Evidence-based clinical guidelines generally consider single conditions, and rarely multimorbidity. We developed an evidence-based guideline for a structured care program to manage polypharmacy in multimorbidity by using a realist synthesis to update the German polypharmacy guideline including the following five methods: formal prioritization in focus groups; systematic guideline review of evidence-based multimorbidity/polypharmacy guidelines; evidence search/synthesis and recommendation development; multidisciplinary consent of recommendations; feasibility test of updated guideline. We identified the need for a better description of the target group, decision support, prioritization of medication, consideration of patient preferences and anticholinergic properties, and of healthcare interfaces. We conducted a systematic guideline review of eight guidelines and extracted and synthesized recommendations using the Ariadne principles. We also included 48 systematic reviews. We formulated and agreed upon 34 recommendations for the revised guideline. During the feasibility test, guideline use enabled 57% of GPs to identify problems, leading to medication changes in 49% and self-assessed improvement in 56% of patients. Although 58% of GPs felt that it was too long, 92% recommended it. Polypharmacy should be systematically reviewed at least annually. Patients, family members, and healthcare professionals should monitor and adjust it using prospective process validation, taking into account patient preferences and agreed treatment goals. Multimorbidity, defined as the presence of two or more simultaneous chronic health conditions in an individual, is becoming the norm in general practice . MultimoIn order to improve the care of patients with chronic diseases, health care systems worldwide have developed and implemented so-called disease management programs (DMPs). In Germany, DMPs are accessible for patients insured by the statutory health insurance. DMPs are available for chronic diseases such as asthma, COPD or diabetes and aim to improve patients’ quality of life as well as the medical care of patients as a whole . DMPs arA rising awareness of polypharmacy in general practice was the reason behind the development of the first German evidence-based guideline on polypharmacy, completed in 2013. The current paper describes how we systematically updated the evidence for this guideline based on a realist synthesis. Our objective was to develop a guideline for use in a polypharmacy management program and to take into account user and healthcare priorities, formulate recommendations for consensus with multiple stakeholders, and test its feasibility prior to authorization. By doing so, we expected to increase feasibility and user acceptance.This project is part of the EVITA project . The aim of this guideline update was to provide evidence-based decision support for a structured care program for polypharmacy in multimorbidity.To systematically update the existing guideline on polypharmacy, we performed a realist synthesis. Realist synthesis has proved themselves as a suitable approach for synthesizing evidence because it also considers why, how and under what conditions interventions work or do not work ,8. The pDefining the scope of the review;Searching and appraising the evidence;Extracting and synthesizing findings;Drawing conclusions and making recommendations ,10.A realist synthesis consists of four stages:The methods used for the planned guideline update are described in The following stakeholders were included in multiple stages of the realist synthesis: The Leitliniengruppe Hessen , which consists of general practitioners who are especially trained in pharmacotherapy and quality circle work. They have developed several GP guidelines since 1998 and were deeply consulted in the following key stages of the synthesis: definition of scope, discussion and appraisal of evidence, formulation of recommendations, discussion and interpretation of practice test results.In addition, 18 international and multidisciplinary experts  were involved in the discussion and appraisal of evidence. These experts participated in a workshop, which was part of a 2-day symposium .The developed recommendations were consented among the LLGH and authorized experts/representatives from other relevant medical disciplines/societies .To define the scope of the planned guideline update, we first carried out two focus group discussions with 30 general practitioners (GPs). Our aim was to identify key attributes for the updated guideline, the overall need for change, and further topics that should be considered in evidence searches. The focus groups were moderated by a senior researcher (C.M.), and notes from the discussions were taken and analyzed by the senior researcher (C.M.) and two research fellows (T.S.D. and B.F.). After completion of the analyses, the results were presented to and discussed with the LLGH (moderated by C.M. and I.S.), and topics for possible inclusion in the planned guideline update were formally prioritized.Identification of the target group;Decision support in de-prescribing; prioritization of medication considering patient preferences and anticholinergic properties;Medication plan and monitoring;Healthcare interfaces.During the focus groups, we recognized that the guideline structure would have to be improved in order to support its acceptance and implementation. To address topics of interest identified in the groups, we also decided to conduct a systematic review of evidence-based guidelines on multimorbidity and polypharmacy see , as wellOther key questions concerned how to collect information on patients’ medication, how to recognize medication-related risks, how to monitor symptoms, and how to avoid inappropriate medications. It was further decided not only to update but also to upgrade the existing guideline on polypharmacy from level S2e to level S3 ; S3: evidence-based and expert-consented consented guideline ) .We conducted a systematic guideline review (SGR)  with theElectronic databases were searched , Turning Research Into Practice (TRIP), Guideline International Network (G-I-N), The National Guideline Clearinghouse) using controlled terms . We did not apply any restrictions to the