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1. Prevalence of Chronic Obstructive Pulmonary Disease and its Associated Factors in Nepal: Findings from a Community-based Household Survey

Author

Adhikari TB, Acharya P, Högman M, Neupane D, Karki A, Drews A, Cooper BG, Sigsgaard T, and Kallestrup P

Subjects
copd, nepal, prevalence, ncd, Diseases of the respiratory system, RC705-779
Abstract

Tara Ballav Adhikari,1,2 Pawan Acharya,1,3 Marieann Högman,4 Dinesh Neupane,1,5 Arjun Karki,6 Arne Drews,7 Brendan G Cooper,8 Torben Sigsgaard,9 Per Kallestrup2 1COBIN Project, Nepal Development Society, Bharatpur, Chitwan, Nepal; 2Center for Global Health, Department of Public Health, Aarhus University, Aarhus, Denmark; 3Hudson College of Public Health, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; 4Department of Medical Sciences, Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden; 5Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA; 6Department of Pulmonary, Critical Care and Sleep Medicine, HAMS Hospital, Kathmandu, Nepal; 7Nepalmed, Leipzig, Germany; 8Lung Function and Sleep, University Hospitals Birmingham, Birmingham, UK; 9Department of Public Health, Section for Environment, Occupation & Health, Aarhus University, Aarhus, DenmarkCorrespondence: Tara Ballav AdhikariCenter for Global Health, Department of Public Health, Aarhus University, Aarhus 8000, Denmark, Email tba@ph.au.dkBackground: Despite chronic obstructive pulmonary disease (COPD) being the commonest non-communicable disease in Nepal, there is limited research evidence estimating the spirometry-based burden of COPD. This study aims to estimate the prevalence of COPD and its correlates through a community-based survey in Pokhara Metropolitan City, a semi-urban area of Western Nepal.Methods: A cross-sectional household survey was conducted among 1459 adults ≥ 40 years. COPD was defined according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria as a post-bronchodilator ratio of forced expiratory volume in 1st second (FEV1) to forced vital capacity (FVC) < 0.70 with the presence of symptoms. COPD was also defined by the lower limit of normal (LLN) threshold – FEV1/FVC < LLN cut-off values with the presence of symptoms. Study participants were interviewed about sociodemographic and behavioural characteristics and respiratory symptoms. Descriptive statistics and logistic regression analysis were applied.Results: Spirometry reports were acceptable in 1438 participants. The mean age of the participants was 55 (± 10) years, and, 54% were female. The prevalence of GOLD-defined COPD was 8.5% (95% CI: 7.1– 10.0) and based on the LLN threshold of 5.4% (95% CI: 4.2– 6.6). The multivariate logistic regression showed that increasing age, low body mass index, illiterate, current or former smoker, and biomass fuel smoke increased the odds of COPD in both the definitions.Conclusion: COPD is highly prevalent at community level and often underdiagnosed. Strategies aiming at early diagnosis and treatment of COPD, especially for the elderly, illiterate, and reducing exposure to smoking and biomass fuel smoke and childhood lung infection could be effective.Keywords: COPD, Nepal, prevalence, NCD

Published
2020

2. Burden of COPD in Nepal

Author

Adhikari TB, Neupane D, and Kallestrup P

Subjects
Burden of disease, disability-adjusted life years (DALYs), Chronic Obstructive Pulmonary Disease (COPD), COPD, Nepal, Diseases of the respiratory system, RC705-779
Abstract

Tara Ballav Adhikari,1 Dinesh Neupane,1,2 Per Kallestrup3 1Nepal Development Society, Chitwan, Nepal; 2Global Health Research Center, Duke Kunshan University, Kunshan, People’s Republic of China; 3Center for Global Health (GloHAU), Department of Public Health, Aarhus University, Aarhus, Denmark Background: COPD is a globally significant public health problem and is the second leading cause of mortality. This study presents the health burden of COPD in Nepal using the Global Burden of Disease (GBD) study 2016 dataset. Methods: This study used the data from the GBD repository presenting morbidity and mortality attributed to COPD, by sex and age. In GBD 2016, due to a lack of the primary source of data in Nepal, estimations on morbidity and mortality of COPD were based on its predictive covariates. Years of life lost (YLLs) were calculated based on the cause of death estimations, applying GBD’s Cause of Death Ensemble modeling. Likewise, years lived with disability (YLDs) were calculated by multiplying the prevalence of each sequela by the disability weight. Disability-adjusted life years (DALYs) were derived as the sum of YLLs and YLDs. Results: Between 1990 and 2016, the estimated age-standardized mortality rate due to COPD was decreasing for both genders, but the decline was much higher among males. Unlike the high rate of incidence among males, the age-standardized DALYs were found to be high among females (2,274.9 [95% UI: 1,702.0–2,881.5] per 100,000). YLLs contributed around 80% of DALYs due to COPD in 2016. Age-standardized YLLs rate was higher among females, with a value of 1,860 (95% uncertainty interval (UI): 1,282.8–2,472.8) vs 1,547.6 (95% UI: 992.1–2,018.5) among the males per 100,000 population. Conclusion: The prevalence and incidence of COPD remained almost stationary over the years, but still very high. Though the incidence and prevalence of disease were high among males, the death rate and DALYs were more significant among females throughout the years. If the current situation prevails, the burden of COPD will continue to increase in the country. Hence, comprehensive social, environmental, and behavioral approaches to curtail the risk factors along with early identification, treatment, and management of COPD is of utmost importance. Keywords: DALYs, disability, mortality, burden of illness, GBD

Published
2018

6. May Measurement Month 2017: an analysis of blood pressure screening results worldwide

Author

Napiza-Granada, C, Sevilla, Ma. RC, Atilano, AA, Ona, DID, More, A, Jose, AP, Maheshwari, A, Kondal, D, Yu, W, Li, W, Xu, S, Yu, J, Zhang, H, Widyantoro, B, Turana, Y, Situmorang, TD, Sofiatin, Y, Barack, R, Lin, H-J, Wang, T-D, Chen, W-J, Sirenko, Y, Evstigneeva, O, Negresku, E, Yousif, ME, Medani, SA, Beheiry, HM, Ali, IA, Zilberman, JM, Marin, MJ, Rodriguez, PD, Garcia-Vasquez, F, Kramoh, KE, Ekoua, D, Lopez-Jaramillo, P, Otero, J, Sanchez, G, Narvaez, C, Accini, JL, Hernandez-Hernandez, R, Octavio, JA, Morr, I, Lopez-Rivera, J, Ojji, D, Arije, A, Babatunte, A, Wahab, KW, Fernandes, M, Pereira, SV, Valentim, M, Dzudie, A, Kingue, S, Djomou Ngongang, DA, Ogola, EN, Barasa, FA, Gitura, B, Malik, F-T-N, Choudhury, SR, Al Mamun, MA, Minh, VH, Viet, NL, Cao Truong, S, Ferri, C, Parati, G, Torlasco, C, Borghi, C, Goma, FM, Syatalimi, C, Zelveian, PH, Barbosa, E, Sebba Barroso, W, Penaherrera, E, Jarrin, E, Yusufali, A, Bazargani, N, Tsinamdzgvrishvili, B, Trapaidze, D, Neupane, D, Mishra, SR, Jozwiak, J, Malyszko, J, Konradi, A, Chazova, I, Ishaq, M, Memon, F, Heagerty, AM, Keitley, J, Brady, AJB, Cockcroft, JR, McDonnell, BJ, Lanas, F, Chia, Y-C, Ndhlovu, H, Kiss, I, Ruilope, LM, Ellenga Mbolla, BF, Milhailidou, AS, Woodiwiss, AJ, Perl, S, Dolan, E, Azevedo, V, Garre, L, Boggia, JG, Lee, VWY, Kowlessur, S, Miglinas, M, Sukackiene, D, Wainford, RD, Habonimana, D, Masupe, T, Ortellado, J, Wuerzner, G, Alcocer, L, Burazeri, G, Sanchez Delgado, E, Lovic, D, Mondo, CK, Mostafa, A, Nadar, SK, Valdez Tiburcio, O, Leiba, A, Dorobantu, M, De Backer, T, Chifamba, J, Stergiou, G, Nwokocha, CR, Sokolovic, S, Toure, AI, Connell, KL, Khan, NA, Burger, D, De Carvalho Rodrigues, M, Kramer, BK, Schmieder, RE, Unger, T, Wyss, FS, Yameogo, NV, Beistline, H, Kenerson, JG, Alfonso, B, Olsen, MH, Soares, M, Beaney, Thomas, Schutte, Aletta E, Tomaszewski, Maciej, Ariti, Cono, Burrell, Louise M, Castillo, Rafael R, Charchar, Fadi J, Damasceno, Albertino, Kruger, Ruan, Lackland, Daniel T, Nilsson, Peter M, Prabhakaran, Dorairaj, Ramirez, Agustin J, Schlaich, Markus P, Wang, Jiguang, Weber, Michael A, and Poulter, Neil R

Published
2018
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7. Comparison of the Accuracy of the 7-Item HADS Depression Subscale and 14-Item Total HADS for Screening for Major Depression: A Systematic Review and Individual Participant Data Meta-Analysis

Author

Wu, Y, Levis, B, Daray, FM, Ioannidis, JPA, Patten, SB, Cuijpers, P, Ziegelstein, RC, Gilbody, S, Fischer, FH, Fan, S, Sun, Y, He, C, Krishnan, A, Neupane, D, Bhandari, PM, Negeri, Z, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Imran, M, Chiovitti, MJ, Boruff, JT, McMillan, D, Kloda, LA, Markham, S, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Al-Adawi, S, Beck, KR, Beraldi, A, Bernstein, CN, Boye, B, Buel-Drabe, N, Bunevicius, A, Can, C, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Costa-Requena, G, Cukor, D, Dabscheck, E, De Souza, J, Downing, M, Feinstein, A, Ferentinos, PP, Flint, AJ, Gallagher, P, Gandy, M, Grassi, L, Haerter, M, Hernando, A, Jackson, ML, Jenewein, J, Jette, N, Juliao, M, Kjaergaard, M, Kohler, S, Konig, H-H, Krishna, LKR, Lee, Y, Loebner, M, Loosman, WL, Love, AW, Loewe, B, Malt, UF, Marrie, RA, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Nelson, CJ, Ng, CG, O'Donnell, ML, O'Rourke, SJ, Ozturk, A, Pabst, A, Pasco, JA, Peceliuniene, J, Pintor, L, Ponsford, JL, Pulido, F, Quinn, TJ, Reme, SE, Reuter, K, Riedel-Heller, SG, Rooney, AG, Sanchez-Gonzalez, R, Saracino, RM, Schellekens, MPJ, Scherer, M, Schwarzbold, ML, Cankorur, VS, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Strobe, NA, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, Weyerer, SB, White, J, Wiese, B, Williams, LJ, Wong, L-Y, Benedetti, A, Thombsi, BD, Wu, Y, Levis, B, Daray, FM, Ioannidis, JPA, Patten, SB, Cuijpers, P, Ziegelstein, RC, Gilbody, S, Fischer, FH, Fan, S, Sun, Y, He, C, Krishnan, A, Neupane, D, Bhandari, PM, Negeri, Z, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Imran, M, Chiovitti, MJ, Boruff, JT, McMillan, D, Kloda, LA, Markham, S, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Al-Adawi, S, Beck, KR, Beraldi, A, Bernstein, CN, Boye, B, Buel-Drabe, N, Bunevicius, A, Can, C, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Costa-Requena, G, Cukor, D, Dabscheck, E, De Souza, J, Downing, M, Feinstein, A, Ferentinos, PP, Flint, AJ, Gallagher, P, Gandy, M, Grassi, L, Haerter, M, Hernando, A, Jackson, ML, Jenewein, J, Jette, N, Juliao, M, Kjaergaard, M, Kohler, S, Konig, H-H, Krishna, LKR, Lee, Y, Loebner, M, Loosman, WL, Love, AW, Loewe, B, Malt, UF, Marrie, RA, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Nelson, CJ, Ng, CG, O'Donnell, ML, O'Rourke, SJ, Ozturk, A, Pabst, A, Pasco, JA, Peceliuniene, J, Pintor, L, Ponsford, JL, Pulido, F, Quinn, TJ, Reme, SE, Reuter, K, Riedel-Heller, SG, Rooney, AG, Sanchez-Gonzalez, R, Saracino, RM, Schellekens, MPJ, Scherer, M, Schwarzbold, ML, Cankorur, VS, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Strobe, NA, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, Weyerer, SB, White, J, Wiese, B, Williams, LJ, Wong, L-Y, Benedetti, A, and Thombsi, BD

