23 results on '"A Wimo"'
Search Results
2. On the 2024 Alzheimer’s Association Criteria: Still Not Ready for Clinical Use
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Zhou, Robin Ziyue, Wimo, A., and Winblad, B.
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- 2024
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3. Validation of the Health Assessment Tool (HAT) based on four aging cohorts from the Swedish National study on Aging and Care
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Ahmad Abbadi, Emmanouil Kokoroskos, Matthew Stamets, Davide L. Vetrano, Nicola Orsini, Sölve Elmståhl, Cecilia Fagerström, Anders Wimo, Anders Sköldunger, Johan Sanmartin Berglund, Christina B. Olsson, Caroline Wachtler, Laura Fratiglioni, and Amaia Calderón-Larrañaga
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Geriatric health assessment ,Frailty ,Aging cohorts ,External validation ,Medicine - Abstract
Abstract Background As global aging accelerates, routinely assessing the functional status and morbidity burden of older patients becomes paramount. The aim of this study is to assess the validity of the comprehensive clinical and functional Health Assessment Tool (HAT) based on four cohorts of older adults (60 + years) from the Swedish National study on Aging and Care (SNAC) spanning urban, suburban, and rural areas. Methods The HAT integrates five health indicators (gait speed, global cognition, number of chronic diseases, and basic and instrumental activities of daily living), providing an individual-level score between 0 and 10. The tool was constructed using nominal response models, first separately for each cohort and then in a harmonized dataset. Outcomes included all-cause mortality over a maximum follow-up of 16 years and unplanned hospital admissions over a maximum of 3 years of follow-up. The predictive capacity was assessed through the area under the curve (AUC) using logistic regressions. For time to death, Cox regressions were performed, and Harrell’s C-indices were reported. Results from the four cohorts were pooled using individual participant data meta-analysis and compared with those from the harmonized dataset. Results The HAT demonstrated high predictive capacity across all cohorts as well as in the harmonized dataset. In the harmonized dataset, the AUC was 0.84 (95% CI 0.81–0.87) for 1-year mortality, 0.81 (95% CI 0.80–0.83) for 3-year mortality, 0.80 (95% CI 0.79–0.82) for 5-year mortality, 0.69 (95% CI 0.67–0.70) for 1-year unplanned admissions, and 0.69 (95% CI 0.68–0.70) for 3-year unplanned admissions. The Harrell’s C for time-to-death throughout 16 years of follow-up was 0.75 (95% CI 0.74–0.75). Conclusions The HAT is a highly predictive, clinically intuitive, and externally valid instrument with potential for better addressing older adults’ health needs and optimizing risk stratification at the population level.
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- 2024
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4. Integrating a multimodal lifestyle intervention with medical food in prodromal Alzheimer’s disease: the MIND-ADmini randomized controlled trial
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Charlotta Thunborg, Rui Wang, Anna Rosenberg, Shireen Sindi, Pia Andersen, Sandrine Andrieu, Laus M. Broersen, Nicola Coley, Celine Couderc, Celine Z. Duval, Gerd Faxen-Irving, Göran Hagman, Merja Hallikainen, Krister Håkansson, Eija Kekkonen, Jenni Lehtisalo, Nicholas Levak, Francesca Mangialasche, Johannes Pantel, Anders Rydström, Anna Stigsdotter-Neely, Anders Wimo, Tiia Ngandu, Hilkka Soininen, Tobias Hartmann, Alina Solomon, and Miia Kivipelto
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Alzheimer’s disease ,Lifestyle intervention ,Multimodal intervention ,Adherence ,Medical food ,Prevention ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Abstract Background The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) showed cognitive benefits from a multidomain lifestyle intervention in at-risk older people. The LipiDiDiet trial highlighted benefits of medical food in prodromal Alzheimer’s disease (AD). However, the feasibility and impact of multimodal interventions combining lifestyle with medical food in prodromal AD is unclear. Methods MIND-ADmini was a 6-month multinational (Sweden, Finland, Germany, France) proof-of-concept randomized controlled trial (RCT). Participants were 60–85 years old, had prodromal AD (International Working Group-1 criteria), and vascular/lifestyle risk factors. The parallel-group RCT had three arms: multimodal lifestyle intervention (nutritional guidance, exercise, cognitive training, vascular/metabolic risk management and social stimulation); multimodal lifestyle intervention + medical food (Fortasyn Connect); and regular health advice/care (control). Participants were randomized 1:1:1 (computer-generated allocation at each site). Outcome evaluators were blinded to randomization. Primary outcome was feasibility of the multimodal intervention, evaluated by recruitment rate during a 6-month recruitment phase, overall adherence in each intervention arm, and 6-month retention rate. Successful adherence was pre-specified as attending ≥ 40% of sessions/domain in ≥ 2/4 domains (lifestyle intervention), and consuming ≥ 60% of the medical food (lifestyle intervention + medical food). The secondary outcomes included adherence/participation to each intervention component and overall adherence to healthy lifestyle changes, measured using a composite score for healthy lifestyle. Cognitive assessments were included as exploratory outcomes, e.g. Clinical Dementia Rating scale. Results During September 2017-May 2019, 93 individuals were randomized (32 lifestyle intervention, 31 lifestyle + medical food, and 30 control group). Overall recruitment rate was 76.2% (64.8% during the first 6 months). Overall 6-month retention rate was 91.4% (lifestyle intervention 87.5%; lifestyle + medical food 90.3%; control 96.7%). Domain-specific adherence in the lifestyle intervention group was 71.9% to cognitive training, 78.1% exercise, 68.8% nutritional guidance, and 81.3% vascular risk management; and in the lifestyle + medical food group, 90.3% to cognitive training, 87.1% exercise, 80.7% nutritional guidance, 87.1% vascular risk management, and 87.1% medical food. Compared with control, both intervention arms showed healthy diet improvements (βLifestyle×Time = 1.11, P = 0.038; βLifestyle+medical food×Time = 1.43, P = 0.007); the lifestyle + medical food group also showed vascular risk reduction (P = 0.043) and less cognitive-functional decline (P
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- 2024
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5. Estimates of Current Capacity for Diagnosing Alzheimer’s Disease in Sweden and the Need to Expand Specialist Numbers
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Mattke, Soeren, Gustavsson, A., Jacobs, L., Kern, S., Palmqvist, S., Eriksdotter, M., Skoog, I., Winblad, B., Wimo, A., and Jönsson, L.