definition of multimorbidity or polypharmacy used in the guidelines, the publication date or to language. Guidelines or guideline-like documents were included when they contained explicit and systematically developed recommendations and had been endorsed by an official organization. Disease-specific guidelines and those with an overly narrow focus were excluded. Two independent researchers conducted the searches and selected guidelines for inclusion (T.S.D. and A.I.G.G.).Three researchers  screened the titles and abstracts of 3939 records found in the databases and on the websites of guideline issuing organizations. Sixty-three guidelines underwent full-text screening. In total, we included four international guidelines on multimorbidity ,15,16,17Four researchers  used the MiChe-Checklist to assess the quality of the guidelines ,23. OverWe searched for further evidence to help answer specific research questions identified in the focus groups and revised the medication process as the central framework of the guideline. In the search, we used forward citation tracking (PUBMED: ‘similar articles’) and selected the Cochrane Review on “Interventions to improve the appropriate use of polypharmacy in older people”  as the kIn total, the search for similar articles detected 123 systematic reviews, with a further 28 identified through snowballing. Bibliographic details on the identified studies were imported into EndNote© and uploaded to Covidence©, and duplicates were removed. Two independent reviewers (M.-S.B. and AI.G.G.) screened the titles, abstracts and full-texts, and included the systematic reviews that fulfilled the inclusion criteria presented in Forty-eight systematic reviews were included in the realist synthesis, most of which concerned interventions to optimize prescribing by, for example, raising awareness of potentially inappropriate medications, using medication reviews, eliciting patient preferences in pharmacotherapy, conducting pharmacist-led interventions, and de-prescribing where appropriate . The eviFor data extraction, we predefined an extraction framework based on the ARIADNE principles, which is a framework to guide care in multimorbid patients . RecommeAt a 2-day meeting, the results of the thematic synthesis were discussed and consented with a multidisciplinary international team of 18 experts  from seven countries . Group dData from the additionally identified systematic reviews were extracted into Excel and assigned to the following categories by one researcher (A.I.G.G.): author; year (reference); context; intervention; outcomes; results; conclusion; guideline chapter; SIGN quality appraisal.The results of the evidence syntheses were discussed with the LLGH in 24 sessions. The evidence syntheses were presented by M.-S.B., T.S.D., C.M., and the sessions moderated by I.S. Existing chapters were revised and new chapters added, whereby each chapter was broken down into “evidence and rationale” and “practice tips and tools”, based on the results of the syntheses. Additional experts were invited to contribute to specific sections of the guideline by providing information on, for example, the interface between general practice and pharmacies, or de-prescribing. Evidence-based recommendations and statements were formulated with the LLGH. References as well as levels of evidence were added to the recommendations and statements. Since recommendations have a normative character, the formulation of recommendations and statements also took into account their relevance for primary care and the transferability of international evidence to a German health care context. As a result, strong recommendations  could be based on a low level of evidence  and vice versa. The grades of recommendation used in the upgraded guideline are presented in n = 3), inventory and assessment (n = 6), coordination with the patient (n = 1), (de-)prescribing and communication (n = 12), drug dispensing (n = 3), drug use and self-management (n = 5), and monitoring and follow-up (n = 4).In total, we formulated 34 recommendations and statements, and assigned them to one of the following groups in accordance with the revised framework of the medication process see : identifSteps 1 to 3 include recommendations on medication review as a systematic process. Steps 4 (drug dispensing) and 5 (medication use/self-management) are only indirectly accessible to GPs, and step 6 (monitoring and follow-up) merges with step 1 and reflects the long-term aim of primary care.In addition to the upgraded long version of the guideline, a short version, as well as a guideline report were developed.Based on a modified version of the RAND appropriateness method, we discussed and agreed upon recommendations with 13 authorized experts from various medical disciplines including nursing and pharmacy, and a trained patient representative .In a first step, participants received the draft of the upgraded long version of the guideline, including a list of all proposed recommendations and statements. Before discussing them with the other participants, they were required to use a six-point Likert scale to rank them online . The results were made available before the consensus conference began and showed that agreement between the participants was high .In a second step, all 34 recommendations were discussed and agreement was reached at an inter-professional consensus conference. The consensus conference was moderated by an external moderator (C.M.