Abstract

The seven-item Hospital Anxiety and Depression Scale Depression subscale (HADS-D) and the total score of the 14-item HADS (HADS-T) are both used for major depression screening. Compared to the HADS-D, the HADS-T includes anxiety items and requires more time to complete. We compared the screening accuracy of the HADS-D and HADS-T for major depression detection. We conducted an individual participant data meta-analysis and fit bivariate random effects models to assess diagnostic accuracy among participants with both HADS-D and HADS-T scores. We identified optimal cutoffs, estimated sensitivity and specificity with 95% confidence intervals, and compared screening accuracy across paired cutoffs via two-stage and individual-level models. We used a 0.05 equivalence margin to assess equivalency in sensitivity and specificity. 20,700 participants (2,285 major depression cases) from 98 studies were included. Cutoffs of ≥7 for the HADS-D (sensitivity 0.79 [0.75, 0.83], specificity 0.78 [0.75, 0.80]) and ≥15 for the HADS-T (sensitivity 0.79 [0.76, 0.82], specificity 0.81 [0.78, 0.83]) minimized the distance to the top-left corner of the receiver operating characteristic curve. Across all sets of paired cutoffs evaluated, differences of sensitivity between HADS-T and HADS-D ranged from -0.05 to 0.01 (0.00 at paired optimal cutoffs), and differences of specificity were within 0.03 for all cutoffs (0.02-0.03). The pattern was similar among outpatients, although the HADS-T was slightly (not nonequivalently) more specific among inpatients. The accuracy of HADS-T was equivalent to the HADS-D for detecting major depression. In most settings, the shorter HADS-D would be preferred. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Published
2023

14. Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression : updated systematic review and individual participant data meta-analysis

Author

Negeri, ZF, Levis, B, Sun, Y, He, C, Krishnan, A, Wu, Y, Bhandari, PM, Neupane, D, Brehaut, E, Benedetti, A, Thombs, BD, and Depression Screening Data (DEPRESSD) PHQ Group

Subjects
Adult, Male, Psychiatric Status Rating Scales, Depressive Disorder, Major, Age Factors, 1103 Clinical Sciences, 1117 Public Health and Health Services, Middle Aged, Patient Health Questionnaire, Reference Standards, Sex Factors, ROC Curve, General & Internal Medicine, Humans, Female
Abstract

Objective: To update a previous individual participant data meta-analysis and determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9), the most commonly used depression screening tool in general practice, for detecting major depression overall and by study or participant subgroups.\ud \ud \ud \ud Design: Systematic review and individual participant data meta-analysis.\ud \ud \ud \ud Data sources: Medline, Medline In-Process, and Other Non-Indexed Citations via Ovid, PsycINFO, Web of Science searched through 9 May 2018.\ud \ud \ud \ud Review methods: Eligible studies administered the PHQ-9 and classified current major depression status using a validated semistructured diagnostic interview (designed for clinician administration), fully structured interview (designed for lay administration), or the Mini International Neuropsychiatric Interview (MINI; a brief interview designed for lay administration). A bivariate random effects meta-analytic model was used to obtain point and interval estimates of pooled PHQ-9 sensitivity and specificity at cut-off values 5-15, separately, among studies that used semistructured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual), fully structured interviews (eg, Composite International Diagnostic Interview), and the MINI. Meta-regression was used to investigate whether PHQ-9 accuracy correlated with reference standard categories and participant characteristics.\ud \ud \ud \ud Results: Data from 44 503 total participants (27 146 additional from the update) were obtained from 100 of 127 eligible studies (42 additional studies; 79% eligible studies; 86% eligible participants). Among studies with a semistructured interview reference standard, pooled PHQ-9 sensitivity and specificity (95% confidence interval) at the standard cut-off value of ≥10, which maximised combined sensitivity and specificity, were 0.85 (0.79 to 0.89) and 0.85 (0.82 to 0.87), respectively. Specificity was similar across reference standards, but sensitivity in studies with semistructured interviews was 7-24% (median 21%) higher than with fully structured reference standards and 2-14% (median 11%) higher than with the MINI across cut-off values. Across reference standards and cut-off values, specificity was 0-10% (median 3%) higher for men and 0-12 (median 5%) higher for people aged 60 or older.\ud \ud \ud \ud Conclusions: Researchers and clinicians could use results to determine outcomes, such as total number of positive screens and false positive screens, at different PHQ-9 cut-off values for different clinical settings using the knowledge translation tool at www.depressionscreening100.com/phq.\ud \ud \ud \ud Study registration: PROSPERO CRD42014010673.

Published
2021

15. Selective cutoff reporting in studies of the accuracy of the Patient Health Questionnaire‐9 and Edinburgh Postnatal Depression Scale: Comparison of results based on published cutoffs versus all cutoffs using individual participant data meta‐analysis

Author

Neupane, D., Levis, B., Bhandari, P.M., Thombs, B.D., Benedetti, A., Sun, Y., He, C., Wu, Y., Krishnan, A., Negeri, Z., Imran, M., Rice, D.B., Riehm, K.E., Saadat, N., Azar, M., Sanchez, T.A., Chiovitti, M.J., Levis, A.W., Boruff, J.T., Cuijpers, P., Gilbody, S., Ioannidis, J.P.A., Kloda, L.A., Patten, S.B., Shrier, I., Ziegelstein, R.C., Comeau, L., Mitchell, N.D., Tonelli, M., Vigod, S.N., Akena, D.H., Alvarado, R., Arroll, B., Bakare, M.O., Baradaran, H.R., Beck, C.T., Bombardier, C.H., Bunevicius, A., Carter, G., Chagas, M.H., Chaudron, L.H., Cholera, R., Clover, K., Conwell, Y., Castro e Couto, T., de Man-van Ginkel, J.M., Delgadillo, J., Fann, J.R., Favez, N., Fung, D., Garcia-Esteve, L., Gelaye, B., Goodyear-Smith, F., Hyphantis, T., Inagaki, M., Ismail, K., Jetté, N., Khalifa, D.S., Khamseh, M.E., Kohlhoff, J., Kozinszky, Z., Kusminskas, L., Liu, S.-I., Lotrakul, M., Loureiro, S.R., Löwe, B., Sidik, S.M., Nakić Radoš, S., Osório, F.L., Pawlby, S.J., Pence, B.W., Rochat, T.J., Rooney, A.G., Sharp, D.J., Stafford, L., Su, K.-P., Sung, S.C., Tadinac, M., Darius Tandon, S., Thiagayson, P., Töreki, A., Torres-Giménez, A., Turner, A., van der Feltz-Cornelis, C.M., Vega Dienstmaier, Johann Martín, Vöhringer, P.A., White, J., Whooley, M.A., Winkley, K., Yamada, M., DEPRESsion Screening Data (DEPRESSD) Collaboration, Clinical Psychology, World Health Organization (WHO) Collaborating Center, APH - Global Health, and APH - Mental Health

Subjects
Astrophysics::High Energy Astrophysical Phenomena, Bivariate analysis, Patient Health Questionnaire, Sensitivity and Specificity, 03 medical and health sciences, 0302 clinical medicine, male, diagnostic test accuracy, individual participant data meta‐analysis, meta‐analysis, publication bias, selective cutoff reporting, Bias, Statistics, Humans, Cutoff, Medicine, controlled study, Edinburgh Postnatal Depression Scale, diagnostic test accuracy study, human, Psychiatric Status Rating Scales, Depressive Disorder, Major, business.industry, adult, Individual participant data, article, Original Articles, Publication bias, Random effects model, individual participant data meta-analysis, 030227 psychiatry, meta-analysis, Psychiatry and Mental health, female, Meta-analysis, diagnostic accuracy, Original Article, business, 030217 neurology & neurosurgery, meta analysis, Patient Health Questionnaire 9
Abstract

Objectives\ud \ud Selectively reported results from only well-performing cutoffs in diagnostic accuracy studies may bias estimates in meta-analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire-9 (PHQ-9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10–13) and compared accuracy estimates based on published cutoffs versus all cutoffs.\ud \ud \ud \ud Methods\ud \ud We conducted bivariate random effects meta-analyses using individual participant data to compare accuracy from published versus all cutoffs.\ud \ud \ud \ud Results\ud \ud For the PHQ-9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: −0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ-9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10.\ud \ud \ud \ud Conclusion\ud \ud Selective cutoff reporting was more pronounced for the PHQ-9 than EPDS.

Published
2021

19. Active commuting and leisure-time physical activity among adults in western Nepal: A cross-sectional study

Author

Paudel, S, Subedi, Narayan, McLachlan, CS, Smith, BJ, Kallestrup, P, Neupane, D, Paudel, S, Subedi, Narayan, McLachlan, CS, Smith, BJ, Kallestrup, P, and Neupane, D

Abstract

ObjectiveTo determine the prevalence and sociodemographic factors associated with active commuting and leisure-time physical activity (LTPA) among adults in western Nepal.DesignCross-sectional study.SettingAdults from semiurban areas in western Nepal.Participants2815 adults aged 25–65 years who participated in the ‘Community-Based Management of Hypertension in Nepal (COBIN)’ Study. Multiple logistic regression analysis was used to identify the sociodemographic factors associated with active commuting and LTPA.OutcomeSelf-reported participation in active commuting and LTPA.ResultsMost study participants (96%) commuted actively (walked or cycled) from one place to another. Our results showed that only a small proportion (3.7%) of participants engaged in moderate or vigorous LTPA. Compared with those in paid employment, the odds of commuting actively were higher among people working in agriculture or as labourers (OR: 4.57, 95% CI: 2.46 to 8.48), those retired/unemployed (OR: 2.98, 95% CI: 1.42 to 6.25) and those in unpaid employment (OR: 1.85, 95% CI: 1.06 to 3.22). Adults who were overweight or had obesity were less likely to commute actively. Compared with adults aged 25–34 years, older adults were less likely (OR: 0.35, 95% CI: 0.17 to 0.72) to engage in LTPA. Women were 0.46 times less likely to engage in LTPA compared with men.ConclusionMost adults engaged in active commuting for work or travel. Less than 5% participated in any form of moderate or vigorous LTPA. Longitudinal studies incorporating objective assessment of physical activity and a range

Published
2021

20. Selective cutoff reporting in studies of the accuracy of the Patient Health Questionnaire-9 and Edinburgh Postnatal Depression Scale: Comparison of results based on published cutoffs versus all cutoffs using individual participant data meta-analysis

Author

Neupane, D, Levis, B, Bhandari, PM, Thombs, BD, Benedetti, A, Sun, Y, He, C, Wu, Y, Krishnan, A, Negeri, Z, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Sanchez, TA, Chiovitti, MJ, Levis, AW, Boruff, JT, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Comeau, L, Mitchell, ND, Tonelli, M, Vigod, SN, Akena, DH, Alvarado, R, Arroll, B, Bakare, MO, Baradaran, HR, Beck, CT, Bombardier, CH, Bunevicius, A, Carter, G, Chagas, MH, Chaudron, LH, Cholera, R, Clover, K, Conwell, Y, Castro e Couto, T, de Man-van Ginkel, JM, Delgadillo, J, Fann, JR, Favez, N, Fung, D, Garcia-Esteve, L, Gelaye, B, Goodyear-Smith, F, Hyphantis, T, Inagaki, M, Ismail, K, Jetté, N, Khalifa, DS, Khamseh, ME, Kohlhoff, J, Kozinszky, Z, Kusminskas, L, Liu, SI, Lotrakul, M, Loureiro, SR, Löwe, B, Sidik, SM, Nakić Radoš, S, Osório, FL, Pawlby, SJ, Pence, BW, Rochat, TJ, Rooney, AG, Sharp, DJ, Stafford, L, Su, KP, Sung, SC, Tadinac, M, Darius Tandon, S, Thiagayson, P, Töreki, A, Torres-Giménez, A, Turner, Alyna, van der Feltz-Cornelis, CM, Vega-Dienstmaier, JM, Vöhringer, PA, White, J, Whooley, MA, Winkley, K, Yamada, M, Neupane, D, Levis, B, Bhandari, PM, Thombs, BD, Benedetti, A, Sun, Y, He, C, Wu, Y, Krishnan, A, Negeri, Z, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Sanchez, TA, Chiovitti, MJ, Levis, AW, Boruff, JT, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Comeau, L, Mitchell, ND, Tonelli, M, Vigod, SN, Akena, DH, Alvarado, R, Arroll, B, Bakare, MO, Baradaran, HR, Beck, CT, Bombardier, CH, Bunevicius, A, Carter, G, Chagas, MH, Chaudron, LH, Cholera, R, Clover, K, Conwell, Y, Castro e Couto, T, de Man-van Ginkel, JM, Delgadillo, J, Fann, JR, Favez, N, Fung, D, Garcia-Esteve, L, Gelaye, B, Goodyear-Smith, F, Hyphantis, T, Inagaki, M, Ismail, K, Jetté, N, Khalifa, DS, Khamseh, ME, Kohlhoff, J, Kozinszky, Z, Kusminskas, L, Liu, SI, Lotrakul, M, Loureiro, SR, Löwe, B, Sidik, SM, Nakić Radoš, S, Osório, FL, Pawlby, SJ, Pence, BW, Rochat, TJ, Rooney, AG, Sharp, DJ, Stafford, L, Su, KP, Sung, SC, Tadinac, M, Darius Tandon, S, Thiagayson, P, Töreki, A, Torres-Giménez, A, Turner, Alyna, van der Feltz-Cornelis, CM, Vega-Dienstmaier, JM, Vöhringer, PA, White, J, Whooley, MA, Winkley, K, and Yamada, M

Abstract

Objectives: Selectively reported results from only well-performing cutoffs in diagnostic accuracy studies may bias estimates in meta-analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire-9 (PHQ-9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10–13) and compared accuracy estimates based on published cutoffs versus all cutoffs. Methods: We conducted bivariate random effects meta-analyses using individual participant data to compare accuracy from published versus all cutoffs. Results: For the PHQ-9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: −0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ-9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10. Conclusion: Selective cutoff reporting was more pronounced for the PHQ-9 than EPDS.