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- 2024
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6. Prevention of dementia using mobile phone applications (PRODEMOS): a multinational, randomised, controlled effectiveness–implementation trial
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Witvliet, Patrick, Hoitink, Mart, van de Groep, Bram, Liu, Hongmei, Ge, Siqi, He, Mingyue, Li, Cancan, Jian, Xuening, Jiang, Bin, Sun, Haixin, Ru, Xiaojuan, Sun, Dongling, Lian, Tenghong, Zhang, Weijiao, Zhang, Wenjing, Qi, Jing, Li, Jinghui, Guan, Huiying, Luo, Dongmei, Zhang, Weijia, Yue, Hao, Zheng, Zijing, Zeng, Qiang, Yang, Huangdai, Tang, Yanyan, Tao, Tianqi, Song, Yan, Meng, Xiaosheng, Zhu, Sirui, Jia, Dongmei, Li, Mo, Li, Wenjie, Mu, Haiyan, Jiang, Wenjing, Gao, Wenchao, Hu, Yueqing, Wang, Guohua, Xu, Xizhu, Zhang, Yichun, Li, Dong, Zhang, Xiaoyu, Guo, Xiuhua, Ye, Xiaoyan, Wei, Xi, Moll van Charante, Eric P, Hoevenaar-Blom, Marieke P, Song, Manshu, Andrieu, Sandrine, Barnes, Linda, Birck, Cindy, Brooks, Rachael, Coley, Nicola, Eggink, Esmé, Georges, Jean, Hafdi, Melanie, van Gool, Willem A, Handels, Ron, Hou, Haifeng, Lyu, Jihui, Niu, Yixuan, Song, Libin, Wang, Wenzhi, Wang, Youxin, Wimo, Anders, Yu, Yueyi, Zhang, Jinxia, Zhang, Wei, Brayne, Carol, Wang, Wei, and Richard, Edo
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- 2024
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7. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Ferrari, Alize J, Santomauro, Damian Francesco, Aali, Amirali, Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbastabar, Hedayat, Abd ElHafeez, Samar, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdollahi, Arash, Abdullahi, Auwal, Abegaz, Kedir Hussein, Abeldaño Zuñiga, Roberto Ariel, Aboagye, Richard Gyan, Abolhassani, Hassan, Abreu, Lucas Guimarães, Abualruz, Hasan, Abu-Gharbieh, Eman, Abu-Rmeileh, Niveen ME, Ackerman, Ilana N, Addo, Isaac Yeboah, Addolorato, Giovanni, Adebiyi, Akindele Olupelumi, Adepoju, Abiola Victor, Adewuyi, Habeeb Omoponle, Afyouni, Shadi, Afzal, Saira, Afzal, Sina, Agodi, Antonella, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Firdos, Ahmad, Shahzaib, Ahmed, Ali, Ahmed, Luai A, Ahmed, Muktar Beshir, Ajami, Marjan, Akinosoglou, Karolina, Akkaif, Mohammed Ahmed, Al Hasan, Syed Mahfuz, Alalalmeh, Samer O, Al-Aly, Ziyad, Albashtawy, Mohammed, Aldridge, Robert W, Alemu, Meseret Desalegn, Alemu, Yihun Mulugeta, Alene, Kefyalew Addis, Al-Gheethi, Adel Ali Saeed, Alharrasi, Maryam, Alhassan, Robert Kaba, Ali, Mohammed Usman, Ali, Rafat, Ali, Syed Shujait Shujait, Alif, Sheikh Mohammad, Aljunid, Syed Mohamed, Al-Marwani, Sabah, Almazan, Joseph Uy, Alomari, Mahmoud A, Al-Omari, Basem, Altaany, Zaid, Alvis-Guzman, Nelson, Alvis-Zakzuk, Nelson J, Alwafi, Hassan, Al-Wardat, Mohammad Sami, Al-Worafi, Yaser Mohammed, Aly, Safwat, Alzoubi, Karem H, Amare, Azmeraw T, Amegbor, Prince M, Ameyaw, Edward Kwabena, Amin, Tarek Tawfik, Amindarolzarbi, Alireza, Amiri, Sohrab, Amugsi, Dickson A, Ancuceanu, Robert, Anderlini, Deanna, Anderson, David B, Andrade, Pedro Prata, Andrei, Catalina Liliana, Ansari, Hossein, Antony, Catherine M, Anwar, Saleha, Anwar, Sumadi Lukman, Anwer, Razique, Anyanwu, Philip Emeka, Arab, Juan Pablo, Arabloo, Jalal, Arafat, Mosab, Araki, Daniel T, Aravkin, Aleksandr Y, Arkew, Mesay, Armocida, Benedetta, Arndt, Michael Benjamin, Arooj, Mahwish, Artamonov, Anton A, Aruleba, Raphael Taiwo, Arumugam, Ashokan, Ashbaugh, Charlie, Ashemo, Mubarek Yesse, Ashraf, Muhammad, Asika, Marvellous O, Askari, Elaheh, Astell-Burt, Thomas, Athari, Seyyed Shamsadin, Atorkey, Prince, Atout, Maha Moh'd Wahbi, Atreya, Alok, Aujayeb, Avinash, Ausloos, Marcel, Avan, Abolfazl, Awotidebe, Adedapo Wasiu, Awuviry-Newton, Kofi, Ayala Quintanilla, Beatriz Paulina, Ayuso-Mateos, Jose L, Azadnajafabad, Sina, Azevedo, Rui M S, Babu, Abraham Samuel, Badar, Muhammad, Badiye, Ashish D, Baghdadi, Soroush, Bagheri, Nasser, Bah, Sulaiman, Bai, Ruhai, Baker, Jennifer L, Bakkannavar, Shankar M, Bako, Abdulaziz T, Balakrishnan, Senthilkumar, Bam, Kiran, Banik, Palash Chandra, Barchitta, Martina, Bardhan, Mainak, Bardideh, Erfan, Barker-Collo, Suzanne Lyn, Barqawi, Hiba Jawdat, Barrow, Amadou, Barteit, Sandra, Barua, Lingkan, Bashiri Aliabadi, Somaye, Basiru, Afisu, Basu, Sanjay, Basu, Saurav, Bathini, Prapthi Persis, Batra, Kavita, Baune, Bernhard T, Bayileyegn, Nebiyou Simegnew, Behnam, Babak, Behnoush, Amir Hossein, Beiranvand, Maryam, Bejarano Ramirez, Diana Fernanda, Bell, Michelle L, Bello, Olorunjuwon Omolaja, Beloukas, Apostolos, Bensenor, Isabela M, Berezvai, Zombor, Bernabe, Eduardo, Bernstein, Robert S, Bettencourt, Paulo J G, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhandari, Dinesh, Bhargava, Ashish, Bhaskar, Sonu, Bhat, Vivek, Bhatti, Gurjit Kaur, Bhatti, Jasvinder Singh, Bhatti, Manpreet S, Bhatti, Rajbir, Bhutta, Zulfiqar A, Bikbov, Boris, Bishai, Jessica Devin, Bisignano, Catherine, Bitra, Veera R, Bjørge, Tone, Bodolica, Virginia, Bodunrin, Aadam Olalekan, Bogale, Eyob Ketema, Bonakdar Hashemi, Milad, Bonny, Aime, Bora Basara, Berrak, Borhany, Hamed, Boxe, Christopher, Brady, Oliver J, Bragazzi, Nicola Luigi, Braithwaite, Dejana, Brant, Luisa C, Brauer, Michael, Breitner, Susanne, Brenner, Hermann, Brown, Julie, Brugha, Traolach, Bulamu, Norma B, Buonsenso, Danilo, Burkart, Katrin, Burns, Richard A, Busse, Reinhard, Bustanji, Yasser, Butt, Zahid A, Byun, Justin, Caetano dos Santos, Florentino Luciano, Calina, Daniela, Cámera, Luis Alberto, Campos-Nonato, Ismael R, Cao, Chao, Capodici, Angelo, Carr, Sinclair, Carreras, Giulia, Carugno, Andrea, Carvalho, Márcia, Castaldelli-Maia, Joao Mauricio, Castañeda-Orjuela, Carlos A, Castelpietra, Giulio, Catapano, Alberico L, Cattaruzza, Maria Sofia, Caye, Arthur, Cegolon, Luca, Cembranel, Francieli, Cenderadewi, Muthia, Cerin, Ester, Chakraborty, Promit Ananyo, Chan, Jeffrey Shi Kai, Chan, Raymond N C, Chandika, Rama Mohan, Chandrasekar, Eeshwar K, Charalampous, Periklis, Chattu, Vijay Kumar, Chatzimavridou-Grigoriadou, Victoria, Chen, Angela W, Chen, An-Tian, Chen, Catherine S, Chen, Haowei, Chen, Nathalie M, Cheng, Esther T W, Chimed-Ochir, Odgerel, Chimoriya, Ritesh, Ching, Patrick R, Cho, William C S, Choi, Sungchul, Chong, Bryan, Chong, Yuen Yu, Choudhari, Sonali Gajanan, Chowdhury, Rajiv, Christensen, Steffan Wittrup