-B.) and was held online due to the COVID-19 pandemic. Recommendations were discussed intensively by participants in the consensus conference and modified live via screen sharing. The discussion was supported by non-voting participants , who provided evidence and reasoning, documented changes and took notes. Of the 34 recommendations, 31 were modified during the consensus process. Most modifications were minor changes in wording and/or strength of recommendation without changing the content of the recommendations. Some recommendations were further improved after the discussion with participants by adding additional information ). Recommendations were agreed upon live using an anonymous online voting system . The level of agreement was 100% for 27 of the recommendations, 92% for 5 recommendations, and 90% and 82% for one recommendation each.A new version of the guideline draft was then sent to conference participants, who were asked to use the Delphi process to obtain comprehensive feedback on the full text guideline from the organizations they represented. The feedback was discussed by the LLGH and the guideline revised where necessary. To ensure transparency, a point-to-point-reply format was used to document all comments and changes, and it was published along with the guideline report .GP practices from the practice-based research network SaxoForN (Saxony and Hesse) and Bielefeld were recruited to test the new guideline for feasibility under field conditions. Twenty-six GPs from 22 practices agreed to participate. Participating GPs received both the long and the short version of the guideline, and they were asked to provide feedback using a 10-item response form that asked for feedback on overall impression, clarity of presentation, definition of the target group, inventory and medication assessment, coordination with patients, providing patients with information on their medication, cooperation with pharmacists, medication use and self-management, monitoring and follow-up, and whether they would recommend the guideline to their colleagues. In addition, GPs were asked to treat around five patients from their practices in accordance with guideline recommendations, and to prepare anonymized case documentation at baseline  and, if possible, for a follow-up consultation. The participating GPs were asked to complete the questionnaires within a month, either online or paper based.Of the 26 GPs, 15 from 12 practices responded within the specified time period. They provided structured feedback and documented 67 initial and 27 follow-up consultations with patients. Although 92% of the GPs would recommend the guideline to their colleagues, 58% thought it was too long, and the two-page short version of the guideline was therefore frequently considered preferable. Eighty-three percent of participants thought the target group was clearly defined. While 75% of the participating GPs regarded the recommendations as helpful, only 25% thought important recommendations could be found easily. Recommendations concerning coordination with patients, providing patients with information on their medication, cooperation with pharmacists, medication use and self-management, and monitoring/follow-up were found helpful by 58%, 58%, 75% and 83% of GPs, respectively.Results from the feasibility test are presented in In 57% of the initial consultations, use of the guideline enabled participants to identify problems, and in 49% of cases, subsequent medication adjustments were made. In 56% of the follow-up consultations, patients reported an improvement in their health. Patients treated by the GPs were between 43 and 92 years old, with 93% of them taking more than 5 long-term medications and 91% having 3 or more chronic diseases. During the initial consultations, GPs reported de-prescribing more than one drug in 46% of patients and prescribing one or more new drugs in 26% of patients. In a further 26% of patients, a change in the dose was made. Seventy-two percent of patients reported obtaining their medications from a particular pharmacy, and 70% said they had an up-to-date medication plan. Forty-six percent of patients felt their treatment was a burden, and GPs tried to reduce this in 28% of cases. At follow-up, 74% of patients had an up-to-date medication plan, and in 59% of cases, medication changes agreed upon during the initial consultation were rated as successful by the GPs. However, in 14.8% of cases, the onset of new nonspecific symptoms/adverse drug reactions was reported.Feedback was discussed with the LLGH and changes were made and documented where appropriate. The pre-final version of the guideline was again sent to the boards of the societies involved in the consensus conference for final approval and authorization. Finally, the upgraded guideline on polypharmacy was published  togeThis guideline upgrade was part of the EVITA project, whose aim it is to develop and implement a nationwide structured management program on polypharmacy. Current disease management programs (DMPs) focus on single diseases and do not adequately take patients with multiple chronic conditions into account. The new guideline was therefore developed to serve as a basis for the development and implementation of a structured polypharmacy management program. The realist synthesis identified issues not previously addressed in the guideline , led to a more stringent framework and provided evidence for the recommendations. The guideline is expected to help GPs and other health care professionals involved in the care of patients with multimorbidity and polypharmacy and can provide evidence-based decision support. Use of a realist synthesis allowed us to ensure the scope of the review was relevant to stakeholders, and helped us to understand the mechanisms of action, and to systematically develop evidence-based recommendations for the guideline. Stakeholders’ perspectives, feasibility and guideline acceptance were assessed and considered throughout the process.The importance of involving stakeholders in guideline development has already been described by organizations such as the National Institute of Health and Care Excellence (NICE) . SimilarHowever, because of the broad range of issues covered in the guideline meant it was not feasible to address all the topics identified in the focus groups in depth. By prioritizing issues, the LLGH enabled us to limit the scope of the review questions, but our evidence searches and synthesis may have missed other topics that may have been relevant to address in this context. Another limitation is that recommendations were formulated with an eye to their relevance to primary care and their use in a German health care context, and some strong recommendations were based on a low level of evidence and vice versa. These may not be suitable for use in other health care contexts.To conclude, the steps of the realist synthesis are suitable for developing a complex guideline. However, prerequisites are a suitable financial framework, time resources and committed guideline developers.