Published
2021

21. Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data

Author

Bhandari, PM, Levis, B, Neupane, D, Patten, SB, Shrier, I, Thombs, BD, Benedetti, A, Bhandari, PM, Levis, B, Neupane, D, Patten, SB, Shrier, I, Thombs, BD, and Benedetti, A

Abstract

OBJECTIVE: To evaluate, across multiple sample sizes, the degree that data-driven methods result in (1) optimal cutoffs different from population optimal cutoff and (2) bias in accuracy estimates. STUDY DESIGN AND SETTING: A total of 1,000 samples of sample size 100, 200, 500 and 1,000 each were randomly drawn to simulate studies of different sample sizes from a database (n = 13,255) synthesized to assess Edinburgh Postnatal Depression Scale (EPDS) screening accuracy. Optimal cutoffs were selected by maximizing Youden's J (sensitivity+specificity-1). Optimal cutoffs and accuracy estimates in simulated samples were compared to population values. RESULTS: Optimal cutoffs in simulated samples ranged from ≥ 5 to ≥ 17 for n = 100, ≥ 6 to ≥ 16 for n = 200, ≥ 6 to ≥ 14 for n = 500, and ≥ 8 to ≥ 13 for n = 1,000. Percentage of simulated samples identifying the population optimal cutoff (≥ 11) was 30% for n = 100, 35% for n = 200, 53% for n = 500, and 71% for n = 1,000. Mean overestimation of sensitivity and underestimation of specificity were 6.5 percentage point (pp) and -1.3 pp for n = 100, 4.2 pp and -1.1 pp for n = 200, 1.8 pp and -1.0 pp for n = 500, and 1.4 pp and -1.0 pp for n = 1,000. CONCLUSIONS: Small accuracy studies may identify inaccurate optimal cutoff and overstate accuracy estimates with data-driven methods.

Published
2021

22. Effectiveness of a Female Community Health Volunteer-Delivered Intervention in Reducing Blood Glucose Among Adults With Type 2 Diabetes An Open-Label, Cluster Randomized Clinical Trial

Author

Gyawali, B, Sharma, R, Mishra, SR, Neupane, D, Vaidya, A, Sandbaek, A, Kallestrup, P, Gyawali, B, Sharma, R, Mishra, SR, Neupane, D, Vaidya, A, Sandbaek, A, and Kallestrup, P

Abstract

IMPORTANCE: Female community health volunteers (FCHVs) are frontline community health workers who have been a valuable resource in improving public health outcomes in Nepal, but their value is understudied in diabetes care. OBJECTIVE: To assess whether an FCHV-delivered intervention is associated with reduced blood glucose levels among adults with type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS: This community-based, open-label, 2-group, cluster randomized clinical trial with a 12-month delayed control group design was conducted in 14 clusters of a semiurban setting in Western Nepal. A total of 244 adults with type 2 diabetes were recruited between November 2016 and April 2017. The follow-up assessment was conducted at 12 months after enrollment. Data analysis was performed from January to February 2019. INTERVENTIONS: Seven clusters were randomized to the FCHV-delivered intervention in which 20 FCHVs provided home visits 3 times a year (once every 4 months) for health promotion counseling and blood glucose monitoring. If participants had blood glucose levels of 126 mg/dL or higher, the FCHVs referred them to the nearest health facility, and if participants were taking antihyperglycemic medication, they were followed up by the FCHVs for adherence to their medication. Seven clusters were randomized to usual care (control group). MAIN OUTCOMES AND MEASURES: The primary outcome was the change in mean fasting blood glucose from baseline to 12-month follow-up. Secondary outcomes included changes in mean systolic blood pressure, mean diastolic blood pressure, mean body mass index, percentage change in the proportion of low physical activity, harmful alcohol consumption, current smoking, low fruit and vegetable intake, and antihyperglycemic medication status. RESULTS: Of 244 participants, 120 women (56.6%) and 92 men (43.4%) completed the trial. At baseline, the mean (SD) age was 51.71 (8.77) years; 127 participants were in the intervention group, and 117 participants w

Published
2021

23. Salt intake and salt-reduction strategies in South Asia: From evidence to action

Author

Ghimire, K, Mishra, SR, Satheesh, G, Neupane, D, Sharma, A, Panda, R, Kallestrup, P, Mclachlan, CS, Ghimire, K, Mishra, SR, Satheesh, G, Neupane, D, Sharma, A, Panda, R, Kallestrup, P, and Mclachlan, CS

Abstract

The World Health Organization recommends salt reduction as a cost-effective intervention to prevent noncommunicable diseases. Salt-reduction interventions are best tailored to the local context, taking into consideration the varying baseline salt-intake levels, population's knowledge, attitude, and behaviors. Fundamental to reduction programs is the source of dietary salt-intake. In South Asian countries, there is a paucity of such baseline evidence around factors that contribute to community salt intake. Upon reviewing the electronic literature databases and government websites through March 31, 2021, we summarized dietary salt intake levels and aimed to identify major sources of sodium in the diet. Information on the current salt reduction strategies in eight South Asian countries were summarized, namely Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. One hundred twelve publications (out of identified 640) met our inclusion-exclusion criteria for full text review. Twenty-one studies were included in the review. Quality of the included studies was assessed using the US National Heart, Lung, and Blood Institute assessment tool. The primary result revealed that mean salt intake of South Asian countries was approximately twice (10 g/day) compared to WHO recommended intake (< 5 g/day). The significant proportion of salt intake is derived from salt additions during cooking and/or discretionary use at table. In most South Asian countries, there is limited data on population sodium intake based on 24-h urinary methods and sources of dietary salt in diet. While salt reduction initiatives have been proposed in these countries, they are yet to be fully implemented and evaluated. Proven salt reduction strategies in high-income countries could possibly be replicated in South Asian countries; however, further community-health promotion studies are necessary to test the effectiveness and scalability of those strategies in the local context.

Published
2021

24. Health System Capacity and Access Barriers to Diagnosis and Treatment of CVD and Diabetes in Nepal

Author

Sharma, A, Kaplan, WA, Satheesh, G, Poudyal, IP, Gyawali, P, Neupane, D, Bhandari, PM, Malla, M, Sapkota, S, Mishra, SR, Sharma, A, Kaplan, WA, Satheesh, G, Poudyal, IP, Gyawali, P, Neupane, D, Bhandari, PM, Malla, M, Sapkota, S, and Mishra, SR

Abstract

BACKGROUND: Universal access to essential medicines and routine diagnostics is required to combat the growing burden of cardiovascular disease (CVD) and diabetes. Evaluating health systems and various access dimensions availability, affordability, accessibility, acceptability, and quality is crucial yet rarely performed, especially in low- and middle-income countries. OBJECTIVE: To evaluate health system capacity and barriers in accessing diagnostics and essential medicines for CVD and diabetes in Nepal. METHODS: We conducted a WHO/HAI nationally-representative survey in 45 health-facilities (public-sector: 11; private-sector: 34) in Nepal to collect availability and price data for 21 essential medicines for treating CVD and diabetes, during MayJuly 2017. Data for 13 routine diagnostics was obtained in 12 health facilities. Medicines were considered unaffordable if the lowest paid worker spends >1 days wage to purchase a monthly supply. To evaluate accessibility, we conducted facility exit interviews among 636 CVD patients. Accessibility (e.g., private-public health facility mix, travel to hospital/pharmacy) and acceptability (i.e. Nepals adoption of WHO Essential Medicine List, and patient medication adherence) were summarized using descriptive statistics, and we conducted a systematic review of relevant literature. We did not evaluate medicine quality. RESULTS: We found that mean availability of generic medicines is low (<50%) in both public and private sectors, and less than one-third medicines met WHOs availability target (80%). Mean (SD) availability of diagnostics was 73.1% (26.8%). Essential medicines appear locally unaffordable. On average, the lowest-paid worker would spend 1.03 (public-sector) and 1.26 (private-sector) days wages to purchase a monthly supply. For a person undergoing CVD secondary preventive-interventions in the private sector, the associated expenditure would be 7.511.2% of monthly household income. Exit-interviews suggest that a long/expe

Published
2021

25. Effects of a health worker-led 3-month yoga intervention on blood pressure of hypertensive patients: a randomised controlled multicentre trial in the primary care setting

Author

Dhungana, RR, Pedisic, Z, Joshi, S, Khanal, MK, Kalauni, OP, Shakya, A, Bhurtel, V, Panthi, S, Kumar, KCR, Ghimire, B, Pandey, AR, Bista, B, Khatiwoda, SR, McLachlan, CS, Neupane, D, de Courten, M, Dhungana, RR, Pedisic, Z, Joshi, S, Khanal, MK, Kalauni, OP, Shakya, A, Bhurtel, V, Panthi, S, Kumar, KCR, Ghimire, B, Pandey, AR, Bista, B, Khatiwoda, SR, McLachlan, CS, Neupane, D, and de Courten, M

Abstract

BACKGROUND: Hypertension control remains a major challenge globally. A recent systematic review suggested that yoga has beneficial effects on reducing blood pressure. However, the role of yoga in hypertension management in primary health care has received little attention, and no studies have evaluated the impact of a yoga program fully delivered by health care staff on hypertension. This study, therefore, assessed the effects of a health worker-led yoga intervention on blood pressure reduction among hypertensives patients in the primary care setting. METHODS: This was a multicentric, two-arm, randomised trial conducted among hypertensive patients in seven Ayurveda Health Centres in Nepal between March 2017 and June 2018. One hundred and twenty-one participants who were on or without medications were randomised to intervention (n = 61) and wait-list control (n = 60) groups using stratified block randomisation. Participants in the intervention arm received an intervention consisting of an initial five-day structured yoga training at the centres and then a further home-based practice of yoga for five days a week for the following 90 days. Both intervention and control groups also participated in a 2-h health education session. The primary outcome of this trial was systolic blood pressure at 90-day follow-up. Data were analysed on an intention-to-treat basis using linear mixed-effects regression models. RESULTS: We included all 121 study participants (intervention/control = 61/60) in the primary analysis (52.1% males; mean ± SD age = 47.8 ± 10.8 years). The difference in systolic blood pressure between the intervention group and the control group was - 7.66 mmHg (95% CI: - 10.4, - 4.93). For diastolic blood pressure, the difference was - 3.86 mmHg (95% CI: - 6.65, - 1.06). No adverse events were reported by the participants. CONCLUSIONS: A yoga program for hypertensive patients consisting of a five-day training in health centres and 90 days of practice at home is effec