McPhee, Chu, Dinh-Toi, Chukwu, Isaac Sunday, Chung, Eric, Chung, Eunice, Chutiyami, Muhammad, Claassens, Mareli M, Cogen, Rebecca M, Columbus, Alyssa, Conde, Joao, Cortesi, Paolo Angelo, Cousin, Ewerton, Criqui, Michael H, Cruz-Martins, Natália, Dadras, Omid, Dai, Siyu, Dai, Xiaochen, Dai, Zhaoli, Dalaba, Maxwell Ayindenaba, Damiani, Giovanni, Das, Jai K, Das, Saswati, Dashti, Mohsen, Dávila-Cervantes, Claudio Alberto, Davletov, Kairat, De Leo, Diego, Debele, Aklilu Tamire, Debopadhaya, Shayom, DeCleene, Nicole K, Deeba, Farah, Degenhardt, Louisa, Del Bo', Cristian, Delgado-Enciso, Ivan, Demetriades, Andreas K, Denova-Gutiérrez, Edgar, Dervenis, Nikolaos, Desai, Hardik Dineshbhai, Desai, Rupak, Deuba, Keshab, Dhama, Kuldeep, Dharmaratne, Samath Dhamminda, Dhingra, Sameer, Dias da Silva, Diana, Diaz, Daniel, Diaz, Luis Antonio, Diaz, Michael J, Dima, Adriana, Ding, Delaney D, Dirac, M Ashworth, Do, Thao Huynh Phuong, do Prado, Camila Bruneli, Dohare, Sushil, Dominguez, Regina-Mae Villanueva, Dong, Wanyue, Dongarwar, Deepa, D'Oria, Mario, Dorsey, E Ray, Doshmangir, Leila, Dowou, Robert Kokou, Driscoll, Tim Robert, Dsouza, Haneil Larson, Dsouza, Viola, Dube, John, Dumith, Samuel C, Duncan, Bruce B, Duraes, Andre Rodrigues, Duraisamy, Senbagam, Durojaiye, Oyewole Christopher, Dzianach, Paulina Agnieszka, Dziedzic, Arkadiusz Marian, Eboreime, Ejemai, Ebrahimi, Alireza, Edinur, Hisham Atan, Edvardsson, David, Eikemo, Terje Andreas, Eini, Ebrahim, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, El Sayed, Iman, El Tantawi, Maha, Elbarazi, Iffat, Elemam, Noha Mousaad, ElGohary, Ghada Metwally Tawfik, Elhadi, Muhammed, Elmeligy, Omar Abdelsadek Abdou, ELNahas, Gihan, Elshaer, Mohammed, Elsohaby, Ibrahim, Engelbert Bain, Luchuo, Erkhembayar, Ryenchindorj, Eshrati, Babak, Estep, Kara, Fabin, Natalia, Fagbamigbe, Adeniyi Francis, Falzone, Luca, Fareed, Mohammad, Farinha, Carla Sofia e Sá, Faris, MoezAlIslam Ezzat Mahmoud, Faro, Andre, Farrokhi, Pegah, Fatehizadeh, Ali, Fauk, Nelsensius Klau, Feigin, Valery L, Feng, Xiaoqi, Fereshtehnejad, Seyed-Mohammad, Feroze, Abdullah Hamid, Ferreira, Nuno, Ferreira, Paulo H, Fischer, Florian, Flavel, Joanne, Flood, David, Flor, Luisa S, Foigt, Nataliya A, Folayan, Morenike Oluwatoyin, Force, Lisa M, Fortuna, Daniela, Foschi, Matteo, Franklin, Richard Charles, Freitas, Alberto, Fukumoto, Takeshi, Furtado, João M, Gaal, Peter Andras, Gadanya, Muktar A, Gaidhane, Abhay Motiramji, Gaihre, Santosh, Galali, Yaseen, Ganbat, Mandukhai, Gandhi, Aravind P, Ganesan, Balasankar, Ganie, Mohd Ashraf, Ganiyani, Mohammad Arfat, Gardner, William M, Gebi, Tilaye Gebru, Gebregergis, Miglas W, Gebrehiwot, Mesfin, Gebremariam, Tesfay B B, Gebremeskel, Teferi Gebru, Gela, Yibeltal Yismaw, Georgescu, Simona Roxana, Getachew Obsa, Abera, Gething, Peter W, Getie, Molla, Ghadiri, Keyghobad, Ghadirian, Fataneh, Ghailan, Khalid Yaser, Ghajar, Alireza, Ghasemi, MohammadReza, Ghasempour Dabaghi, Ghazal, Ghasemzadeh, Afsaneh, Ghazy, Ramy Mohamed, Gholamrezanezhad, Ali, Ghorbani, Mahsa, Ghotbi, Elena, Gibson, Ruth Margaret, Gill, Tiffany K, Ginindza, Themba G, Girmay, Alem, Glasbey, James C, Göbölös, Laszlo, Godinho, Myron Anthony, Goharinezhad, Salime, Goldust, Mohamad, Golechha, Mahaveer, Goleij, Pouya, Gona, Philimon N, Gorini, Giuseppe, Goulart, Alessandra C, Grada, Ayman, Grivna, Michal, Guan, Shi-Yang, Guarducci, Giovanni, Gubari, Mohammed Ibrahim Mohialdeen, Gudeta, Mesay Dechasa, Guha, Avirup, Guicciardi, Stefano, Gulati, Snigdha, Gulisashvili, David, Gunawardane, Damitha Asanga, Guo, Cui, Gupta, Anish Kumar, Gupta, Bhawna, Gupta, Ishita, Gupta, Mohak, Gupta, Rajeev, Gupta, Veer Bala, Gupta, Vijai Kumar, Gupta, Vivek Kumar, Gutiérrez, Reyna Alma, Habibzadeh, Farrokh, Habibzadeh, Parham, Haddadi, Rasool, Hadi, Najah R, Haep, Nils, Hafezi-Nejad, Nima, Hafiz, Abdul, Hagins, Hailey, Halboub, Esam S, Halimi, Aram, Haller, Sebastian, Halwani, Rabih, Hamilton, Erin B, Hankey, Graeme J, Hannan, Md Abdul, Haque, Md Nuruzzaman, Harapan, Harapan, Haro, Josep Maria, Hartvigsen, Jan, Hasaballah, Ahmed I, Hasan, Ikramul, Hasanian, Mohammad, Hasnain, Md Saquib, Hassan, Amr, Haubold, Johannes, Havmoeller, Rasmus J, Hay, Simon I, Hayat, Khezar, Hebert, Jeffrey J, Hegazi, Omar E, Heidari, Golnaz, Helfer, Bartosz, Hemmati, Mehdi, Hendrie, Delia, Henson, Claire A, Hezam, Kamal, Hiraike, Yuta, Hoan, Nguyen Quoc, Holla, Ramesh, Hon, Julia, Hossain, Md Mahbub, Hosseinzadeh, Hassan, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hsu, Johnathan M, Huang, Junjie, Hugo, Fernando N, Hushmandi, Kiavash, Hussain, Javid, Hussein, Nawfal R, Huynh, Chantal K, Huynh, Hong-Han, Hwang, Bing-Fang, Iannucci, Vincent C, Ihler, Audrey L, Ikiroma, Adalia I, Ikuta, Kevin S, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Imam, Mohammad Tarique, Immurana, Mustapha, Irham, Lalu Muhammad, Islam, Md Rabiul, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ismail, Faisal, Ismail, Nahlah Elkudssiah, Isola, Gaetano, Iwagami, Masao, Iwu, Chidozie C D, Iyer, Mahalaxmi, Jaafari, Jalil, Jacobsen, Kathryn H, Jadidi-Niaragh, Farhad, Jafarinia, Morteza, Jaggi, Khushleen, Jahankhani, Kasra, Jahanmehr, Nader, Jahrami, Haitham, Jain, Akhil, Jain, Nityanand, Jairoun, Ammar Abdulrahman, Jaiswal, Abhishek, Jakovljevic, Mihajlo, Jatau, Abubakar Ibrahim, Javadov, Sabzali, Javaheri, Tahereh, Jayapal, Sathish Kumar, Jayaram, Shubha, Jee, Sun Ha, Jeganathan, Jayakumar, Jeyakumar, Angeline, Jha, Anil K, Jiang, Heng, Jin, Yinzi, Jonas, Jost B, Joo, Tamas, Joseph, Abel, Joseph, Nitin, Joshua, Charity Ehimwenma, Jozwiak, Jacek Jerzy, Jürisson, Mikk, K, Vaishali, Kaambwa, Billingsley, Kabir, Ali, Kabir, Zubair, Kadashetti, Vidya, Kalani, Rizwan, Kalankesh, Leila R, Kaliyadan, Feroze, Kalra, Sanjay, Kamenov, Kaloyan, Kamyari, Naser, Kanagasabai, Thanigaivelan, Kandel, Himal, Kanmanthareddy, Arun R, Kanmodi, Kehinde Kazeem, Kantar, Rami S, Karaye, Ibraheem M, Karim, Asima, Karimi, Salah Eddin, Karimi, Yeganeh, Kasraei, Hengameh, Kassel, Molly B, Kauppila, Joonas H, Kawakami, Norito, Kayode, Gbenga A, Kazemi, Foad, Kazemian, Sina, Keikavoosi-Arani, Leila, Keller, Cathleen, Kempen, John H, Kerr, Jessica A, Keshtkar, Kamyab, Kesse-Guyot, Emmanuelle, Keykhaei, Mohammad, Khajuria, Himanshu, Khalaji, Amirmohammad, Khalid, Asaad, Khalid, Nauman, Khalilian, Alireza, Khamesipour, Faham, Khan, Asaduzzaman, Khan, Ikramullah, Khan, Maseer, Khan, Moien