTIVES: To find out the occurrence rate and risk factors of unplanned reoperation (any unscheduled surgery within 30 d after the initial surgery) in patients who have received oral squamous cell carcinoma (OSCC) surgery and vascularized free flap reconstruction. PATIENTS AND METHODS: We organized a retrospective study of 1058 patients who underwent OSCC resection and reconstruction with vascularized free flaps from 2011 to 2019. Clinical characteristics, reasons for unplanned reoperation, flap types, and previous treatment were compared between the unplanned reoperation group and the control group. Univariate and multivariate analyses were performed to identify perioperative risk factors for unplanned reoperation. The related perioperative factors that may influence perioperative infusion were included in propensity score matching to investigate the independent contribution of intraoperative colloid infusion on unplanned reoperation. RESULTS: The overall rate of unplanned reoperation in OSCC patients was 11% (n=115). Flap necrosis and bleeding were the most common causes. Higher American Society of Anesthesiologists (ASA) grade [odds ratio (OR)=1.709, P=0.009], postoperative anemia (OR=0.983, P=0.011) and excessive intraoperative colloid input (OR=1.55, P=0.037) were identified as risk factors for unplanned reoperation. Propensity score matching was applied, and the difference of unplanned reoperation incidence between the matched groups was statistically significant (14.59% versus 8.54%; P=0.025). The multivariate analyses after propensity score matching confirmed that the intraoperative rate of colloid infusion of more than 2.3 mL/kg/h (OR=1.756, P=0.042) and prior radiotherapy (OR=2.78, P=0.001) are independent risk factors for unplanned reoperation. CONCLUSION: High intraoperative colloid infusion rate and prior radiotherapy may increase the risk of unplanned reoperation in patients who underwent OSCC surgery and vascularized free flap reconstruction.

Clinical Outcomes of Individuals with COVID-19 and Tuberculosis during the Pre-Vaccination Period of the Pandemic: A Systematic Review.

BACKGROUND: Tuberculosis, like COVID-19, is most often a pulmonary disease. The COVID-19 pandemic has severely disrupted tuberculosis services in myriad ways: health facility closures, lockdowns, travel bans, overwhelmed healthcare systems, restricted export of antituberculous drugs, etc. The effects of the shared risk on outcomes of the two diseases is not known, particularly for the first year of the pandemic, during the period before COVID-19 vaccines became widely available. OBJECTIVE: We embarked on a systematic review to elucidate the consequences of tuberculosis on COVID-19 outcomes and of COVID-19 on tuberculosis outcomes during the pre-vaccination period of the pandemic. METHODS: The systematic review protocol is registered in PROSPERO. We conducted an initial search of PubMed, Embase, Web of Science, WHO coronavirus database, medRxiv, bioRxiv, preprints.org, and Google Scholar using terms relating to COVID-19 and tuberculosis. We selected cohort and case-control studies for extraction and assessed quality with the Newcastle-Ottawa scale. RESULTS AND CONCLUSION: We identified 2108 unique abstracts published between December 2019 and January 2021. We extracted data from 18 studies from 8 countries. A total of 650,317 persons had a diagnosis of COVID-19, and 4179 had a diagnosis of current or prior tuberculosis. We explored links between tuberculosis and COVID-19 incidence, mortality, and other adverse outcomes. Nine studies reported on mortality and 13 on other adverse outcomes; results on the association between tuberculosis and COVID-19 mortality/adverse outcomes were heterogenous. Tuberculosis outcomes were not fully available in any studies, due to short follow-up (maximum of 3 months after COVID-19 diagnosis), so the effects of COVID-19 on tuberculosis outcomes could not be assessed. Much of the rapid influx of literature on tuberculosis and COVID-19 during this period was published on preprint servers, and therefore not peer-reviewed. It offered limited examination of the effect of tuberculosis on COVID-19 outcomes and even less on the effect of COVID-19 on tuberculosis treatment outcomes.

Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A Case Study of South Carolina.

Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has been an emerging data source to reveal fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate the second wave spreading of COVID-19 in January 2021 in three major metropolitan statistical areas (Columbia, Greenville, and Charleston) in South Carolina, United States. Based on the simulation, the number of historical county-level COVID-19 cases was allocated to neighborhoods (Census blockgroups) and points of interest (POIs), and the transmission rate of each allocated place was estimated. The result reveals that the COVID-19 infections during the study period mainly occurred in neighborhoods (86%), and the number is approximately proportional to the neighborhood’s population. Restaurants and elementary and secondary schools contributed more COVID-19 infections than other POI categories. The simulation results for the coastal tourism Charleston area show high transmission rates in POIs related to travel and leisure activities. The results suggest that the neighborhood-level infectious controlling measures are critical in reducing COVID-19 infections. We also found that the households of lower socioeconomic status may be an umbrella against infection due to fewer visits to places such as malls and restaurants associated with their low financial status. Control measures should be tailored to different geographic locations since transmission rates and infection counts of POI categories vary among metropolitan areas.

Population Mobility and Aging Accelerate the Transmission of Coronavirus Disease 2019 in the Deep South: A County-Level Longitudinal Analysis.

Population mobility and aging at local areas contributed to the geospatial disparities in the coronavirus disease 2019 (COVID-19) transmission among 418 counties in the Deep South. In predicting the incidence of COVID-19, a significant interaction was found between mobility and the proportion of older adults. Effective disease control measures should be tailored to vulnerable communities.