GP.Mur is a clinically important red blood cell (RBC) phenotype in Southeast Asia. The molecular entity of GP.Mur is glycophorin B-A-B hybrid protein that promotes band 3 expression and band 3–AQP1 interaction, and alters the organization of band 3 complexes with Rh/RhAG complexes. GP.Mur+ RBCs are more resistant to osmotic stress. To explore whether GP.Mur+ RBCs could be structurally more resilient, we compared deformability and osmotic fragility of fresh RBCs from 145 adults without major illness (47% GP.Mur). We also evaluated potential impacts of cellular and lipid factors on RBC deformability and osmotic resistivity. Contrary to our anticipation, these two physical properties were independent from each other based on multivariate regression analyses. GP.Mur+ RBCs were less deformable than non-GP.Mur RBCs. We also unexpectedly found 25% microcytosis in GP.Mur+ female subjects (10/40). Both microcytosis and membrane cholesterol reduced deformability, but the latter was only observed in non-GP.Mur and not GP.Mur+ normocytes. The osmotic fragility of erythrocytes was not affected by microcytosis; instead, larger mean corpuscular volume (MCV) increased the chances of hypotonic burst. From comparison with GP.Mur+ RBCs, higher band 3 expression strengthened the structure of RBC membrane and submembranous cytoskeletal networks and thereby reduced cell deformability; stronger band 3–AQP1 interaction additionally supported osmotic resistance. Thus, red cell deformability and osmotic resistivity involve distinct structural–functional roles of band 3. GP staneostasis ,9,10. Oneostasis . GP.Mur+eostasis  and (ii)eostasis ,13. AQP1eostasis ,15. GP.MBoth deformability and osmotic fragility are physical properties applied to diagnostics of abnormal or unstable erythrocytes, such as spherocytosis and hemolytic anemia. Deformability measures the extensibility of an erythrocyte upon mechanical stress. Red cell deformability is influenced by (1) surface area (SA)-to-volume (V) ratio of a cell, (2) intracellular viscosity, and (3) membrane viscoelasticity . The intDiffering from deformability, osmotic fragility measures cell membrane extensibility upon hypotonic stress. Because osmotic fragility is measured by changing tonicity, this method is sensitive to movements of ions and water across the red cell membrane. The direction of ion (or water) flux through band 3 (or AQP1) follows the concentration gradients of individual ions (or water) if no cellular or molecular regulation is imposed. AQP1 and band 3 interact transiently on the surface of red cells; their protein–protein interaction disappears when red cells swell in a hypotonic milieu . IntriguThis study compared biophysical properties of GP.Mur+ and non-GP.Mur erythrocyte samples that were collected from nondiseased adult subjects. People who were interested in participating in the study were first asked to complete a questionnaire on their health status. Based on their answers to the questionnaire, those with severe cardiovascular, diabetic, hematological, or other major catastrophic diseases or conditions defined by the Taiwan National Health Insurance (TW-NHI) criteria  were excPeripheral blood was collected in an EDTA tube, a serum gel tube, and an ACD tube. A portion of the blood sample collected in the ACD tube was washed, fractionated, and aliquoted for RBC storage in a −80 °C freezer for later analyses. Fresh blood samples were analyzed for complete blood count (CBC), routine RBC typing, serum lipid analyses, osmotic fragility tests, and red cell deformability. Frozen aliquots of washed RBCs were subjected to membrane cholesterol analyses.a and anti-Mur antisera. The serologically positive samples were then verified by GYP.Mur-typing PCR as described in [GP.Mur blood type was serologically screened using anti-Miribed in .TM Red Cholesterol Assay kit . Briefly, a vial of 200 μL frozen RBC sample was centrifuged to remove the storage buffer, followed by PBS wash. All processes from this point on were on ice. The RBC pellet was hypotonically lysed with 1 mL of ice-cold 10 mM Tris buffer, pH 8.0, followed by centrifuge at 14,000× g and 4 °C to obtain the ghost (membrane) pellet. The ghost pellet was vortex-mixed with 100 μL of 1% Triton X-100 in PBS. The membrane cholesterol content in this detergent-lysed sample was quantified using the AmplexTM kit, according to the company’s instruction manual.Membrane cholesterol was quantitated from frozen packed RBC samples using the Amplexmax  and SS1/2 (shear stress capable of triggering 50% EImax) based on the experimental