AB, Khanmohammadi, Shaghayegh, Khatab, Khaled, Khatami, Fatemeh, Khatatbeh, Moawiah Mohammad, Khater, Amir M, Khayat Kashani, Hamid Reza, Khidri, Feriha Fatima, Khodadoust, Elaheh, Khormali, Moein, Khorrami, Zahra, Kifle, Zemene Demelash, Kim, Min Seo, Kimokoti, Ruth W, Kisa, Adnan, Kisa, Sezer, Knudsen, Ann Kristin Skrindo, Kocarnik, Jonathan M, Kochhar, Sonali, Koh, Hyun Yong, Kolahi, Ali-Asghar, Kompani, Farzad, Koren, Gerbrand, Korzh, Oleksii, Kosen, Soewarta, Koulmane Laxminarayana, Sindhura Lakshmi, Krishan, Kewal, Krishna, Varun, Krishnamoorthy, Vijay, Kuate Defo, Barthelemy, Kuddus, Md Abdul, Kuddus, Mohammed, Kuitunen, Ilari, Kulkarni, Vishnutheertha, Kumar, Manasi, Kumar, Nithin, Kumar, Rakesh, Kurmi, Om P, Kusuma, Dian, Kyu, Hmwe Hmwe, La Vecchia, Carlo, Lacey, Ben, Ladan, Muhammad Awwal, Laflamme, Lucie, Lafranconi, Alessandra, Lahariya, Chandrakant, Lai, Daphne Teck Ching, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lám, Judit, Lan, Qing, Lan, Tuo, Landires, Iván, Lanfranchi, Francesco, Langguth, Berthold, Laplante-Lévesque, Ariane, Larijani, Bagher, Larsson, Anders O, Lasrado, Savita, Lauriola, Paolo, Le, Huu-Hoai, Le, Long Khanh Dao, Le, Nhi Huu Hanh, Le, Trang Diep Thanh, Leasher, Janet L, Ledda, Caterina, Lee, Munjae, Lee, Paul H, Lee, Sang-woong, Lee, Seung Won, Lee, Wei-Chen, Lee, Yo Han, LeGrand, Kate E, Lenzi, Jacopo, Leong, Elvynna, Leung, Janni, Li, Ming-Chieh, Li, Wei, Li, Xiaopan, Li, Yichong, Li, Yongze, Lim, Lee-Ling, Lim, Stephen S, Lindstrom, Megan, Linn, Shai, Liu, Gang, Liu, Runben, Liu, Shiwei, Liu, Wei, Liu, Xiaofeng, Liu, Xuefeng, Llanaj, Erand, Lo, Chun-Han, López-Bueno, Rubén, Loreche, Arianna Maever, Lorenzovici, László, Lozano, Rafael, Lubinda, Jailos, Lucchetti, Giancarlo, Lunevicius, Raimundas, Lusk, Jay B, lv, hengliang, Ma, Zheng Feei, Machairas, Nikolaos, Madureira-Carvalho, Áurea M, Magaña Gómez, Javier A, Maghazachi, Azzam A, Maharjan, Preeti, Mahasha, Phetole Walter, Maheri, Mina, Mahjoub, Soleiman, Mahmoud, Mansour Adam, Mahmoudi, Elham, Majeed, Azeem, Makris, Konstantinos Christos, Malakan Rad, Elaheh, Malhotra, Kashish, Malik, Ahmad Azam, Malik, Iram, Malta, Deborah Carvalho, Manla, Yosef, Mansour, Ali, Mansouri, Pejman, Mansournia, Mohammad Ali, Mantilla Herrera, Ana M, Mantovani, Lorenzo Giovanni, Manu, Emmanuel, Marateb, Hamid Reza, Mardi, Parham, Martinez, Gabriel, Martinez-Piedra, Ramon, Martini, Daniela, Martins-Melo, Francisco Rogerlândio, Martorell, Miquel, Marx, Wolfgang, Maryam, Sharmeen, Marzo, Roy Rillera, Mathangasinghe, Yasith, Mathieson, Stephanie, Mathioudakis, Alexander G, Mattumpuram, Jishanth, Maugeri, Andrea, Mayeli, Mahsa, Mazidi, Mohsen, Mazzotti, Antonio, McGrath, John J, 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Theo, and Murray, Christopher J L
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8. New International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) Open-Source Model Framework for the Health Technology Assessment of Early Alzheimer’s Disease Treatment: Development and Use Cases
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Handels, Ron, Herring, William L., Grimm, Sabine, Sköldunger, Anders, Winblad, Bengt, Wimo, Anders, and Jönsson, Linus
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9. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Massimiliano, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafañe, Jorge Hugo, Violante, Francesco S, Vlassov, Vasily, Vollset, Stein Emil, Volovat, Simona Ruxandra, Vongpradith, Avina, Waheed, Yasir, Wang, Cong, Wang, Fang, Wang, Ning, Wang, Shu, Wang, Yanzhong, Wang, Yuan-Pang, Ward, Paul, Wassie, Emebet Gashaw, Weaver, Marcia R, Weerakoon, Kosala Gayan, Weintraub, Robert G, Weiss, Daniel J, Weldemariam, Abrha Hailay, Wells, Katherine M, Wen, Yi Feng, Whisnant, Joanna L, Whiteford, Harvey A, Wiangkham, Taweewat, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Wilandika, Angga, Wilkerson, Caroline, Willeit, Peter, Wimo, Anders, Woldegebreal, Demewoz H, Wolf, Axel Walter, Wong, Yen Jun, Woolf, Anthony D, Wu, Chenkai, Wu, Felicia, Wu, Xinsheng, Wu, Zenghong, Wulf Hanson, Sarah, Xia, Yanjie, Xiao, Hong, Xu, Xiaoyue, Xu, Yvonne Yiru, Yadav, Lalit, Yadollahpour, Ali, Yaghoubi, Sajad, Yamagishi, Kazumasa, Yang, Lin, Yano, Yuichiro, Yao, Yao, Yaribeygi, Habib, Yazdanpanah, Mohammad Hosein, Ye, Pengpeng, Yehualashet, Sisay Shewasinad, Yesuf, Subah Abderehim, Yezli, Saber, Yiğit, Arzu, Yiğit, Vahit, Yigzaw, Zeamanuel Anteneh, Yismaw, Yazachew, Yon, Dong Keon, Yonemoto, Naohiro, Younis, Mustafa Z, Yu, Chuanhua, Yu, Yong, Yusuf, Hadiza, Zahid, Mondal Hasan, Zakham, Fathiah, Zaki, Leila, Zaki, Nazar, Zaman, Burhan Abdullah, Zamora, Nelson, Zand, Ramin, Zandieh, Ghazal G Z, Zar, Heather J, Zarrintan, Armin, Zastrozhin, Mikhail Sergeevich, Zhang, Haijun, Zhang, Ning, Zhang, Yunquan, Zhao, Hanqing, Zhong, Chenwen, Zhong, Panliang, Zhou, Juexiao, Zhu, Zhaohua, Ziafati, Makan, Zielińska, Magdalena, Zimsen, Stephanie R M, Zoladl, Mohammad, Zumla, Alimuddin, Zyoud, Samer H, Vos, Theo, and Murray, Christopher J L
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- 2024
10. Validation of the Health Assessment Tool (HAT) based on four aging cohorts from the Swedish National study on Aging and Care
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Abbadi, Ahmad, primary, Kokoroskos, Emmanouil, additional, Stamets, Matthew, additional, Vetrano, Davide L., additional, Orsini, Nicola, additional, Elmståhl, Sölve, additional, Fagerström, Cecilia, additional, Wimo, Anders, additional, Sköldunger, Anders, additional, Berglund, Johan Sanmartin, additional, Olsson, Christina B., additional, Wachtler, Caroline, additional, Fratiglioni, Laura, additional, and Calderón-Larrañaga, Amaia, additional
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- 2024
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11. Slovenian Memory Clinic Organization with the Introduction of Potential New Alzheimer’s Disease Treatment
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Zupanic, Eva, primary, Emersic, Andreja, additional, Wimo, Anders, additional, Winblad, Bengt, additional, Speh, Andreja, additional, and Kramberger, Milica Gregoric, additional
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- 2024