Published
2021

28. May Measurement Month 2017: an analysis of blood pressure screening results worldwide

Author

Beaney, T, Schutte, A, Tomaszewski, M, Ariti, C, Burrell, L, Castillo, R, Charchar, F, Damasceno, A, Kruger, R, Lackland, D, Nilsson, P, Prabhakaran, D, Ramirez, A, Schlaich, M, Wang, J, Weber, M, Poulter, N, Napiza-Granada, C, Sevilla, M, Atilano, A, Ona, D, More, A, Jose, A, Maheshwari, A, Kondal, D, Yu, W, Li, W, Xu, S, Yu, J, Zhang, H, Widyantoro, B, Turana, Y, Situmorang, T, Sofiatin, Y, Barack, R, Lin, H, Wang, T, Chen, W, Sirenko, Y, Evstigneeva, O, Negresku, E, Yousif, M, Medani, S, Beheiry, H, Ali, I, Zilberman, J, Marin, M, Rodriguez, P, Garcia-Vasquez, F, Kramoh, K, Ekoua, D, Lopez-Jaramillo, P, Otero, J, Sanchez, G, Narvaez, C, Accini, J, Hernandez-Hernandez, R, Octavio, J, Morr, I, Lopez-Rivera, J, Ojji, D, Arije, A, Babatunte, A, Wahab, K, REIS FERNANDES, M, Pereira, S, Valentim, M, Dzudie, A, Kingue, S, Djomou Ngongang, D, Ogola, E, Barasa, F, Gitura, B, Malik, F, Choudhury, S, Al Mamun, M, Minh, V, Viet, N, Cao Truong, S, Ferri, C, Parati, G, Torlasco, C, Borghi, C, Goma, F, Syatalimi, C, Zelveian, P, Barbosa, E, Sebba Barroso, W, Penaherrera, E, Jarrin, E, Yusufali, A, Bazargani, N, Tsinamdzgvrishvili, B, Trapaidze, D, Neupane, D, Mishra, S, Jozwiak, J, Malyszko, J, Konradi, A, Chazova, I, Ishaq, M, Memon, F, Heagerty, A, Keitley, J, Brady, A, Cockcroft, J, Mcdonnell, B, Lanas, F, Chia, Y, Ndhlovu, H, Kiss, I, Ruilope, L, Ellenga Mbolla, B, Milhailidou, A, Woodiwiss, A, Perl, S, Dolan, E, Azevedo, V, Garre, L, Boggia, J, Lee, V, Kowlessur, S, Miglinas, M, Sukackiene, D, Wainford, R, Habonimana, D, Masupe, T, Ortellado, J, Wuerzner, G, Alcocer, L, Burazeri, G, Sanchez Delgado, E, Lovic, D, Mondo, C, Mostafa, A, Nadar, S, Valdez Tiburcio, O, Leiba, A, Dorobantu, M, De Backer, T, Chifamba, J, Stergiou, G, Nwokocha, C, Sokolovic, S, Toure, A, Connell, K, Khan, N, Burger, D, De Carvalho Rodrigues, M, Kramer, B, Schmieder, R, Unger, T, Wyss, F, Yameogo, N, Beistline, H, Kenerson, J, Alfonso, B, Olsen, M, Soares, M, Beaney, Thomas, Schutte, Aletta E, Tomaszewski, Maciej, Ariti, Cono, Burrell, Louise M, Castillo, Rafael R, Charchar, Fadi J, Damasceno, Albertino, Kruger, Ruan, Lackland, Daniel T, Nilsson, Peter M, Prabhakaran, Dorairaj, Ramirez, Agustin J, Schlaich, Markus P, Wang, Jiguang, Weber, Michael A, Poulter, Neil R, Napiza-Granada, C., Sevilla, Ma. RC, Atilano, A. A., Ona, D. I. D., More, A., Jose, A. P., Maheshwari, A., Kondal, D., Yu, W., Li, W., Xu, S., Yu, J., Zhang, H., Widyantoro, B., Turana, Y., Situmorang, T. D., Sofiatin, Y., Barack, R., Lin, H. -J., Wang, T. -D., Chen, W. -J., Sirenko, Y., Evstigneeva, O., Negresku, E., Yousif, M. E., Medani, S. A., Beheiry, H. M., Ali, I. A., Zilberman, J. M., Marin, M. J., Rodriguez, P. D., Garcia-Vasquez, F., Kramoh, K. E., Ekoua, D., Lopez-Jaramillo, P., Otero, J., Sanchez, G., Narvaez, C., Accini, J. L., Hernandez-Hernandez, R., Octavio, J. A., Morr, I., Lopez-Rivera, J., Ojji, D., Arije, A., Babatunte, A., Wahab, K. W., REIS FERNANDES, MARCOS ANTONIO, Pereira, S. V., Valentim, M., Dzudie, A., Kingue, S., Djomou Ngongang, D. A., Ogola, E. N., Barasa, F. A., Gitura, B., Malik, F-T-N, Choudhury, S. R., Al Mamun, M. A., Minh, V. H., Viet, N. L., Cao Truong, S., Ferri, C., Parati, G., Torlasco, C., Borghi, C., Goma, F. M., Syatalimi, C., Zelveian, P. H., Barbosa, E., Sebba Barroso, W., Penaherrera, E., Jarrin, E., Yusufali, A., Bazargani, N., Tsinamdzgvrishvili, B., Trapaidze, D., Neupane, D., Mishra, S. R., Jozwiak, J., Malyszko, J., Konradi, A., Chazova, I., Ishaq, M., Memon, F., Heagerty, A. M., Keitley, J., Brady, A. J. B., Cockcroft, J. R., McDonnell, B. J., Lanas, F., Chia, Y. -C., Ndhlovu, H., Kiss, I., Ruilope, L. M., Ellenga Mbolla, B. F., Milhailidou, A. S., Woodiwiss, A. J., Perl, S., Dolan, E., Azevedo, V., Garre, L., Boggia, J. G., Lee, V. W. Y., Kowlessur, S., Miglinas, M., Sukackiene, D., Wainford, R. D., Habonimana, D., Masupe, T., Ortellado, J., Wuerzner, G., Alcocer, L., Burazeri, G., Sanchez Delgado, E., Lovic, D., Mondo, C. K., Mostafa, A., Nadar, S. K., Valdez Tiburcio, O., Leiba, A., Dorobantu, M., De Backer, T., Chifamba, J., Stergiou, G., Nwokocha, C. R., Sokolovic, S., Toure, A. I., Connell, K. L., Khan, N. A., Burger, D., De Carvalho Rodrigues, M., Kramer, B. K., Schmieder, R. E., Unger, T., Wyss, F. S., Yameogo, N. V., Beistline, H., Kenerson, J. G., Alfonso, B., Olsen, M. H., Soares, M., Beaney, T, Schutte, A, Tomaszewski, M, Ariti, C, Burrell, L, Castillo, R, Charchar, F, Damasceno, A, Kruger, R, Lackland, D, Nilsson, P, Prabhakaran, D, Ramirez, A, Schlaich, M, Wang, J, Weber, M, Poulter, N, Napiza-Granada, C, Sevilla, M, Atilano, A, Ona, D, More, A, Jose, A, Maheshwari, A, Kondal, D, Yu, W, Li, W, Xu, S, Yu, J, Zhang, H, Widyantoro, B, Turana, Y, Situmorang, T, Sofiatin, Y, Barack, R, Lin, H, Wang, T, Chen, W, Sirenko, Y, Evstigneeva, O, Negresku, E, Yousif, M, Medani, S, Beheiry, H, Ali, I, Zilberman, J, Marin, M, Rodriguez, P, Garcia-Vasquez, F, Kramoh, K, Ekoua, D, Lopez-Jaramillo, P, Otero, J, Sanchez, G, Narvaez, C, Accini, J, Hernandez-Hernandez, R, Octavio, J, Morr, I, Lopez-Rivera, J, Ojji, D, Arije, A, Babatunte, A, Wahab, K, REIS FERNANDES, M, Pereira, S, Valentim, M, Dzudie, A, Kingue, S, Djomou Ngongang, D, Ogola, E, Barasa, F, Gitura, B, Malik, F, Choudhury, S, Al Mamun, M, Minh, V, Viet, N, Cao Truong, S, Ferri, C, Parati, G, Torlasco, C, Borghi, C, Goma, F, Syatalimi, C, Zelveian, P, Barbosa, E, Sebba Barroso, W, Penaherrera, E, Jarrin, E, Yusufali, A, Bazargani, N, Tsinamdzgvrishvili, B, Trapaidze, D, Neupane, D, Mishra, S, Jozwiak, J, Malyszko, J, Konradi, A, Chazova, I, Ishaq, M, Memon, F, Heagerty, A, Keitley, J, Brady, A, Cockcroft, J, Mcdonnell, B, Lanas, F, Chia, Y, Ndhlovu, H, Kiss, I, Ruilope, L, Ellenga Mbolla, B, Milhailidou, A, Woodiwiss, A, Perl, S, Dolan, E, Azevedo, V, Garre, L, Boggia, J, Lee, V, Kowlessur, S, Miglinas, M, Sukackiene, D, Wainford, R, Habonimana, D, Masupe, T, Ortellado, J, Wuerzner, G, Alcocer, L, Burazeri, G, Sanchez Delgado, E, Lovic, D, Mondo, C, Mostafa, A, Nadar, S, Valdez Tiburcio, O, Leiba, A, Dorobantu, M, De Backer, T, Chifamba, J, Stergiou, G, Nwokocha, C, Sokolovic, S, Toure, A, Connell, K, Khan, N, Burger, D, De Carvalho Rodrigues, M, Kramer, B, Schmieder, R, Unger, T, Wyss, F, Yameogo, N, Beistline, H, Kenerson, J, Alfonso, B, Olsen, M, Soares, M, Beaney, Thomas, Schutte, Aletta E, Tomaszewski, Maciej, Ariti, Cono, Burrell, Louise M, Castillo, Rafael R, Charchar, Fadi J, Damasceno, Albertino, Kruger, Ruan, Lackland, Daniel T, Nilsson, Peter M, Prabhakaran, Dorairaj, Ramirez, Agustin J, Schlaich, Markus P, Wang, Jiguang, Weber, Michael A, Poulter, Neil R, Napiza-Granada, C., Sevilla, Ma. RC, Atilano, A. A., Ona, D. I. D., More, A., Jose, A. P., Maheshwari, A., Kondal, D., Yu, W., Li, W., Xu, S., Yu, J., Zhang, H., Widyantoro, B., Turana, Y., Situmorang, T. D., Sofiatin, Y., Barack, R., Lin, H. -J., Wang, T. -D., Chen, W. -J., Sirenko, Y., Evstigneeva, O., Negresku, E., Yousif, M. E., Medani, S. A., Beheiry, H. M., Ali, I. A., Zilberman, J. M., Marin, M. J., Rodriguez, P. D., Garcia-Vasquez, F., Kramoh, K. E., Ekoua, D., Lopez-Jaramillo, P., Otero, J., Sanchez, G., Narvaez, C., Accini, J. L., Hernandez-Hernandez, R., Octavio, J. A., Morr, I., Lopez-Rivera, J., Ojji, D., Arije, A., Babatunte, A., Wahab, K. W., REIS FERNANDES, MARCOS ANTONIO, Pereira, S. V., Valentim, M., Dzudie, A., Kingue, S., Djomou Ngongang, D. A., Ogola, E. N., Barasa, F. A., Gitura, B., Malik, F-T-N, Choudhury, S. R., Al Mamun, M. A., Minh, V. H., Viet, N. L., Cao Truong, S., Ferri, C., Parati, G., Torlasco, C., Borghi, C., Goma, F. M., Syatalimi, C., Zelveian, P. H., Barbosa, E., Sebba Barroso, W., Penaherrera, E., Jarrin, E., Yusufali, A., Bazargani, N., Tsinamdzgvrishvili, B., Trapaidze, D., Neupane, D., Mishra, S. R., Jozwiak, J., Malyszko, J., Konradi, A., Chazova, I., Ishaq, M., Memon, F., Heagerty, A. M., Keitley, J., Brady, A. J. B., Cockcroft, J. R., McDonnell, B. J., Lanas, F., Chia, Y. -C., Ndhlovu, H., Kiss, I., Ruilope, L. M., Ellenga Mbolla, B. F., Milhailidou, A. S., Woodiwiss, A. J., Perl, S., Dolan, E., Azevedo, V., Garre, L., Boggia, J. G., Lee, V. W. Y., Kowlessur, S., Miglinas, M., Sukackiene, D., Wainford, R. D., Habonimana, D., Masupe, T., Ortellado, J., Wuerzner, G., Alcocer, L., Burazeri, G., Sanchez Delgado, E., Lovic, D., Mondo, C. K., Mostafa, A., Nadar, S. K., Valdez Tiburcio, O., Leiba, A., Dorobantu, M., De Backer, T., Chifamba, J., Stergiou, G., Nwokocha, C. R., Sokolovic, S., Toure, A. I., Connell, K. L., Khan, N. A., Burger, D., De Carvalho Rodrigues, M., Kramer, B. K., Schmieder, R. E., Unger, T., Wyss, F. S., Yameogo, N. V., Beistline, H., Kenerson, J. G., Alfonso, B., Olsen, M. H., and Soares, M.

Abstract

Background: Increased blood pressure is the biggest contributor to the global burden of disease and mortality. Data suggest that less than half of the population with hypertension is aware of it. May Measurement Month was initiated to raise awareness of the importance of blood pressure and as a pragmatic interim solution to the shortfall in screening programmes. Methods: This cross-sectional survey included volunteer adults (≥18 years) who ideally had not had their blood pressures measured in the past year. Each participant had their blood pressure measured three times and received a a questionnaire about demographic, lifestyle, and environmental factors. The primary objective was to raise awareness of blood pressure, measured by number of countries involved, number of people screened, and number of people who have untreated or inadequately treated hypertension (defined as systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg, or both, or on the basis of receiving antihypertensive medication). Multiple imputation was used to estimate the mean of the second and third blood pressure readings if these were not recorded. Measures of association were analysed using linear mixed models. Findings: Data were collected from 1 201 570 individuals in 80 countries. After imputation, of the 1 128 635 individuals for whom a mean of the second and third readings was available, 393 924 (34·9%) individuals had hypertension. 153 905 (17·3%) of 888 616 individuals who were not receiving antihypertensive treatment were hypertensive, and 105 456 (46·3%) of the 227 721 individuals receiving treatment did not have controlled blood pressure. Significant differences in adjusted blood pressures and hypertension prevalence were apparent between regions. Adjusted blood pressure was higher in association with antihypertensive medication, diabetes, cerebrovascular disease, smoking, and alcohol consumption. Blood pressure was higher when measured on the right arm than on the le

Published
2018

29. Protocol for a partially nested randomised controlled trial to evaluate the effectiveness of the scleroderma patient-centered intervention network COVID-19 home-isolation activities together (SPIN-CHAT) program to reduce anxiety among at-risk scleroderma patients