EI profile [RBC deformability was measured using the Rheoscan-D ektacytometer . The test analyzed fresh blood samples that were collected in ACD tubes. Before loaded onto Rheoscan-D, 6 μL of washed RBCs was diluted in 600 μL of polyvinylpyrrolidone phosphate buffered solution . The loaded sample was subjected to rotational speeds with increasing shear stresses ranging from 0.3 to 30 Pa at 37 °C. Images of the stress-induced, deformed RBCs were captured by laser diffraction. The elongation index (EI) of an individual RBC at a given shear stress is defined as (A − B)/(A + B), where A is the major (or longest) axial length and B the minor (or shortest) axial length of the imaged RBC. Rheoscan-D also calculated EI profile ,26.2O), followed by gentle mix and 30 min incubation at room temperature. They were then centrifuged for 5 min to pellet unruptured RBCs. Interpretation of the osmotic fragility test results should begin from the highest to the lowest concentrations of NaCl over a white board or a white background. The beginning of hemolysis was determined by visually comparing the test samples with a negative control for the first occurrence of faint pink-reddish color in the supernatant after centrifuge. The test recorded %NaCl at which hemolysis began and ended for each sample. The former was the concentration of NaCl at which pink color started to show in the supernatant; the latter was the concentration of NaCl at which the RBC pellet was no longer visible.Five microliters of fresh whole blood was each added to 0.5 mL of serially diluted NaCl solutions  on RBC deformability or on osmotic resistivity (dependent variable); p < 0.05 was deemed statistically significant. Statistics and plotting were performed using SPSS version 26 (IBM) and OriginPro 2020 software, respectively.The independent This study examined the influence of GP.Mur phenotype on RBC deformability and osmotic resistibility. Among the 145 adult subjects recruited (59 men and 86 women), 13 had microcytosis with mean corpuscular volume (MCV) < 80 μL . Intrigu*** p < 0.001): 0.218 ± 0.070% (GP.Mur) versus 0.288 ± 0.067% (non-GP.Mur). Notably, GP.Mur+ microcytes were able to tolerate more hypotonic conditions than GP.Mur+ normocytes in the beginning , were similar between GP.Mur+ and non-GP.Mur normocytes . GP.Mur+max, as the dependent variable in the multivariate regression, and first assessed the effects of gender, GP.Mur type, microcytosis, and the two parameters of osmotic fragility . RBC deformability was independent from the two parameters of osmotic fragility in this model  and lipid factors on red cell deformability. We found that the impact of MCV to EI samples  or to mi samples . We did  samples . If we c samples , the ana samples  would rer = 0.26, * p < 0.05). However, membrane cholesterol did not affect the deformability of GP.Mur+ RBCs . As band 3 and AQP1 interact more strongly on GP.Mur+ RBCs and the degree of their interaction depends on tonicity [By multivariate regression analysis, we also examined the potential factors that could affect the osmotic resistance of RBCs, including GP.Mur type, microcytosis, MCV, RDW, MCHC, and EIch other . GP.Mur ch other . Microcych other , though ch other . On the tonicity , these dThe erythrocyte membrane structure evolved to endure forces during ~120 days of circulation. Without band 3 protein embedded in the membrane, erythrocytes would not have the biconcave shape . From thFrom the three factors influencing erythrocyte deformability described in the Introduction , neitherBesides GP.Mur phenotype, membrane cholesterol also influences membrane viscoelasticity ,29. The In conclusion, this study explored cellular physical distinction between red cell deformability and osmotic fragility in a large cohort comprising nearly half GP.Mur+ subjects. GP.Mur phenotype/higher band 3 expression was an important variable contributing to deformability differences and osmotic fragility differences . However6 RBCs per μL peripheral blood, and all three men with microcytosis had >5.50 × 106 RBCs per μL . This argues against more thalassemia among GP.Mur+ women. Furthermore, thalassemic RBCs are fragile, contrasting to GP.Mur+ RBCs that are more resilient to external forces (On a separate note, we unexpectedly found 25% microcytosis in GP.Mur+ women in this study . In a sel forces . We do nLimitation: The small percentage of GP.Mur+ people remained to be a major limiting factor during subject recruitment, though the prevalence of GP.Mur special blood type in Taiwan is higher than many parts of the world.