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12. Validation of the Health Assessment Tool (HAT) based on four aging cohorts from the Swedish National study on Aging and Care
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Abbadi, Ahmad, Kokoroskos, Emmanouil, Stamets, Matthew, Vetrano, Davide L., Orsini, Nicola, Elmståhl, Sölve, Fagerström, Cecilia, Wimo, Anders, Sköldunger, Anders, Sanmartin Berglund, Johan, Olsson, Christina B., Wachtler, Caroline, Fratiglioni, Laura, Calderón-Larrañaga, Amaia, Abbadi, Ahmad, Kokoroskos, Emmanouil, Stamets, Matthew, Vetrano, Davide L., Orsini, Nicola, Elmståhl, Sölve, Fagerström, Cecilia, Wimo, Anders, Sköldunger, Anders, Sanmartin Berglund, Johan, Olsson, Christina B., Wachtler, Caroline, Fratiglioni, Laura, and Calderón-Larrañaga, Amaia
- Abstract
Background: As global aging accelerates, routinely assessing the functional status and morbidity burden of older patients becomes paramount. The aim of this study is to assess the validity of the comprehensive clinical and functional Health Assessment Tool (HAT) based on four cohorts of older adults (60 + years) from the Swedish National study on Aging and Care (SNAC) spanning urban, suburban, and rural areas. Methods: The HAT integrates five health indicators (gait speed, global cognition, number of chronic diseases, and basic and instrumental activities of daily living), providing an individual-level score between 0 and 10. The tool was constructed using nominal response models, first separately for each cohort and then in a harmonized dataset. Outcomes included all-cause mortality over a maximum follow-up of 16 years and unplanned hospital admissions over a maximum of 3 years of follow-up. The predictive capacity was assessed through the area under the curve (AUC) using logistic regressions. For time to death, Cox regressions were performed, and Harrell’s C-indices were reported. Results from the four cohorts were pooled using individual participant data meta-analysis and compared with those from the harmonized dataset. Results: The HAT demonstrated high predictive capacity across all cohorts as well as in the harmonized dataset. In the harmonized dataset, the AUC was 0.84 (95% CI 0.81–0.87) for 1-year mortality, 0.81 (95% CI 0.80–0.83) for 3-year mortality, 0.80 (95% CI 0.79–0.82) for 5-year mortality, 0.69 (95% CI 0.67–0.70) for 1-year unplanned admissions, and 0.69 (95% CI 0.68–0.70) for 3-year unplanned admissions. The Harrell’s C for time-to-death throughout 16 years of follow-up was 0.75 (95% CI 0.74–0.75). Conclusions: The HAT is a highly predictive, clinically intuitive, and externally valid instrument with potential for better addressing older adults’ health needs and optimizing risk stratification at the population level. © The Author(s) 2024., SNAC, NEAR
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- 2024
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13. Integrating a multimodal lifestyle intervention with medical food in prodromal Alzheimer’s disease : the MIND-ADmini randomized controlled trial
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Thunborg, Charlotta, Wang, Rui, Rosenberg, Anna, Sindi, Shireen, Andersen, Pia, Andrieu, Sandrine, Broersen, Laus M., Coley, Nicola, Couderc, Celine, Duval, Celine Z., Faxen-Irving, Gerd, Hagman, Göran, Hallikainen, Merja, Håkansson, Krister, Kekkonen, Eija, Lehtisalo, Jenni, Levak, Nicholas, Mangialasche, Francesca, Pantel, Johannes, Rydström, Anders, Stigsdotter Neely, Anna, Wimo, Anders, Ngandu, Tiia, Soininen, Hilkka, Hartmann, Tobias, Solomon, Alina, Kivipelto, Miia, Thunborg, Charlotta, Wang, Rui, Rosenberg, Anna, Sindi, Shireen, Andersen, Pia, Andrieu, Sandrine, Broersen, Laus M., Coley, Nicola, Couderc, Celine, Duval, Celine Z., Faxen-Irving, Gerd, Hagman, Göran, Hallikainen, Merja, Håkansson, Krister, Kekkonen, Eija, Lehtisalo, Jenni, Levak, Nicholas, Mangialasche, Francesca, Pantel, Johannes, Rydström, Anders, Stigsdotter Neely, Anna, Wimo, Anders, Ngandu, Tiia, Soininen, Hilkka, Hartmann, Tobias, Solomon, Alina, and Kivipelto, Miia
- Abstract
Background: The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) showed cognitive benefits from a multidomain lifestyle intervention in at-risk older people. The LipiDiDiet trial highlighted benefits of medical food in prodromal Alzheimer’s disease (AD). However, the feasibility and impact of multimodal interventions combining lifestyle with medical food in prodromal AD is unclear. Methods: MIND-ADmini was a 6-month multinational (Sweden, Finland, Germany, France) proof-of-concept randomized controlled trial (RCT). Participants were 60–85 years old, had prodromal AD (International Working Group-1 criteria), and vascular/lifestyle risk factors. The parallel-group RCT had three arms: multimodal lifestyle intervention (nutritional guidance, exercise, cognitive training, vascular/metabolic risk management and social stimulation); multimodal lifestyle intervention + medical food (Fortasyn Connect); and regular health advice/care (control). Participants were randomized 1:1:1 (computer-generated allocation at each site). Outcome evaluators were blinded to randomization. Primary outcome was feasibility of the multimodal intervention, evaluated by recruitment rate during a 6-month recruitment phase, overall adherence in each intervention arm, and 6-month retention rate. Successful adherence was pre-specified as attending ≥ 40% of sessions/domain in ≥ 2/4 domains (lifestyle intervention), and consuming ≥ 60% of the medical food (lifestyle intervention + medical food). The secondary outcomes included adherence/participation to each intervention component and overall adherence to healthy lifestyle changes, measured using a composite score for healthy lifestyle. Cognitive assessments were included as exploratory outcomes, e.g. Clinical Dementia Rating scale. Results: During September 2017-May 2019, 93 individuals were randomized (32 lifestyle intervention, 31 lifestyle + medical food, and 30 control group). Overall recruitment rate was
- Published
- 2024