Author

Thombs, B.D., Kwakkenbos, L., Carrier, M.E., Bourgeault, A., Tao, L.D., Harb, S., Gagarine, M., Rice, D., Bustamante, L., Ellis, K., Duchek, D., Wu, Y., Bhandari, P.M., Neupane, D., Carboni-Jimenez, A., Henry, R.S., Krishnan, A., Sun, Y., Levis, B., He, C., Turner, K.A., Benedetti, A., Culos-Reed, N., El-Baalbaki, G., Hebblethwaite, S., Bartlett, S.J., Dyas, L., Patten, S., Varga, J., Fortune, C., Gietzen, A., Guillot, G., Lewis, N., Nielsen, K., Richard, M., Sauve, M., Welling, J., Baron, M., Furst, D.E., Gottesman, K., Malcarne, V., Mayes, M.D., Mouthon, L., Nielson, W.R., Riggs, R., Wigley, F., Assassi, S., Boutron, I., Ells, C., Ende, C. van den, Fligelstone, K., Frech, T., Godard, D., Harel, D., Hinchcliff, M., Hudson, M., Johnson, S.R., Larche, M., Leite, C., Nguyen, C., Pope, J., Portales, A., Rannou, F., Reyna, T.S.R., Schouffoer, A.A., Suarez-Almazor, M.E., Agard, C., Albert, A., Andre, M., Arsenault, G., Benzidia, I., Bernstein, E.J., Berthier, S., Bissonnette, L., Boire, G., Bruns, A., Carreira, P., Casadevall, M., Chaigne, B., Chung, L., Cohen, P., Correia, C., Dagenais, P., Denton, C., Domsic, R., Dubois, S., Dunne, J.V., Dunogue, B., Fare, R., Farge-Bancel, D., Fortin, P.R., Gill, A., Gordon, J., Granel-Rey, B., Gyger, G., Hachulla, E., Hatron, P.Y., Herrick, A.L., Hij, A., Hoa, S., Ikic, A., Jones, N., Fernandes, A.J.D., Kafaja, S., Khalidi, N., Lambert, M., Launay, D., Liang, P., Maillard, H., Maltez, N., Manning, J., Marie, I., Martin, M., Martin, T., Masetto, A., Maurier, F., Mekinian, A., Melchor, S., Nikpour, M., Olagne, L., Poindron, V., Proudman, S., Regent, A., Riviere, S., Robinson, D., Rodriguez, E., Roux, S., Smets, P., Smith, D., Sobanski, V., Spiera, R., Steen, V., Stevens, W., Sutton, E., Terrier, B., Thorne, C., Wilcox, P., Ayala, M.C., Ostbo, N., Scleroderma Patient-ctr Interventi, and SPIN Investigators

Subjects
Coronavirus, COVID-19, Systemic sclerosis, Mental health, Anxiety, RCT, Trial, Scleroderma
Abstract

Objective: Contagious disease outbreaks and related restrictions can lead to negative psychological outcomes, particularly in vulnerable populations at risk due to pre-existing medical conditions. No randomised controlled trials (RCTs) have tested interventions to reduce mental health consequences of contagious disease outbreaks. The primary objective of the Scleroderma Patient-centered Intervention Network COVID-19 Home-isolation Activities Together (SPIN-CHAT) Trial is to evaluate the effect of a videoconference-based program on symptoms of anxiety. Secondary objectives include evaluating effects on symptoms of depression, stress, loneliness, boredom, physical activity, and social interaction.Methods: The SPIN-CHAT Trial is a pragmatic RCT that will be conducted using the SPIN-COVID-19 Cohort, a sub-cohort of the SPIN Cohort. Eligible participants will be SPIN-COVID-19 Cohort participants without a positive COVID-19 test, with at least mild anxiety (PROMIS Anxiety 4a v1.0 T-score >= 55), not working from home, and not receiving current counselling or psychotherapy. We will randomly assign 162 participants to intervention groups of 7 to 10 participants each or waitlist control. We will use a partially nested RCT design to reflect dependence between individuals in training groups but not in the waitlist control. The SPIN-CHAT Program includes activity engagement, education on strategies to support mental health, and mutual participant support. Intervention participants will receive the 4-week (3 sessions per week) SPIN-CHAT Program via video-conference. The primary outcome is PROMIS Anxiety 4a score immediately post-intervention.Ethics and dissemination: The SPIN-CHAT Trial will test whether a brief videoconference-based intervention will improve mental health outcomes among at-risk individuals during contagious disease outbreak.

Published
2020

30. Accuracy of the PHQ-2 Alone and in Combination With the PHQ-9 for Screening to Detect Major Depression: Systematic Review and Meta-analysis

Author

Levis B, Sun Y, He C, Wu Y, Krishnan A, Bhandari PM, Neupane D, Imran M, Brehaut E, Negeri Z, Fischer FH, Benedetti A, Thombs BD, Depression Screening Data (DEPRESSD) PHQ Collaboration, Che L, Levis A, Riehm K, Saadat N, Azar M, Rice D, Boruff J, Kloda L, Cuijpers P, Gilbody S, Ioannidis J, McMillan D, Patten S, Shrier I, Ziegelstein R, Moore A, Akena D, Amtmann D, Arroll B, Ayalon L, Baradaran H, Beraldi A, Bernstein C, Bhana A, Bombardier C, Buji RI, Butterworth P, Carter G, Chagas M, Chan J, Chan LF, Chibanda D, Cholera R, Clover K, Conway A, Conwell Y, Daray F, de Man-van Ginkel J, Delgadillo J, Diez-Quevedo C, Fann J, Field S, Fisher J, Fung D, Garman E, Gelaye B, Gholizadeh L, Gibson L, Goodyear-Smith F, Green E, Greeno C, Hall B, Hampel P, Hantsoo L, Haroz E, Harter M, Hegerl U, Hides L, Hobfoll S, Honikman S, Hudson M, Hyphantis T, Inagaki M, Ismail K, Jeon HJ, Jetté N, Khamseh M, Kiely K, Kohler S, Kohrt B, Kwan Y, Lamers F, Asunción Lara M, Levin-Aspenson H, Lino V, Liu S-I, Lotrakul M, Loureiro S, Löwe B, Luitel N, Lund C, Marrie RA, Marsh L, Marx B, McGuire A, Mohd Sidik S, Munhoz T, Muramatsu K, Nakku J, Navarrete L, Osório F, Patel V, Pence B, Persoons P, Petersen I, Picardi A, Pugh S, Quinn T, Rancans E, Rathod S, Reuter K, Roch S, Rooney A, Rowe H, Santos I, Schram M, Shaaban J, Shinn E, Sidebottom A, Simning A, Spangenberg L, Stafford L, Sung S, Suzuki K, Swartz R, Tan PLL, Taylor-Rowan M, Tran T, Turner A, van der Feltz-Cornelis C, van Heyningen T, van Weert H, Wagner L, Li Wang J, White J, Winkley K, Wynter K, Yamada M, Zhi Zeng Q, and Zhang Y

Subjects
Adult, Male, Depressive Disorder, Major, Patient Health Questionnaire, behavioral disciplines and activities, Sensitivity and Specificity, humanities, Interviews as Topic, ROC Curve, General & Internal Medicine, mental disorders, Humans, Mass Screening, Female, 11 Medical and Health Sciences
Abstract

Importance:The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9. Objective:To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression. Data Sources:MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-May 2018). Study Selection:Eligible data sets compared PHQ-2 scores with major depression diagnoses from a validated diagnostic interview. Data Extraction and Synthesis:Individual participant data were synthesized with bivariate random-effects meta-analysis to estimate pooled sensitivity and specificity of the PHQ-2 alone among studies using semistructured, fully structured, or Mini International Neuropsychiatric Interview (MINI) diagnostic interviews separately and in combination with the PHQ-9 vs the PHQ-9 alone for studies that used semistructured interviews. The PHQ-2 score ranges from 0 to 6, and the PHQ-9 score ranges from 0 to 27. Results:Individual participant data were obtained from 100 of 136 eligible studies (44 318 participants; 4572 with major depression [10%]; mean [SD] age, 49 [17] years; 59% female). Among studies that used semistructured interviews, PHQ-2 sensitivity and specificity (95% CI) were 0.91 (0.88-0.94) and 0.67 (0.64-0.71) for cutoff scores of 2 or greater and 0.72 (0.67-0.77) and 0.85 (0.83-0.87) for cutoff scores of 3 or greater. Sensitivity was significantly greater for semistructured vs fully structured interviews. Specificity was not significantly different across the types of interviews. The area under the receiver operating characteristic curve was 0.88 (0.86-0.89) for semistructured interviews, 0.82 (0.81-0.84) for fully structured interviews, and 0.87 (0.85-0.88) for the MINI. There were no significant subgroup differences. For semistructured interviews, sensitivity for PHQ-2 scores of 2 or greater followed by PHQ-9 scores of 10 or greater (0.82 [0.76-0.86]) was not significantly different than PHQ-9 scores of 10 or greater alone (0.86 [0.80-0.90]); specificity for the combination was significantly but minimally higher (0.87 [0.84-0.89] vs 0.85 [0.82-0.87]). The area under the curve was 0.90 (0.89-0.91). The combination was estimated to reduce the number of participants needing to complete the full PHQ-9 by 57% (56%-58%). Conclusions and Relevance:In an individual participant data meta-analysis of studies that compared PHQ scores with major depression diagnoses, the combination of PHQ-2 (with cutoff ≥2) followed by PHQ-9 (with cutoff ≥10) had similar sensitivity but higher specificity compared with PHQ-9 cutoff scores of 10 or greater alone. Further research is needed to understand the clinical and research value of this combined approach to screening.

Published
2020

31. Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: A synthesis of three individual participant data meta-analyses

Author

Wu, Y. Levis, B. Ioannidis, J.P.A. Benedetti, A. Thombs, B.D. Sun, Y. He, C. Krishnan, A. Bhandari, P.M. Neupane, D. Negeri, Z. Imran, M. Rice, D.B. Riehm, K.E. Saadat, N. Azar, M. Levis, A.W. Sanchez, T.A. Chiovitti, M.J. Yan, X.W. Boruff, J. Kloda, L.A. Cuijpers, P. Gilbody, S. McMillan, D. Patten, S.B. Shrier, I. Ziegelstein, R.C. Comeau, L. Mitchell, N.D. Tonelli, M. Vigod, S.N. Henry, M. Ismail, Z. Loiselle, C.G. Akena, D.H. Al-Adawi, S. Alamri, S.H. Alvarado, R. Alvarado-Esquivel, C. Amtmann, D. Arroll, B. Ayalon, L. Bakare, M.O. Baradaran, H.R. Barnes, J. Bavle, A.D. Beck, C.T. Beraldi, A. Bernstein, C.N. Bhana, A. Bindt, C. Bombardier, C.H. Boyce, P.M. Büel-Drabe, N. Buji, R.I. Bunevicius, A. Butnoriene, J. Bunevicius, R. Butterworth, P. Carter, G. Chagas, M.H. Chan, J.C.N. Chan, L.F. Chaudron, L.H. Chen, C.-K. Cholera, R. Clover, K. Conroy, R.M. Conway, A. Conwell, Y. Correa, H. Castro E Couto, T. Cukor, D. Dabscheck, E. Daray, F.M. De Figueiredo, F.P. De Man-Van Ginkel, J.M. Diez-Quevedo, C. Douven, E. Downing, M.G. Eapen, V. Fann, J.R. Feinstein, A. Ferentinos, P.P. Fernandes, M. Field, S. Figueiredo, B. Fischer, F.H. Fisher, J.R.W. Flint, A.J. Fujimori, M. Fung, D.S.S. Gallagher, P. Gandy, M. Garcia-Esteve, L. Garman, E.C. Gelaye, B. Gholizadeh, L. Giardinelli, L. Gibson, L.J. Goodyear-Smith, F. Grassi, L. Green, E.P. Greeno, C.G. Hall, B.J. Hantsoo, L. Haroz, E.E. Harter, M. Hegerl, U. Helle, N. Hides, L. Hobfoll, S.E. Honikman, S. Howard, L.M. Hudson, M. Hyphantis, T. Inagaki, M. Jenewein, J. Jeon, H.J. Jette, N. Keller, M. Khalifa, D.S. Khamseh, M.E. Kiely, K.M. Kim, S.-W. Kjargaard, M. Kohler, S. Kohlhoff, J. Kohrt, B.A. Kozinszky, Z. Kusminskas, L. Kwan, Y. Lamers, F. Lara, M.A. Lelli, L. Leonardou, A.A. Levin-Aspenson, H.F. Lotrakul, M. Loureiro, S.R. Lowe, B. Luitel, N.P. Lund, C. Maes, M. Marrie, R.A. Marsh, L. Martin-Santos, R. Marx, B.P. Massardo, L. Matsuoka, Y. Mehner, A. Meuti, V. Michopoulos, I. Misery, L. Sidik, S.M. Munhoz, T.N. Muramatsu, K. Radoš, S.N. Nakku, J.E.M. Navarrete, L. Garcia, P.N. Navines, R. Nishi, D. O'Donnell, M.L. Luwa E-Andjafono, D.O. Osório, F.L. Öztürk, A. Peceliuniene, J. Pence, B.W. Persoons, P. Picardi, A. Pintor, L. Ponsford, J.L. Pugh, S.L. Quinn, T.J. Rancans, E. Rathod, S.D. Reme, S.E. Reuter, K. Robertson-Blackmore, E. Rochat, T.J. Rooney, A.G. Rowe, H.J. Sánchez-González, R. Santos, I.S. Schram, M.T. Schwarzbold, M.L. Cankorur, V.S. Shaaban, J. Sharpe, L. Shinn, E.H. Sidebottom, A. Simard, S. Simning, A. Singer, S. Siu, B.W.M. Skalkidou, A. Spangenberg, L. Stafford, L. Stein, A. Stewart, R.C. Stone, J. Su, K.-P. Sultan, S. Sundström-Poromaa, I. Sung, S.C. Suzuki, K. Tadinac, M. Tan, P.L.L. Tandon, S.D. Taylor-Rowan, M. Teixeira, A.L. Tendais, I. Thiagayson, P. Tiringer, I. Töreki, A. Torres-Giménez, A. Tran, T.D. Trevillion, K. Tung, K.-Y. Turner, A. Turner, K. Van Der Feltz-Cornelis, C.M. Van Heyningen, T. Van Weert, H.C. Vega-Dienstmaier, J.M. Vöhringer, P.A. Wagner, L.I. Walterfang, M. Wang, J.L. Wang, W. Wang, L.-J. White, J. Wong, D.K. Wynter, K. Yamada, M. Yonkers, K.A. Zeng, Q.Z. Zhang, Y. DEPRESsion Screening Data (DEPRESSD) Collaboration