The COVID-19 pandemic increased the need for new valid scientific evidence to support urgent clinical and policy decision making; as well as improved processes for the rapid synthesis, uptake and application of that evidence. Evidence informed policymaking (EIPM) can be considered as a way to access and use the results of evidence in practice. This study aimed to determine what effects COVID-19 had on the way Iranian health managers and policymakers use evidence in their decisions.This study was conducted in 2021 applying a qualitative research design. Data was collected through semi-structured interviews. Thirty health care managers, policy makers and medical university faculty members were recruited as the study participants, initially via a purposive sample, followed by snowballing. A conventional content analysis presented by Hsieh and Shannon (2005) was applied for data analysis.Ten main themes emerged from the data including: 1) roles and duties of knowledge brokers (KBs); 2-5) the roles, benefits, barriers and necessities of applying Knowledge Translation Exchange (KTE) tools; 6-8) the facilitators, benefits and barriers to the application of evidence during COVID-19; 9) challenges of rapid evidence production evidence during COVID-19 and 10) consequences of not applying evidence during COVID-19. According to the present conceptual framework, KBs act as an intermediator between the large amounts of knowledge produced and decision makers. KTE tools should be applied to enhance EIPM during COVID-19. Attention should be paid to the facilitators, barriers, benefits and necessities of evidence application during COVID-19 to avoid negative consequences for the health system.Results of this study show that developing KTE tools and activating KBs can be among the main strategies to produce applied actionable messages for policymakers to move toward EIPM; and that this applies even when rapid decision making is required, such as during the COVID-19 pandemic. It is strongly recommended to reinforce the local capacities through supporting scientific networks and relationships between research centers and local and national policymakers. At the same time, attention to local barriers to and facilitators of the application of evidence while facing a pandemic can pave the way to better identification of health system`s problems and rapid responses. Corona Virus Disease 19 (COVID-19) has been the worst public health disaster in recent decades and it has severely impacted on health systems and economies all over the world. Such an emergency has placed unexpected pressures on decision makers and policymakers at all the levels to make urgent decisions with wide ranging consequences. These decisions have had to be made despite high levels of uncertainty and significant long term consequences for the lives of millions of people .Knowledge exchange translation (KTE) is a concept that implies a systematic and dynamic process.for the application of knowledge in order to improve a community`s health, provide more effective services and strengthen the healthcare systems. In another words KTE acts as a bridge between the researchers and the policymakers and managers to transfer the actionable messages extracted from the researches for better decision making. At the same time KTE can help synthesizing and building recommendations from the available researches as a base for the policymakers and managers` decisions and best practices. About the role and importance of KTE one of the participants added:“KTE can be applied as a tool during the pandemic to translate the scientific and complex concepts to the actionable messages that can be used by the managers and policymakers. For instance, it was an obligation for each of the universities of medical sciences to produce a policy note applying the results of their research and the valid evidence and share it with the others. This can be help a lot”[P5].About the benefits of KTE the present participants emphasized that:“Applying practical evidence during the pandemic can easily lead to better clinical decision making and more appropriate policies. Also it can help to increase the health literacy of the community in the area of vaccines and other preventive areas against the pandemic” [P7].Or elsewhere another participant stated:“KTE led to implementation of the policies that resulted in public behavioral changes and also the changes in the people`s lifestyle like social distancing, wearing facemasks, staying home and so on” [P18].It is important to mention that applying KTE in a developing country encounters many cultural, structural and executive barriers. In this regard, one of the participants describes the barriers as follows:“One of the main barriers in implementing KTE in our country is unfortunately overcoming preferences and the political benefits towards EIPM. Such a barrier can widely affect the appropriate process of decision making and policy making” [P10].Another participant added:“there are many published articles in the area of COVID-19 but unfortunately we don’t have access to all of them. Another barrier I think is related to this problem that many of our managers and even policy makers are not familiar with the concept of KTE in practice” [P12].The participants mentioned that KTE is in itself is a useful concept, but it was more important to consider the practical tools through which it is operationalized.