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14. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Shahid, W, Shahwan, MJ, Shaikh, MA, Shakeri, A, Shalash, AS, Sham, S, Shamim, MA, Shamshirgaran, MA, Shamsi, MA, Shanawaz, M, Shankar, A, Shannawaz, M, Sharath, M, Sharifan, A, Sharifi-Rad, J, Sharma, M, Sharma, R, Sharma, S, Sharma, U, Sharma, V, Shastry, RP, Shavandi, A, Shayan, AM, Shayan, M, Shehabeldine, AME, Shetty, PH, Shibuya, K, Shifa, JE, Shiferaw, D, Shiferaw, WS, Shigematsu, M, Shiri, R, Shitaye, NA, Shittu, A, Shivakumar, KM, Shivarov, V, Shokati Eshkiki, Z, Shool, S, Shrestha, S, Shuval, K, Sibhat, MM, Siddig, EE, Sigfusdottir, ID, Silva, DAS, Silva, JP, Silva, LMLR, Silva, S, Simpson, CR, Singal, A, Singh, A, Singh, BB, Singh, H, Singh, JA, Singh, M, Singh, P, Skou, ST, Sleet, DA, Slepak, ELN, Solanki, R, Soliman, SSM, Song, S, Song, Y, Sorensen, RJD, Soriano, JB, Soyiri, IN, Spartalis, M, Sreeramareddy, CT, Stark, BA, Starodubova, AV, Stein, C, Stein, DJ, Steiner, C, Steiner, TJ, Steinmetz, JD, Steiropoulos, P, Stockfelt, L, Stokes, MA, Subedi, NS, Subramaniyan, V, Suemoto, CK, Suleman, M, Suliankatchi Abdulkader, R, Sultana, A, Sundström, J, Swain, CK, Szarpak, L, Tabaee Damavandi, P, Tabarés-Seisdedos, R, Tabatabaei Malazy, O, Tabatabaeizadeh, S-A, Tabatabai, S, Tabche, C, Tabish, M, Tadakamadla, SK, Taheri Abkenar, Y, Taheri Soodejani, M, Taherkhani, A, Taiba, J, Talaat, IM, Talukder, A, Tampa, M, Tamuzi, JL, Tan, K-K, Tandukar, S, Tang, H, Tavakoli Oliaee, R, Tavangar, SM, Teimoori, M, Temsah, M-H, Teramoto, M, Thangaraju, P, Thankappan, KR, Thapar, R, Thayakaran, R, Thirunavukkarasu, S, Thomas, N, Thomas, NK, Thum, CCC, Tichopad, A, Ticoalu, JHV, Tillawi, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Torre, AE, Touvier, M, Tovani-Palone, MR, Tran, JT, Tran, MTN, Tran, NM, Tran, N-H, Trico, D, Tromans, SJ, Truyen, TTTT, Tsatsakis, A, Tsegay, GM, Tsermpini, EE, Tumurkhuu, M, Tyrovolas, S, Udoh, A, Umair, M, Umakanthan, S, Umar, TP, Undurraga, EA, Unim, B, Unnikrishnan, B, Unsworth, CA, Upadhyay, E, Urso, D, Usman, JS, Vahabi, SM, Vaithinathan, AG, Van den Eynde, J, Varga, O, Varma, RP, Vart, P, Vasankari, TJ, Vasic, M, Vaziri, S, Vellingiri, B, Venketasubramanian, N, Veroux, M, Verras, G-I, Vervoort, D, Villafañe, JH, Violante, FS, Vlassov, V, Vollset, SE, Volovat, SR, Vongpradith, A, Waheed, Y, Wang, C, Wang, F, Wang, N, Wang, S, Wang, Y, Wang, Y-P, Ward, P, Wassie, EG, Weaver, MR, Weerakoon, KG, Weintraub, RG, Weiss, DJ, Weldemariam, AH, Wells, KM, Wen, YF, Whisnant, JL, Whiteford, HA, Wiangkham, T, Wickramasinghe, DP, Wickramasinghe, ND, Wilandika, A, Wilkerson, C, Willeit, P, Wimo, A, Woldegebreal, DH, Wolf, AW, Wong, YJ, Woolf, AD, Wu, C, Wu, F, Wu, X, Wu, Z, Wulf Hanson, S, Xia, Y, Xiao, H, Xu, X, Xu, YY, Yadav, L, Yadollahpour, A, Yaghoubi, S, Yamagishi, K, Yang, L, Yano, Y, Yao, Y, Yaribeygi, H, Yazdanpanah, MH, Ye, P, Yehualashet, SS, Yesuf, SA, Yezli, S, Yiğit, A, Yiğit, V, Yigzaw, ZA, Yismaw, Y, Yon, DK, Yonemoto, N, Younis, MZ, Yu, C, Yu, Y, Yusuf, H, Zahid, MH, Zakham, F, Zaki, L, Zaki, N, Zaman, BA, Zamora, N, Zand, R, Zandieh, GGZ, Zar, HJ, Zarrintan, A, Zastrozhin, MS, Zhang, H, Zhang, N, Zhang, Y, Zhao, H, Zhong, C, Zhong, P, Zhou, J, Zhu, Z, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoladl, M, Zumla, A, Zyoud, SH, Vos, T, and Murray, CJL
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- 2024
15. Costs of diagnosing early Alzheimer's disease in three European memory clinic settings: Results from the precision medicine in Alzheimer's disease project.
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Wimo, Anders, Kirsebom, Bjørn‐Eivind, Timón‐Reina, Santiago, Vromen, Ellen, Selnes, Per, Bon, Jaka, Emersic, Andreja, Kramberger, Milica Gregoric, Speh, Andreja, Visser, Pieter Jelle, Winblad, Bengt, and Fladby, Tormod
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ALZHEIMER'S disease diagnosis , *CEREBROSPINAL fluid examination , *COST effectiveness , *COGNITIVE testing , *RESEARCH funding , *MAGNETIC resonance imaging , *POSITRON emission tomography , *DESCRIPTIVE statistics , *APOLIPOPROTEINS , *EARLY diagnosis , *INDIVIDUALIZED medicine , *CONFIDENCE intervals , *MEDICAL care costs , *BIOMARKERS - Abstract
Objectives: The implementation of disease‐modifying treatments for Alzheimer's Disease (AD) will require cost‐effective diagnostic processes. As part of The Precision Medicine In AD consortium (PMI‐AD) project, the aim is to analyze the baseline costs of diagnosing early AD at memory clinics in Norway, Slovenia, and the Netherlands. Methods: The costs of cognitive testing and a clinical examination, apolipoprotein E, magnetic resonance imaging (MRI), cerebrospinal fluid (CSF), positron emission tomography and blood‐based biomarkers (BBM), which are used in different combinations in the three countries, were analyzed. Standardized unit costs, adjusted for GDP per capita and based on Swedish conditions were applied. The costs were expressed in euros (€) as of 2019. A diagnostic set comprising clinical examination, cognitive testing, MRI and CSF was defined as the gold standard, with MRI mainly used as an exclusion filter. Results: Cost data were available for 994 persons in Norway, 169 in Slovenia and 1015 in the Netherlands. The mean diagnostic costs were 1478 (95% confidence interval 1433–1523) € in Norway, 851 (731–970) € in Slovenia and 1184 (1135–1232) € in the Netherlands. Norway had the highest unit costs but also the greatest use of tests. With a uniform diagnostic test set applied, the diagnostic costs were 1264 (1238–1291) €, in Norway, 843 (771–914) € in Slovenia and 1184 (1156–1213) € in the Netherlands. There were no major cost differences between the final set of diagnoses. Conclusions: The total costs for setting a diagnosis of AD varied somewhat in the three countries, depending on unit costs and use of tests. These costs are relatively low in comparison to the societal costs of AD. Key points: The introduction of blood‐based biomarkers for detecting Alzheimer's Disease (AD) can change the diagnostic process.Given the expected demands for treatment of cognitive disorders such as AD, the costs and capacity of the diagnostic work‐up are of great importance for care funders and planners.Our study incorporating diagnostic costs from three distinct European regions provides valuable inputs for cost‐effectiveness studies. [ABSTRACT FROM AUTHOR]
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- 2024
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16. People get ready! A new generation of Alzheimer's therapies may require new ways to deliver and pay for healthcare.