Abstract

Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. Results: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80). Conclusions: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics. © 2020

Published
2020

32. May measurement month 2019: The global blood pressure screening campaign of the international society of hypertension

Author

Beaney, T. Schutte, A.E. Stergiou, G.S. Borghi, C. Burger, D. Charchar, F. Cro, S. Diaz, A. Damasceno, A. Espeche, W. Jose, A.P. Khan, N. Kokubo, Y. Maheshwari, A. Marin, M.J. More, A. Neupane, D. Nilsson, P. Patil, M. Prabhakaran, D. Ramirez, A. Rodriguez, P. Schlaich, M. Steckelings, U.M. Tomaszewski, M. Unger, T. Wainford, R. Wang, J. Williams, B. Poulter, N.R. MMM Investigators

Abstract

Elevated blood pressure remains the single biggest risk factor contributing to the global burden of disease and mortality. May Measurement Month is an annual global screening campaign aiming to improve awareness of blood pressure at the individual and population level. Adults (≥18 years) recruited through opportunistic sampling were screened at sites in 92 countries during May 2019. Ideally, 3 blood pressure readings were measured for each participant, and data on lifestyle factors and comorbidities were collected. Hypertension was defined as a systolic blood pressure ≥140 mm Hg, or a diastolic blood pressure ≥90 mm Hg (mean of the second and third readings) or taking antihypertensive medication. When necessary, multiple imputation was used to estimate participants' mean blood pressure. Mixed-effects models were used to evaluate associations between blood pressure and participant characteristics. Of 1 508 130 screenees 482 273 (32.0%) had never had a blood pressure measurement before and 513 337 (34.0%) had hypertension, of whom 58.7% were aware, and 54.7% were on antihypertensive medication. Of those on medication, 57.8% were controlled to

Published
2020

33. Depression prevalence using the HADS-D compared to SCID major depression classification: An individual participant data meta-analysis

Author

Brehaut, E. Neupane, D. Levis, B. Wu, Y. Sun, Y. Krishnan, A. He, C. Bhandari, P.M. Negeri, Z. Riehm, K.E. Rice, D.B. Azar, M. Yan, X.W. Imran, M. Chiovitti, M.J. Saadat, N. Cuijpers, P. Ioannidis, J.P.A. Markham, S. Patten, S.B. Ziegelstein, R.C. Henry, M. Ismail, Z. Loiselle, C.G. Mitchell, N.D. Tonelli, M. Boruff, J.T. Kloda, L.A. Beraldi, A. Braeken, A.P.B.M. Carter, G. Clover, K. Conroy, R.M. Cukor, D. da Rocha e Silva, C.E. De Souza, J. Downing, M.G. Feinstein, A. Ferentinos, P.P. Fischer, F.H. Flint, A.J. Fujimori, M. Gallagher, P. Goebel, S. Jetté, N. Julião, M. Keller, M. Kjærgaard, M. Love, A.W. Löwe, B. Martin-Santos, R. Michopoulos, I. Navines, R. O'Rourke, S.J. Öztürk, A. Pintor, L. Ponsford, J.L. Rooney, A.G. Sánchez-González, R. Schwarzbold, M.L. Sharpe, M. Simard, S. Singer, S. Stone, J. Tung, K.-Y. Turner, A. Walker, J. Walterfang, M. White, J. Benedetti, A. Thombs, B.D.

Abstract

Objectives: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale – depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence. Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated. Results: 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was −21.1% to 19.5%. Conclusions: HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview. © 2020 Elsevier Inc.

Published
2020

34. Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale – Depression subscale scores: An individual participant data meta-analysis of 73 primary studies

Author

Wu, Y. Levis, B. Sun, Y. Krishnan, A. He, C. Riehm, K.E. Rice, D.B. Azar, M. Yan, X.W. Neupane, D. Bhandari, P.M. Imran, M. Chiovitti, M.J. Saadat, N. Boruff, J.T. Cuijpers, P. Gilbody, S. McMillan, D. Ioannidis, J.P.A. Kloda, L.A. Patten, S.B. Shrier, I. Ziegelstein, R.C. Henry, M. Ismail, Z. Loiselle, C.G. Mitchell, N.D. Tonelli, M. Al-Adawi, S. Beraldi, A. Braeken, A.P.B.M. Büel-Drabe, N. Bunevicius, A. Carter, G. Chen, C.-K. Cheung, G. Clover, K. Conroy, R.M. Cukor, D. da Rocha e Silva, C.E. Dabscheck, E. Daray, F.M. Douven, E. Downing, M.G. Feinstein, A. Ferentinos, P.P. Fischer, F.H. Flint, A.J. Fujimori, M. Gallagher, P. Gandy, M. Goebel, S. Grassi, L. Härter, M. Jenewein, J. Jetté, N. Julião, M. Kim, J.-M. Kim, S.-W. Kjærgaard, M. Köhler, S. Loosman, W.L. Löwe, B. Martin-Santos, R. Massardo, L. Matsuoka, Y. Mehnert, A. Michopoulos, I. Misery, L. Navines, R. O'Donnell, M.L. Öztürk, A. Peceliuniene, J. Pintor, L. Ponsford, J.L. Quinn, T.J. Reme, S.E. Reuter, K. Rooney, A.G. Sánchez-González, R. Schwarzbold, M.L. Senturk Cankorur, V. Shaaban, J. Sharpe, L. Sharpe, M. Simard, S. Singer, S. Stafford, L. Stone, J. Sultan, S. Teixeira, A.L. Tiringer, I. Turner, A. Walker, J. Walterfang, M. Wang, L.-J. White, J. Wong, D.K. Benedetti, A. Thombs, B.D.

Abstract

Objective: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). Methods: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores. Results: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)). Conclusion: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity. © 2019 Elsevier Inc.

Published
2020

35. Validation of the COVID-19 Fears Questionnaires for Chronic Medical Conditions: A Scleroderma Patient-centered Intervention Network COVID-19 Cohort study

Author

Wu, Y., Kwakkenbos, L., Henry, R.S., Tao, L.X., Harb, S., Bourgeault, A., Carrier, M.E., Levis, B., Sun, Y., Bhandari, P.M., Carboni-Jiménez, A., Gagarine, M., He, C., Krishnan, A., Negeri, Z.F., Neupane, D., Mouthon, L., Bartlett, S.J., Benedetti, A., Thombs, B.D., Culos-Reed, N., El-Baalbaki, G., Hebblethwaite, S., Patten, S.B., Varga, J., Bustamante, L., Duchek, D., Ellis, K., Rice, D.B., Dyas, L., Fortune, C., Gietzen, A., Guillot, G., Lewis, N., Nielsen, K., Richard, M., Sauvé, M., Welling, J.J.K.C., Wu, Y., Kwakkenbos, L., Henry, R.S., Tao, L.X., Harb, S., Bourgeault, A., Carrier, M.E., Levis, B., Sun, Y., Bhandari, P.M., Carboni-Jiménez, A., Gagarine, M., He, C., Krishnan, A., Negeri, Z.F., Neupane, D., Mouthon, L., Bartlett, S.J., Benedetti, A., Thombs, B.D., Culos-Reed, N., El-Baalbaki, G., Hebblethwaite, S., Patten, S.B., Varga, J., Bustamante, L., Duchek, D., Ellis, K., Rice, D.B., Dyas, L., Fortune, C., Gietzen, A., Guillot, G., Lewis, N., Nielsen, K., Richard, M., Sauvé, M., and Welling, J.J.K.C.

Abstract

Contains fulltext : 226380.pdf (publisher's version ) (Closed access), Objective: Fear associated with medical vulnerability should be considered when assessing mental health among individuals with chronic medical conditions during the COVID-19 pandemic. The objective was to develop and validate the COVID-19 Fears Questionnaire for Chronic Medical Conditions. Methods: Fifteen initial items were generated based on suggestions from 121 people with the chronic autoimmune disease systemic sclerosis (SSc; scleroderma). Patients in a COVID-19 SSc cohort completed items between April 9 and 27, 2020. Exploratory factor analysis (EFA) and item analysis were used to select items for inclusion. Cronbach's alpha and Pearson correlations were used to evaluate internal consistency reliability and convergent validity. Factor structure was confirmed with confirmatory factor analysis (CFA) in follow-up data collection two weeks later. Results: 787 participants completed baseline measures; 563 of them completed the follow-up assessment. Ten of 15 initial items were included in the final questionnaire. EFA suggested that a single dimension explained the data reasonably well. There were no indications of floor or ceiling effects. Cronbach's alpha was 0.91. Correlations between the COVID-19 Fears Questionnaire and measures of anxiety (r = 0.53), depressive symptoms (r = 0.44), and perceived stress (r = 0.50) supported construct validity. CFA supported the single-factor structure (χ2(35) = 311.2, p < 0.001, Tucker-Lewis Index = 0.97, Comparative Fit Index = 0.96, Root Mean Square Error of Approximation = 0.12). Conclusion: The COVID-19 Fears Questionnaire for Chronic Medical Conditions can be used to assess fear among people at risk due to pre-existing medical conditions during the COVID-19 pandemic.

Published
2020

36. Protocol for a partially nested randomised controlled trial to evaluate the effectiveness of the scleroderma patient-centered intervention network COVID-19 home-isolation activities together (SPIN-CHAT) program to reduce anxiety among at-risk scleroderma patients

Author

Thombs, BD, Kwakkenbos, L, Carrier, M-E, Bourgeault, A, Tao, L, Harb, S, Gagarine, M, Rice, D, Bustamante, L, Ellis, K, Duchek, D, Wu, Y, Bhandari, PM, Neupane, D, Carboni-Jimenez, A, Henry, RS, Krishnan, A, Sun, Y, Levis, B, He, C, Turner, KA, Benedetti, A, Culos-Reed, N, El-Baalbaki, G, Hebblethwaite, S, Bartlett, SJ, Dyas, L, Patten, S, Varga, J, Fortune, C, Gietzen, A, Guillot, G, Lewis, N, Nielsen, K, Richard, M, Sauve, M, Welling, J, Baron, M, Furst, DE, Gottesman, K, Malcarne, V, Mayes, MD, Mouthon, L, Nielson, WR, Riggs, R, Wigley, F, Assassi, S, Boutron, I, Ells, C, van den Ende, C, Fligelstone, K, Frech, T, Godard, D, Harel, D, Hinchcliff, M, Hudson, M, Johnson, SR, Larche, M, Leite, C, Nguyen, C, Pope, J, Portales, A, Rannou, F, Rodriguez Reyna, TS, Schouffoer, AA, Suarez-Almazor, ME, Agard, C, Albert, A, Andre, M, Arsenault, G, Benzidia, I, Bernstein, EJ, Berthier, S, Bissonnette, L, Boire, G, Bruns, A, Carreira, P, Casadevall, M, Chaigne, B, Chung, L, Cohen, P, Correia, C, Dagenais, P, Denton, C, Domsic, R, Dubois, S, Dunne, J, Dunogue, B, Fare, R, Farge-Bancel, D, Fortin, PR, Gill, A, Gordon, J, Granel-Rey, B, Gyger, G, Hachulla, E, Hatron, P-Y, Herrick, AL, Hij, A, Hoa, S, Ikic, A, Jones, N, Fernandes, AJDB, Kafaja, S, Khalidi, N, Lambert, M, Launay, D, Liang, P, Maillard, H, Maltez, N, Manning, J, Marie, I, Martin, M, Martin, T, Masetto, A, Maurier, F, Mekinian, A, Melchor, S, Nikpour, M, Olagne, L, Poindron, V, Proudman, S, Regent, A, Riviere, S, Robinson, D, Rodriguez, E, Roux, S, Smets, P, Smith, D, Sobanski, V, Spiera, R, Steen, V, Stevens, W, Sutton, E, Terrier, B, Thorne, C, Wilcox, P, Ayala, MC, Ostbo, N, Thombs, BD, Kwakkenbos, L, Carrier, M-E, Bourgeault, A, Tao, L, Harb, S, Gagarine, M, Rice, D, Bustamante, L, Ellis, K, Duchek, D, Wu, Y, Bhandari, PM, Neupane, D, Carboni-Jimenez, A, Henry, RS, Krishnan, A, Sun, Y, Levis, B, He, C, Turner, KA, Benedetti, A, Culos-Reed, N, El-Baalbaki, G, Hebblethwaite, S, Bartlett, SJ, Dyas, L, Patten, S, Varga, J, Fortune, C, Gietzen, A, Guillot, G, Lewis, N, Nielsen, K, Richard, M, Sauve, M, Welling, J, Baron, M, Furst, DE, Gottesman, K, Malcarne, V, Mayes, MD, Mouthon, L, Nielson, WR, Riggs, R, Wigley, F, Assassi, S, Boutron, I, Ells, C, van den Ende, C, Fligelstone, K, Frech, T, Godard, D, Harel, D, Hinchcliff, M, Hudson, M, Johnson, SR, Larche, M, Leite, C, Nguyen, C, Pope, J, Portales, A, Rannou, F, Rodriguez Reyna, TS, Schouffoer, AA, Suarez-Almazor, ME, Agard, C, Albert, A, Andre, M, Arsenault, G, Benzidia, I, Bernstein, EJ, Berthier, S, Bissonnette, L, Boire, G, Bruns, A, Carreira, P, Casadevall, M, Chaigne, B, Chung, L, Cohen, P, Correia, C, Dagenais, P, Denton, C, Domsic, R, Dubois, S, Dunne, J, Dunogue, B, Fare, R, Farge-Bancel, D, Fortin, PR, Gill, A, Gordon, J, Granel-Rey, B, Gyger, G, Hachulla, E, Hatron, P-Y, Herrick, AL, Hij, A, Hoa, S, Ikic, A, Jones, N, Fernandes, AJDB, Kafaja, S, Khalidi, N, Lambert, M, Launay, D, Liang, P, Maillard, H, Maltez, N, Manning, J, Marie, I, Martin, M, Martin, T, Masetto, A, Maurier, F, Mekinian, A, Melchor, S, Nikpour, M, Olagne, L, Poindron, V, Proudman, S, Regent, A, Riviere, S, Robinson, D, Rodriguez, E, Roux, S, Smets, P, Smith, D, Sobanski, V, Spiera, R, Steen, V, Stevens, W, Sutton, E, Terrier, B, Thorne, C, Wilcox, P, Ayala, MC, and Ostbo, N