“I don’t it is possible to engage in KTE unless the valid, timeliness and accurate knowledge is available and accessible. Without these pre-requisites applying the present results may be more harmful” [P30].Another participant indicated that:“Without production the actionable messages according to the stakeholder`s wants and tendencies, KTE can`t be useful. Our community is not research literate enough to understand the results of many scientific research unless it can be translated according to their knowledge and level of literacy” [P14].Participants also considered the facilitators to implementing EIPM according to the community`s acceptance and needs. One participant said:“We can say one facilitator here has the right beliefs and positive attitudes of the health managers and policymakers regarding the application of evidence in decision making. Their training also can be helpful” [P16].Another participant added:“in my opinion, the culture and organization atmosphere toward the research and applying the results can be as a facilitator. Another important factor is whether the manager or the policymaker who is expected to make decisions was appointed according to merit and having scientific understanding and skills or not” [P27].And similarly, another participant pointed to the process of retrieving the evidence as a facilitator.“it is really important that policymakers have the possibility and opportunity of timely access to the evidence before their final decisions. A policymaker normally doesn’t have time for searching and retrieving the evidence…” [P33].There are different barriers to applying evidence in policymaking during pandemic. Among them are organizational, legal, cultural, structural and financial barriers. A participant implied that:“many of the barriers are related to the organizations. For instance, a policymaker that always acts traditionally with no creativity, can`t use evidence in his/her decision making. He is not even aware of such a thing and is just occupied with his routine and daily duties; with no experience of applying evidence in policymaking…” [P19].Another participant said:“sometimes the policymakers want to use scientific evidence in their decisions but the regulations restrict them. The bureaucratic structure of the organization, especially in the governmental sector, can make it much worse” [P20].The participants also pointed to many benefits of EIPM during the pandemic. For example, one participant clarified:“the experience of the pandemic shows us how applying the scientific evidence in our decision making can help us avoid trial and error, duplicated actions and waste of time and resources” [P22].Another participant also added:“applying evidence helps us know the nature of the disease better and faster particularly regarding different conditions of the regions or different environments like hospitals, health centers, laboratories, …” [P29].According to the participants it is important to pay attention to how evidence is produced and applied during the pandemic. One participant stated that:“one necessity is that during pandemic, along with producing the evidence, we should pay attention to the quality of the produced evidence” [P25].Another participant indicated that:“ethical considerations are among the most requirements of producing the evidence during pandemic. It is important not to underestimate the problems of vulnerable groups such as elderly population. It is also significant for producing and applying the evidence related to vaccines” [P35].According to the participants` viewpoints, lack of attention and neglecting the use of evidence in policymaking during pandemic may lead to negative consequences. For instance:“a negative consequence can be a situation that the health organization cannot move forward and the trial and error approach will be used. This can threaten the organization`s efficiency and effectiveness” [P31].Another participant added:“those policymakers who ignore the evidence during the pandemic, may lose a great deal of time and resources; human resource, financial and the equipment. All these can lead to trial and error, organization collapse and conflict as well as frustration and dissatisfaction” [P17].And finally another participant stated:“another consequence of not using scientific evidence in the process of policymaking is that the community will experience the frustration and exhaustion; and mental problems will increase. Such a community may face a delay in returning to normal conditions” [P30].Figure The aim of this study was to determine how policymakers apply scientific evidence to guide related decisions during COVID-19 pandemic. Our conceptual model reflects the themes that emerged among health care managers and policy makers  who also found that KBs could help build a deeper understanding between the needs of both evidence producers and end users. At the same time, KBs can facilitate interaction and sharing the information among the producers and users of the evidence .Kuchenmüller et al. (2021) have also emphasized that global policy organizations such as the World Health Organisation (WHO) have supported scientific evidence for empowering and training policymakers during COVID-19 pandemic. They have also suggested that WHO has played a significant role as an organized knowledge broker globally .There have however been some use of KTE tools such as policy briefs, which were issued by The World Health Organization (WHO) with some recommendations for evidence based recommendation on appropriate responses to COVID-19 via breaking transmission chains, diagnosis and treatment of the disease and reinforcement of health systems.These poAccording to the present results, KTE is considered as another concept and process, during which tools can be applied to facilitate EIPM during COVID-19 pandemic. El-Jardali et al. (2020) have also declared that a purposive approach to KTE is helpful in situations such as the Covid-19 pandemic. They emphasis a combination of factors including: making scientific evidence accessible, appropriate and understandable for the political context; improving trust and overcoming misinformation; and facilitating common platforms where different stakeholders from diverse sectors can work to solve problems together[Our study also uncovered barriers faced by policy makers to engaging in KTE during the COVID-19 pandemic; echoing other studies. Mahendradhata et al. 