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Wahlberg, Karin, Winblad, Bengt, Cole, Amanda, Herring, William L., Ramsberg, Joakim, Torontali, Ilona, Visser, Pieter‐Jelle, Wimo, Anders, Wollaert, Lieve, and Jönsson, Linus
- Abstract
The development of disease‐modifying therapies (DMTs) for Alzheimer's disease (AD) has progressed over the last decade, and the first‐ever therapies with potential to slow the progression of disease are approved in the United States. AD DMTs could provide life‐changing opportunities for people living with this disease, as well as for their caregivers. They could also ease some of the immense societal and economic burden of dementia. However, AD DMTs also come with major challenges due to the large unmet medical need, high prevalence of AD, new costs related to diagnosis, treatment and monitoring, and uncertainty in the therapies' actual clinical value. This perspective article discusses, from the broad perspective of various health systems and stakeholders, how we can overcome these challenges and improve society's readiness for AD DMTs. We propose that innovative payment models such as performance‐based payments, in combination with learning healthcare systems, could be the way forward to enable timely patient access to treatments, improve accuracy of cost‐effectiveness evaluations and overcome budgetary barriers. Other important considerations include the need for identification of key drivers of patient value, the relevance of different economic perspectives (i.e. healthcare vs. societal) and ethical questions in terms of treatment eligibility criteria. [ABSTRACT FROM AUTHOR]
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- 2024
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17. Predicting sojourn times across dementia disease stages, institutionalization, and mortality.
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Tate, Ashley E, Bouteloup, Vincent, van Maurik, Ingrid S., Jean, Delphine, Mank, Arenda, Speh, Andreja, Boilet, Valerie, van Harten, Argonde, Eriksdotter, Maria, Wimo, Anders, Dufouil, Carole, van der Flier, Wiesje M., and Jönsson, Linus
- Abstract
INTRODUCTION: Inferring the timeline from mild cognitive impairment (MCI) to severe dementia is pivotal for patients, clinicians, and researchers. Literature is sparse and often contains few patients. We aim to determine the time spent in MCI, mild‐, moderate‐, severe dementia, and institutionalization until death. METHODS: Multistate modeling with Cox regression was used to obtain the sojourn time. Covariates were age at baseline, sex, amyloid status, and Alzheimer's disease (AD) or other dementia diagnosis. The sample included a register (SveDem) and memory clinics (Amsterdam Dementia Cohort and Memento). RESULTS: Using 80,543 patients, the sojourn time from clinically identified MCI to death across all patient groups ranged from 6.20 (95% confidence interval [CI]: 5.57–6.98) to 10.08 (8.94–12.18) years. DISCUSSION: Generally, sojourn time was inversely associated with older age at baseline, males, and AD diagnosis. The results provide key estimates for researchers and clinicians to estimate prognosis. [ABSTRACT FROM AUTHOR]
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- 2024
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18. Die SERAD Studie: Galantamin verbessert die Kognition bei Heimpatienten mit schwerer Alzheimerdemenz
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Burns, A, Ibach, B, Bernabei, R, Bullock, R, Cruz Jentoft, A.J, Frölich, L, Hock, C, Triau, E, Vandewoude, M, Wimo, A, Came, E, van Baelen, B, van Oene, J, and Schwalen, S
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- 2024
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19. IPECAD Modeling Workshop 2023 Cross Comparison Challenge on Cost-Effectiveness Models in Alzheimer's Disease.
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Handels R, Herring WL, Kamgar F, Aye S, Tate A, Green C, Gustavsson A, Wimo A, Winblad B, Sköldunger A, Raket LL, Stellick CB, Spackman E, Hlávka J, Wei Y, Mar J, Soto-Gordoa M, de Kok I, Brück C, Anderson R, Pemberton-Ross P, Urbich M, and Jönsson L
- Abstract
Objectives: Decision-analytic models assessing the value of emerging Alzheimer's disease (AD) treatments are challenged by limited evidence on short-term trial outcomes and uncertainty in extrapolating long-term patient-relevant outcomes. To improve understanding and foster transparency and credibility in modeling methods, we cross-compared AD decision models in a hypothetical context of disease-modifying treatment for mild cognitive impairment (MCI) due to AD., Methods: A benchmark scenario (US setting) was used with target population MCI due to AD and a set of synthetically generated hypothetical trial efficacy estimates. Treatment costs were excluded. Model predictions (10-year horizon) were assessed and discussed during a 2-day workshop., Results: Nine modeling groups provided model predictions. Implementation of treatment effectiveness varied across models based on trial efficacy outcome selection (CDR-SB, CDR-global, MMSE, FAQ) and analysis method (observed severity transitions, change from baseline, progression hazard ratio, or calibration to these). Predicted mean time in MCI ranged from 2.6-5.2 years for control strategy, and from 0.1-1.0 years for difference between intervention and control strategies. Predicted quality-adjusted life-year gains ranged from 0.0-0.6 and incremental costs (excluding treatment costs) from -US$66,897 to US$11,896., Conclusions: Trial data can be implemented in different ways across health-economic models leading to large variation in model predictions. We recommend 1) addressing the choice of outcome measure and treatment effectiveness assumptions in sensitivity analysis, 2) a standardized reporting table for model predictions, and 3) exploring the use of registries for future AD treatments measuring long-term disease progression to reduce uncertainty of extrapolating short-term trial results by health economic models., (Copyright © 2024. Published by Elsevier Inc.)
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- 2024
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20. Prevention of dementia using mobile phone applications (PRODEMOS): a multinational, randomised, controlled effectiveness-implementation trial.