Abstract

Objective Contagious disease outbreaks and related restrictions can lead to negative psychological outcomes, particularly in vulnerable populations at risk due to pre-existing medical conditions. No randomised controlled trials (RCTs) have tested interventions to reduce mental health consequences of contagious disease outbreaks. The primary objective of the Scleroderma Patient-centered Intervention Network COVID-19 Home-isolation Activities Together (SPIN-CHAT) Trial is to evaluate the effect of a videoconference-based program on symptoms of anxiety. Secondary objectives include evaluating effects on symptoms of depression, stress, loneliness, boredom, physical activity, and social interaction.

Published
2020

37. Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale - Depression subscale scores: An individual participant data meta-analysis of 73 primary studies

Author

Wu, Y, Levis, B, Sun, Y, Krishnan, A, He, C, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Neupane, D, Bhandari, PM, Imran, M, Chiovitti, MJ, Saadat, N, Boruff, JT, Cuijpers, P, Gilbody, S, McMillan, D, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Tonelli, M, Al-Adawi, S, Beraldi, A, Braeken, APBM, Bueel-Drabe, N, Bunevicius, A, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Cukor, D, Rocha e Silva, CE, Dabscheck, E, Daray, FM, Douven, E, Downing, MG, Feinstein, A, Ferentinos, PP, Fischer, FH, Flint, AJ, Fujimori, M, Gallagher, P, Gandy, M, Goebel, S, Grassi, L, Haerter, M, Jenewein, J, Jette, N, Juliao, M, Kim, J-M, Kim, S-W, Kjaergaard, M, Kohler, S, Loosman, WL, Loewe, B, Martin-Santos, R, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Navines, R, O'Donnell, ML, Ozturk, A, Peceliuniene, J, Pintor, L, Ponsford, JL, Quinn, TJ, Reme, SE, Reuter, K, Rooney, AG, Sanchez-Gonzalez, R, Schwarzbold, ML, Cankorur, VS, Shaaban, J, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, White, J, Wong, DK, Benedetti, A, Thombs, BD, Wu, Y, Levis, B, Sun, Y, Krishnan, A, He, C, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Neupane, D, Bhandari, PM, Imran, M, Chiovitti, MJ, Saadat, N, Boruff, JT, Cuijpers, P, Gilbody, S, McMillan, D, Ioannidis, JPA, Kloda, LA, Patten, SB, Shrier, I, Ziegelstein, RC, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Tonelli, M, Al-Adawi, S, Beraldi, A, Braeken, APBM, Bueel-Drabe, N, Bunevicius, A, Carter, G, Chen, C-K, Cheung, G, Clover, K, Conroy, RM, Cukor, D, Rocha e Silva, CE, Dabscheck, E, Daray, FM, Douven, E, Downing, MG, Feinstein, A, Ferentinos, PP, Fischer, FH, Flint, AJ, Fujimori, M, Gallagher, P, Gandy, M, Goebel, S, Grassi, L, Haerter, M, Jenewein, J, Jette, N, Juliao, M, Kim, J-M, Kim, S-W, Kjaergaard, M, Kohler, S, Loosman, WL, Loewe, B, Martin-Santos, R, Massardo, L, Matsuoka, Y, Mehnert, A, Michopoulos, I, Misery, L, Navines, R, O'Donnell, ML, Ozturk, A, Peceliuniene, J, Pintor, L, Ponsford, JL, Quinn, TJ, Reme, SE, Reuter, K, Rooney, AG, Sanchez-Gonzalez, R, Schwarzbold, ML, Cankorur, VS, Shaaban, J, Sharpe, L, Sharpe, M, Simard, S, Singer, S, Stafford, L, Stone, J, Sultan, S, Teixeira, AL, Tiringer, I, Turner, A, Walker, J, Walterfang, M, Wang, L-J, White, J, Wong, DK, Benedetti, A, and Thombs, BD

Abstract

OBJECTIVE: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). METHODS: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores. RESULTS: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)). CONCLUSION: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity.

Published
2020

38. Depression prevalence using the HADS-D compared to SCID major depression classification: An individual participant data meta-analysis

Author

Brehaut, E, Neupane, D, Levis, B, Wu, Y, Sun, Y, Krishnan, A, He, C, Bhandari, PM, Negeri, Z, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Imran, M, Chiovitti, MJ, Saadat, N, Cuijpers, P, Ioannidis, JPA, Markham, S, Patten, SB, Ziegelstein, RC, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Tonelli, M, Boruff, JT, Kloda, LA, Beraldi, A, Braeken, APBM, Carter, G, Clover, K, Conroy, RM, Cukor, D, da Rocha E Silva, CE, De Souza, J, Downing, MG, Feinstein, A, Ferentinos, PP, Fischer, FH, Flint, AJ, Fujimori, M, Gallagher, P, Goebel, S, Jette, N, Juliao, M, Keller, M, Kjaergaard, M, Love, AW, Loewe, B, Martin-Santos, R, Michopoulos, I, Navines, R, O'Rourke, SJ, Ozturk, A, Pintor, L, Ponsford, JL, Rooney, AG, Sanchez-Gonzalez, R, Schwarzbold, ML, Sharpe, M, Simard, S, Singer, S, Stone, J, Tung, K-Y, Turner, A, Walker, J, Walterfang, M, White, J, Benedetti, A, Thombs, BD, Brehaut, E, Neupane, D, Levis, B, Wu, Y, Sun, Y, Krishnan, A, He, C, Bhandari, PM, Negeri, Z, Riehm, KE, Rice, DB, Azar, M, Yan, XW, Imran, M, Chiovitti, MJ, Saadat, N, Cuijpers, P, Ioannidis, JPA, Markham, S, Patten, SB, Ziegelstein, RC, Henry, M, Ismail, Z, Loiselle, CG, Mitchell, ND, Tonelli, M, Boruff, JT, Kloda, LA, Beraldi, A, Braeken, APBM, Carter, G, Clover, K, Conroy, RM, Cukor, D, da Rocha E Silva, CE, De Souza, J, Downing, MG, Feinstein, A, Ferentinos, PP, Fischer, FH, Flint, AJ, Fujimori, M, Gallagher, P, Goebel, S, Jette, N, Juliao, M, Keller, M, Kjaergaard, M, Love, AW, Loewe, B, Martin-Santos, R, Michopoulos, I, Navines, R, O'Rourke, SJ, Ozturk, A, Pintor, L, Ponsford, JL, Rooney, AG, Sanchez-Gonzalez, R, Schwarzbold, ML, Sharpe, M, Simard, S, Singer, S, Stone, J, Tung, K-Y, Turner, A, Walker, J, Walterfang, M, White, J, Benedetti, A, and Thombs, BD

Abstract

OBJECTIVES: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale - depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence. METHODS: We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated. RESULTS: 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was -21.1% to 19.5%. CONCLUSIONS: HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview.

Published
2020

39. May Measurement Month 2018: an analysis of blood pressure screening results from Nepal.

Author

Adhikari, TB, Bhattarai, H, Ranabhat, K, Khanal, P, Mishra, SR, Koirala, S, Pandey, S, Devkota, S, Gairhe, M, Dhamala, B, Soti, PB, Paudel, S, Lohani, G, Koirala, B, Beaney, T, Ster, AC, Poulter, NR, Neupane, D, Adhikari, TB, Bhattarai, H, Ranabhat, K, Khanal, P, Mishra, SR, Koirala, S, Pandey, S, Devkota, S, Gairhe, M, Dhamala, B, Soti, PB, Paudel, S, Lohani, G, Koirala, B, Beaney, T, Ster, AC, Poulter, NR, and Neupane, D

Abstract

Raised blood pressure (BP) is a leading risk factor for mortality globally and in Nepal. May Measurement Month (MMM) is a global initiative aimed at screening for hypertension and raising awareness on high BP worldwide. This study provides the results of the 2018 MMM (MMM18) in Nepal. An opportunistic cross-sectional survey of volunteers aged ≥18 years was carried out in May 2018 nationwide. The standard MMM protocol was followed for BP measurement, the definition of hypertension, and statistical analysis. The campaign was publicized through various social media for recruiting volunteers and inviting participation. A total of 15 561 (58.7% male) from 35 districts of Nepal were screened in MMM18, of which 4 321 (27.8%) had hypertension. A total of 2 633 (19.0%) of 13 873 individuals who were not on antihypertensive treatment were found to be hypertensive. Of those on medication, 799 (47.4%) had uncontrolled BP. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly higher in people on antihypertensive treatment, smokers, and alcohol drinkers compared with those who were not on antihypertensive treatment, smokers, and alcohol drinkers, respectively. Likewise, SBP and DBP steadily increased across increasing body mass index categories. MMM18 was the largest BP screening campaign undertaken in Nepal. MMM has highlighted the importance of a periodic public health program at the national level to increase awareness on hypertension detection and control rate, and thus, the prevention of cardiovascular diseases.

Published
2020

40. Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis

Author

McGrath, S, Zhao, X, Steele, R, Thombs, BD, Benedetti, A, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Sun, Y, Krishnan, A, He, C, Wu, Y, Bhandari, PM, Neupane, D, Imran, M, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Akena, DH, Arroll, B, Ayalon, L, Baradaran, HR, Baron, M, Beraldi, A, Bombardier, CH, Butterworth, P, Carter, G, Chagas, MH, Chan, JCN, Cholera, R, Chowdhary, N, Clover, K, Conwell, Y, Ginkel, JMDM-V, Delgadillo, J, Fann, JR, Fischer, FH, Fischler, B, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, CG, Hall, BJ, Harrison, PA, Harter, M, Hegerl, U, Hides, L, Hobfoll, SE, Hudson, M, Hyphantis, T, Inagaki, M, Ismail, K, Jette, N, Khamseh, ME, Kiely, KM, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, SR, Loewe, B, Marsh, L, McGuire, A, Sidik, SM, Munhoz, TN, Muramatsu, K, Osorio, FL, Patel, V, Pence, BW, Persoons, P, Picardi, A, Reuter, K, Rooney, AG, Santos, IS, Shaaban, J, Sidebottom, A, Simning, A, Stafford, L, Sung, SC, Tan, PLL, Turner, A, van der Feltz-Cornelis, CM, van Weert, HC, Vohringer, PA, White, J, Whooley, MA, Winkley, K, Yamada, M, Zhang, Y, McGrath, S, Zhao, X, Steele, R, Thombs, BD, Benedetti, A, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Sun, Y, Krishnan, A, He, C, Wu, Y, Bhandari, PM, Neupane, D, Imran, M, Boruff, J, Cuijpers, P, Gilbody, S, Ioannidis, JPA, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Akena, DH, Arroll, B, Ayalon, L, Baradaran, HR, Baron, M, Beraldi, A, Bombardier, CH, Butterworth, P, Carter, G, Chagas, MH, Chan, JCN, Cholera, R, Chowdhary, N, Clover, K, Conwell, Y, Ginkel, JMDM-V, Delgadillo, J, Fann, JR, Fischer, FH, Fischler, B, Fung, D, Gelaye, B, Goodyear-Smith, F, Greeno, CG, Hall, BJ, Harrison, PA, Harter, M, Hegerl, U, Hides, L, Hobfoll, SE, Hudson, M, Hyphantis, T, Inagaki, M, Ismail, K, Jette, N, Khamseh, ME, Kiely, KM, Kwan, Y, Lamers, F, Liu, S-I, Lotrakul, M, Loureiro, SR, Loewe, B, Marsh, L, McGuire, A, Sidik, SM, Munhoz, TN, Muramatsu, K, Osorio, FL, Patel, V, Pence, BW, Persoons, P, Picardi, A, Reuter, K, Rooney, AG, Santos, IS, Shaaban, J, Sidebottom, A, Simning, A, Stafford, L, Sung, SC, Tan, PLL, Turner, A, van der Feltz-Cornelis, CM, van Weert, HC, Vohringer, PA, White, J, Whooley, MA, Winkley, K, Yamada, M, and Zhang, Y

Abstract

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data.

Published
2020

41. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis.

Author

Levis, B, Benedetti, A, Ioannidis, JPA, Sun, Y, Negeri, Z, He, C, Wu, Y, Krishnan, A, Bhandari, PM, Neupane, D, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Boruff, J, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Alamri, SH, Amtmann, D, Ayalon, L, Baradaran, HR, Beraldi, A, Bernstein, CN, Bhana, A, Bombardier, CH, Carter, G, Chagas, MH, Chibanda, D, Clover, K, Conwell, Y, Diez-Quevedo, C, Fann, JR, Fischer, FH, Gholizadeh, L, Gibson, LJ, Green, EP, Greeno, CG, Hall, BJ, Haroz, EE, Ismail, K, Jetté, N, Khamseh, ME, Kwan, Y, Lara, MA, Liu, S-I, Loureiro, SR, Löwe, B, Marrie, RA, Marsh, L, McGuire, A, Muramatsu, K, Navarrete, L, Osório, FL, Petersen, I, Picardi, A, Pugh, SL, Quinn, TJ, Rooney, AG, Shinn, EH, Sidebottom, A, Spangenberg, L, Tan, PLL, Taylor-Rowan, M, Turner, A, van Weert, HC, Vöhringer, PA, Wagner, LI, White, J, Winkley, K, Thombs, BD, Levis, B, Benedetti, A, Ioannidis, JPA, Sun, Y, Negeri, Z, He, C, Wu, Y, Krishnan, A, Bhandari, PM, Neupane, D, Imran, M, Rice, DB, Riehm, KE, Saadat, N, Azar, M, Boruff, J, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Shrier, I, Ziegelstein, RC, Alamri, SH, Amtmann, D, Ayalon, L, Baradaran, HR, Beraldi, A, Bernstein, CN, Bhana, A, Bombardier, CH, Carter, G, Chagas, MH, Chibanda, D, Clover, K, Conwell, Y, Diez-Quevedo, C, Fann, JR, Fischer, FH, Gholizadeh, L, Gibson, LJ, Green, EP, Greeno, CG, Hall, BJ, Haroz, EE, Ismail, K, Jetté, N, Khamseh, ME, Kwan, Y, Lara, MA, Liu, S-I, Loureiro, SR, Löwe, B, Marrie, RA, Marsh, L, McGuire, A, Muramatsu, K, Navarrete, L, Osório, FL, Petersen, I, Picardi, A, Pugh, SL, Quinn, TJ, Rooney, AG, Shinn, EH, Sidebottom, A, Spangenberg, L, Tan, PLL, Taylor-Rowan, M, Turner, A, van Weert, HC, Vöhringer, PA, Wagner, LI, White, J, Winkley, K, and Thombs, BD

Abstract

OBJECTIVES: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores ≥10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 ≥10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence. STUDY DESIGN AND SETTING: Individual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status. RESULTS: A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 ≥10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%); pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%); and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 ≥10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 ≥14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 ≥14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%). CONCLUSION: PHQ-9 ≥10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in individual studies.

Published
2020

42. Effectiveness of a scalable group-based education and monitoring program, delivered by health workers, to improve control of hypertension in rural India: A cluster randomised controlled trial.

Author

Neupane, D, Gamage, DG, Riddell, MA, Joshi, R, Thankappan, KR, Chow, CK, Oldenburg, B, Evans, RG, Mahal, AS, Kalyanram, K, Kartik, K, Suresh, O, Thomas, N, Mini, GK, Maulik, PK, Srikanth, VK, Arabshahi, S, Varma, RP, Guggilla, RK, D'Esposito, F, Sathish, T, Alim, M, Thrift, AG, Neupane, D, Gamage, DG, Riddell, MA, Joshi, R, Thankappan, KR, Chow, CK, Oldenburg, B, Evans, RG, Mahal, AS, Kalyanram, K, Kartik, K, Suresh, O, Thomas, N, Mini, GK, Maulik, PK, Srikanth, VK, Arabshahi, S, Varma, RP, Guggilla, RK, D'Esposito, F, Sathish, T, Alim, M, and Thrift, AG

Abstract

BACKGROUND: New methods are required to manage hypertension in resource-poor settings. We hypothesised that a community health worker (CHW)-led group-based education and monitoring intervention would improve control of blood pressure (BP). METHODS AND FINDINGS: We conducted a baseline community-based survey followed by a cluster randomised controlled trial of people with hypertension in 3 rural regions of South India, each at differing stages of epidemiological transition. Participants with hypertension, defined as BP ≥ 140/90 mm Hg or taking antihypertensive medication, were advised to visit a doctor. In each region, villages were randomly assigned to intervention or usual care (UC) in a 1:2 ratio. In intervention clusters, trained CHWs delivered a group-based intervention to people with hypertension. The program, conducted fortnightly for 3 months, included monitoring of BP, education about hypertension, and support for healthy lifestyle change. Outcomes were assessed approximately 2 months after completion of the intervention. The primary outcome was control of BP (BP < 140/90 mm Hg), analysed using mixed effects regression, clustered by village within region and adjusted for baseline control of hypertension (using intention-to-treat principles). Of 2,382 potentially eligible people, 637 from 5 intervention clusters and 1,097 from 10 UC clusters were recruited between November 2015 and April 2016, with follow-up occurring in 459 in the intervention group and 1,012 in UC. Mean age was 56.9 years (SD 13.7). Baseline BP was similar between groups. Control of BP improved from baseline to follow-up more in the intervention group (from 227 [49.5%] to 320 [69.7%] individuals) than in the UC group (from 528 [52.2%] to 624 [61.7%] individuals) (odds ratio [OR] 1.6, 95% CI 1.2-2.1; P = 0.001). In secondary outcome analyses, there was a greater decline in systolic BP in the intervention than UC group (-5.0 mm Hg, 95% CI -7.1 to -3.0; P < 0.001) and a greater decline in dias

Published
2020

48. May measurement month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension (vol 40, pg 2006, 2019)

Author

Beaney, T, Burrell, LM, Castillo, RR, Charchar, FJ, Cro, S, Damasceno, A, Kruger, R, Nilsson, PM, Prabhakaran, D, Ramirez, AJ, Schlaich, MP, Schutte, AE, Tomaszewski, M, Touyz, R, Wang, JG, Weber, MA, Poulter, NR, Burazeri, G, Qirjako, G, Roshi, E, Cunashi, R, Fernandes, MJCC, Pereira, VSS, Neto, MFMP, Oliveira, PNM, Feijao, ACG, Cerniello, Y, Marin, MJ, Vasquez, GF, Espeche, WG, Stisman, D, Fuentes, IA, Zilberman, JM, Rodriguez, P, Babinyan, KY, Engibaryan, AH, Avagyan, AM, Minasyan, AA, Gevorkyan, AT, Carnagarin, R, Carrington, MJ, Sharman, JE, Lee, R, Perl, S, Niederl, E, Malik, FT, Choudhury, SR, Al Mamun, MA, Ishraquzzaman, M, Anthony, F, Connell, K, De Backer, TLM, Krzesinski, J, Houenassi, MD, Houehanou, CY, Sokolovic, S, Bahtijarevic, R, Tiro, MB, Mosepele, M, Masupe, TK, Barroso, WS, Gomes, MAM, Feitosa, ADM, Brandao, AA, Miranda, RD, Azevedo, VMAA, Dias, LM, Garcia, GDN, Martins, IPP, Dzudie, A, Kingue, S, Djomou, FAN, Njume, E, Khan, N, Lanas, FT, Garcia, MS, Paccot, MF, Torres, P, Li, Y, Liu, M, Xu, L, Li, L, Chen, X, Deng, J, Zhao, W, Fu, L, Zhou, Y, Lopez-Jaramillo, P, Otero, J, Camacho, PA, Accini, JL, Sanchez, G, Arcos, E, M'Buyamba-Kabangu, JR, Katamba, FK, Ngoyi, GN, Buila, NM, Bayauli, PM, Mbolla, EBF, Bakekolo, PR, Landa, KCM, Kaky, KGS, Kramoh, EK, Ngoran, YNK, Olsen, MH, Valoy, VL, Santillan, M, Rafael, AGM, Penaherrera, CE, Villalba, J, Ramirez, M, Arteaga, F, Delgado, P, Beistline, H, Cappuccio, FP, Keitley, J, Tay, T, Goshu, DY, Kassie, DM, Gebru, SA, Pathak, A, Denolle, T, Tsinamdzgvrishvili, B, Trapaidze, D, Sturua, L, Abesadze, T, Grdzelidze, N, Grabfelder, M, Kramer, BK, Schmeider, RE, Twumasi-Ankrah, B, Tannor, EK, Lincoln, MD, Deku, EM, Quintana, WFS, Kenerson, J, Baptiste, JED, Saintilmond, WW, Barrientos, AL, Jose, PA, More, A, Takalkar, A, Turana, Y, Widyantoro, B, Danny, SS, Djono, S, Handari, SD, Tambunan, M, Tiksnadi, BB, Hermiawaty, E, Tavassoli, E, Zolfaghari, M, Dolan, E, O'Brien, E, Borghi, C, Ferri, C, Torlasco, C, Parati, G, Nwokocha, CR, Nwokocha, M, Ogola, EN, Gitura, BM, Barasa, AL, Barasa, FA, Wairagu, AW, Nalwa, WZ, Najem, RN, Abu Alfa, AK, Fageh, HA, Msalam, OM, Derbi, HA, Bettamar, KA, Zakauskiene, U, Vickiene, A, Calmes, J, Alkerwi, A, Gantenbein, M, Ndhlovu, HLL, Masiye, JK, Chirwa, ML, Nyirenda, NM, Dhlamini, TD, Chia, YC, Ching, SM, Devaraj, NK, Ouane, N, Fane, T, Kowlessur, S, Ori, B, Heecharan, J, Alcocer, L, Chavez, A, Ruiz, G, Espinosa, C, Gomez-Alvarez, E, Neupane, D, Bhattarai, H, Ranabhat, K, Adhikari, TB, Koirala, S, Toure, IA, Soumana, KH, Wahab, KW, Omotoso, AB, Sani, MU, Okubadejo, NU, Nadar, SK, Al-Riyami, HA, Ishaq, M, Memon, F, Sidique, S, Choudhry, HA, Khan, RA, Ayala, M, Maidana, AJO, Bogado, GG, Ona, D, Atilano, A, Granada, C, Bartolome, R, Manese, L, Mina, A, Dumlao, MC, Villaruel, MC, Gomez, L, Jozwiak, J, Malyszko, J, Banach, M, Mastej, M, Rodrigues, DCMM, Martins, LL, Paval, A, Dorobantu, M, Konradi, AO, Chazova, IE, Rotar, O, Spoares, MC, Viegas, D, Almustafa, BA, Alshurafa, SA, Brady, A, Bovet, P, Viswanathan, B, Oladapo, OO, Russell, JW, Beheiry, HM, Ali, IA, Osman, AAA, Fahal, NAW, Osman, HA, Altahir, F, Persson, M, Wuerzner, G, Burkard, T, Wang, TD, Lin, HJ, Pan, HY, Chen, WJ, Lin, E, Mondo, CK, Ingabire, PM, Khomazyuk, TT, Krotova, VV, Negresku, E, Evstigneeva, O, Bazargani, NN, Agrawal, A, Bin Belaila, BA, Suhail, AM, Muhammed, KO, Shuri, HH, Wainford, RD, Levy, PD, Boggia, JJ, Garre, LL, Hernandez-Hernandez, R, Octavio-Seijas, JA, Lopez-Rivera, JA, Morr, I, Duin, A, Huynh, M, Cao, ST, Nguyen, VL, To, M, Phan, HN, Cockroft, J, McDonnell, B, Goma, FM, Syatalimi, C, Chifamba, J, Gwini, R, Tiburcio, O, and Xia, X

Subjects
Science & Technology, Cardiac & Cardiovascular Systems, Cardiovascular System & Hematology, Cardiovascular System & Cardiology, 1103 Clinical Sciences, Life Sciences & Biomedicine, 1102 Cardiorespiratory Medicine and Haematology
Published
2019

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