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Moll van Charante EP, Hoevenaar-Blom MP, Song M, Andrieu S, Barnes L, Birck C, Brooks R, Coley N, Eggink E, Georges J, Hafdi M, van Gool WA, Handels R, Hou H, Lyu J, Niu Y, Song L, Wang W, Wang Y, Wimo A, Yu Y, Zhang J, Zhang W, Brayne C, Wang W, and Richard E
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- Humans, Male, Female, Aged, Middle Aged, China epidemiology, United Kingdom epidemiology, Risk Factors, Dementia prevention & control, Dementia epidemiology, Telemedicine, Mobile Applications
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Background: The expected increase of dementia prevalence in the coming decades will mainly be in low-income and middle-income countries and in people with low socioeconomic status in high-income countries. This study aims to reduce dementia risk factors in underserved populations at high-risk using a coach-supported mobile health (mHealth) intervention., Methods: This open-label, blinded endpoint, hybrid effectiveness-implementation randomised controlled trial (RCT) investigated whether a coach-supported mHealth intervention can reduce dementia risk in people aged 55-75 years of low socioeconomic status in the UK or from the general population in China with at least two dementia risk factors. The primary effectiveness outcome was change in cardiovascular risk factors, ageing, and incidence of dementia (CAIDE) risk score from baseline to after 12-18 months of intervention. Implementation outcomes were coverage, adoption, sustainability, appropriateness, acceptability, fidelity, feasibility, and costs assessed using a mixed-methods approach. All participants with complete data on the primary outcome, without imputation of missing outcomes were included in the analysis (intention-to-treat principle). This trial is registered with ISRCTN, ISRCTN15986016, and is completed., Findings: Between Jan 15, 2021, and April 18, 2023, 1488 people (601 male and 887 female) were randomly assigned (734 to intervention and 754 to control), with 1229 (83%) of 1488 available for analysis of the primary effectiveness outcome. After a mean follow-up of 16 months (SD 2·5), the mean CAIDE score improved 0·16 points in the intervention group versus 0·01 in the control group (mean difference -0·16, 95% CI -0·29 to -0·03). 1533 (10%) invited individuals responded; of the intervention participants, 593 (81%) of 734 adopted the intervention and 367 (50%) of 734 continued active participation throughout the study. Perceived appropriateness (85%), acceptability (81%), and fidelity (79%) were good, with fair overall feasibility (53% of intervention participants and 58% of coaches), at low cost. No differences in adverse events between study arms were found., Interpretation: A coach-supported mHealth intervention is modestly effective in reducing dementia risk factors in those with low socioeconomic status in the UK and any socioeconomic status in China. Implementation is challenging in these populations, but those reached actively participated. Whether this intervention will result in less cognitive decline and dementia requires a larger RCT with long follow-up., Funding: EU Horizon 2020 Research and Innovation Programme and the National Key R&D Programmes of China., Translation: For the Mandarin translation of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests AW received research grants from EU IMI2 (MOPEAD), JPND (ADDITION, EURO-FINGER, PMI-AD), IHI (PROMINENT), and the Swedish VINNOVA program (PREDEM)(all paid to institution) and is licence holder of RUD-instrument (in part); outside the submitted work. RH received research grants from JPND, ZonMW, IMI, H2020 (paid to institution); received consulting fees from Lilly Nederland, iMTA, Biogen Nederlands, Biogen MA, Eisai (paid to institution); is a member of ISPOR special interest group open-source models, IPECAD modelling group and Alzheimer Europe Expert Advisory Panel (unpaid); outside the submitted work. SA received grants from EU (Institutional grant [Horizon 2020 Research and Innovation Programme agreement 779238]); Region Occitanie/Pyrénées-Méditerranée (1901175); the European Regional Development Fund (MP0022856); MSD Avenir Inspire Chairs of Excellence (Alzheimer Prevention in Occitania and Catalonia, EDENIS, KORIAN, Pfizer, and Pierre-Fabre); AXA Personal (current); Biogen Personal (2022); Roche Personal (2021); Leventis foundation (2022); ADI (2022); and has a leadership role in the French Alzheimer association (Scientific Committee); outside the submitted work. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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21. Integrating a multimodal lifestyle intervention with medical food in prodromal Alzheimer's disease: the MIND-AD mini randomized controlled trial.
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Thunborg C, Wang R, Rosenberg A, Sindi S, Andersen P, Andrieu S, Broersen LM, Coley N, Couderc C, Duval CZ, Faxen-Irving G, Hagman G, Hallikainen M, Håkansson K, Kekkonen E, Lehtisalo J, Levak N, Mangialasche F, Pantel J, Rydström A, Stigsdotter-Neely A, Wimo A, Ngandu T, Soininen H, Hartmann T, Solomon A, and Kivipelto M
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- Humans, Female, Male, Aged, Middle Aged, Aged, 80 and over, Prodromal Symptoms, Combined Modality Therapy methods, Exercise physiology, Cognitive Dysfunction therapy, Cognitive Dysfunction prevention & control, Alzheimer Disease therapy, Alzheimer Disease psychology, Life Style
- Abstract
Background: The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) showed cognitive benefits from a multidomain lifestyle intervention in at-risk older people. The LipiDiDiet trial highlighted benefits of medical food in prodromal Alzheimer's disease (AD). However, the feasibility and impact of multimodal interventions combining lifestyle with medical food in prodromal AD is unclear., Methods: MIND-AD
mini was a 6-month multinational (Sweden, Finland, Germany, France) proof-of-concept randomized controlled trial (RCT). Participants were 60-85 years old, had prodromal AD (International Working Group-1 criteria), and vascular/lifestyle risk factors. The parallel-group RCT had three arms: multimodal lifestyle intervention (nutritional guidance, exercise, cognitive training, vascular/metabolic risk management and social stimulation); multimodal lifestyle intervention + medical food (Fortasyn Connect); and regular health advice/care (control). Participants were randomized 1:1:1 (computer-generated allocation at each site). Outcome evaluators were blinded to randomization. Primary outcome was feasibility of the multimodal intervention, evaluated by recruitment rate during a 6-month recruitment phase, overall adherence in each intervention arm, and 6-month retention rate. Successful adherence was pre-specified as attending ≥ 40% of sessions/domain in ≥ 2/4 domains (lifestyle intervention), and consuming ≥ 60% of the medical food (lifestyle intervention + medical food). The secondary outcomes included adherence/participation to each intervention component and overall adherence to healthy lifestyle changes, measured using a composite score for healthy lifestyle. Cognitive assessments were included as exploratory outcomes, e.g. Clinical Dementia Rating scale., Results: During September 2017-May 2019, 93 individuals were randomized (32 lifestyle intervention, 31 lifestyle + medical food, and 30 control group). Overall recruitment rate was 76.2% (64.8% during the first 6 months). Overall 6-month retention rate was 91.4% (lifestyle intervention 87.5%; lifestyle + medical food 90.3%; control 96.7%). Domain-specific adherence in the lifestyle intervention group was 71.9% to cognitive training, 78.1% exercise, 68.8% nutritional guidance, and 81.3% vascular risk management; and in the lifestyle + medical food group, 90.3% to cognitive training, 87.1% exercise, 80.7% nutritional guidance, 87.1% vascular risk management, and 87.1% medical food. Compared with control, both intervention arms showed healthy diet improvements (βLifestyle×Time = 1.11, P = 0.038; βLifestyle+medical food×Time = 1.43, P = 0.007); the lifestyle + medical food group also showed vascular risk reduction (P = 0.043) and less cognitive-functional decline (P < 0.05, exploratory analysis). There were 5 serious adverse events (control group: 1; lifestyle intervention: 3; lifestyle + medical food: 1) unrelated to interventions., Conclusions: The multidomain lifestyle intervention, alone or combined with medical food, had good feasibility and adherence in prodromal AD. Longer-term cognitive and other health benefits should be further investigated in a larger-scale trial., Trial Registration: ClinicalTrials.gov NCT03249688., (© 2024. The Author(s).)- Published
- 2024
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22. Predicting sojourn times across dementia disease stages, institutionalization, and mortality.
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Tate AE, Bouteloup V, van Maurik IS, Jean D, Mank A, Speh A, Boilet V, van Harten A, Eriksdotter M, Wimo A, Dufouil C, van der Flier WM, and Jönsson L
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- Male, Humans, Disease Progression, Institutionalization, Alzheimer Disease complications, Dementia diagnosis, Dementia complications, Cognitive Dysfunction psychology
- Abstract
Introduction: Inferring the timeline from mild cognitive impairment (MCI) to severe dementia is pivotal for patients, clinicians, and researchers. Literature is sparse and often contains few patients. We aim to determine the time spent in MCI, mild-, moderate-, severe dementia, and institutionalization until death., Methods: Multistate modeling with Cox regression was used to obtain the sojourn time. Covariates were age at baseline, sex, amyloid status, and Alzheimer's disease (AD) or other dementia diagnosis. The sample included a register (SveDem) and memory clinics (Amsterdam Dementia Cohort and Memento)., Results: Using 80,543 patients, the sojourn time from clinically identified MCI to death across all patient groups ranged from 6.20 (95% confidence interval [CI]: 5.57-6.98) to 10.08 (8.94-12.18) years., Discussion: Generally, sojourn time was inversely associated with older age at baseline, males, and AD diagnosis. The results provide key estimates for researchers and clinicians to estimate prognosis., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2024
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23. Editorial: On the 2024 Alzheimer's Association Criteria: Still Not Ready for Clinical Use.
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Zhou RZ, Wimo A, and Winblad B
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- Humans, Alzheimer Disease diagnosis
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Competing Interests: The authors report no conflict of interest.
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- 2024
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