2021) found that a lack of knowledge about KTE as a concept and how to apply it limited evidence utilisation. They also found that restricted resources, lack of organizational support, lack of critical appraisal skills, and non-aligned missions between researchers and policymakers were further barriers in applying KTE [ found thOliver et al. (2014) in a review article have summarized the main barriers and facilitators of applying evidence by policymakers. They have concluded that timely access to high-quality scientific research along with collaboration and communication with the policymakers can act as the main effective factors in applying evidence by policymakers. Lack of access to evidence, non-clarity, suitability, trustworthiness of the findings, timeliness and costs were named as the main barriers of applying evidence by the policymakers . HasanpoOur study has also shown that policymakers are aware of the benefits of EIPM, and that this awareness was heightened during the pandemic. Lancaster et al. (2020) also revealed that the COVID-19 pandemic led to an increased interest in and uptake research in their decision making. They emphasized that the pandemic resulted in the opportunity for the judgement of the policymakers` decisions according to their restrictions .And finally, results of our study have shown that a failure to use and apply evidence by policymakers during COVID-19 pandemic led to negative consequences including public dissatisfaction, ineffective decision making, organizational collapse, frustration, conflicts and failure to change amongst staff, prohibited organizational improvement and growth. In this regard, Ioannidis 2020) has also claimed that lack of applying scientific research by policymakers during pandemic may lead to dissemination of misinformation, exaggerated estimations and inappropriate allocation of the resources. All of these can threaten the scientific reputation of public health, media and health policymakers [020 has aOn the other hand, according to the present results, applying EIPM by the policymakers, is accompanied by some necessities the same as identifying the knowledge gap, determining the lessons learned, producing sustainable and flexible resources, establishing of a research network and legal and ethical mechanism for access to health data. According to Yang (2020), during pandemic, evidence based management should benefit from different standards the same as scientific quality, relatedness, appropriateness and rationality of the evidence. Furthermore, the capacities of applying evidence should be made inside and outside of the government. Yan also strongly emphasized that in a democratic community, policy making should be based on both evidence and the values . This stThis study has some limitations. First some interview had to be conducted via telephone due to COVID-19 restrictions at the time which may limit the interactions during the interview. Second, for the same reason most of policymakers and managers had a very restricted time to allocate for the interviews, hence in-depth discussion on issues were not all possible. Third, as this was a qualitative research study, results should be understood in context before applying lessons to different countries and circumstances.Large volumes of evidence are being produced during the Covid-19 pandemic. Applying this evidence should be of central concern for health managers and policymakers. The results of this study show that developing purposive KTE strategies and activating KBs can be among the main strategies to move toward EIPM during the pandemic. At the same time attention to local barriers and facilitators of applying evidence can pave the way for policymakers to better identifying the health system`s problems and preparing rapid response in the pandemic condition.


Over 1 million biomedical publications are added to PubMed each year. Meanwhile, the internet offers the lay public a seemingly endless quantity of scientific information, opinions and beliefs. The sheer volume of information available presents a major challenge to clinicians who are expected to make everyday decisions based on the best available evidence. Many exciting discoveries in our field come to our notice through uncontrolled or poorly controlled observational studies and need robust evaluation in the context of randomized trials before they can be adopted into routine clinical practice. This process takes time and, in some cases, may not happen at all. Clinicians face a quandary—do they accept results based on suboptimal study designs or risk rejecting potentially effective treatments in their quest for epistemic certainty. Part of the challenge in identifying evidence we can trust is the proliferation of low-quality and misleading publications which can obscure the truth. How can researchers, journals, clinicians and patients play a part in improving this interface between science and health care delivery?Science is, and has always been, corrigible—with most advances occurring in incremental steps. Acceptance of error is central to a scientific approach where hypotheses are tested and, if proved wrong, rejected. Willingness to live with uncertainty is a key attribute of science and a strength rather than a weakness in those who believe in scientific thought. As this legitimate element of uncertainty should not be allowed to paralyse clinical decision-making, we need a dynamic process of decision-making using evidence available at any given time, to guide treatments which are effective, safe and acceptable.Acceptance of evidence-based medicine implies awareness of the variable quality of evidence within the scientific literature. Researchers know that the chances of error can be minimized by choosing the most appropriate study design, sample size and outcomes for a study and by actively taking steps to minimize bias. Better understanding of tests of statistical significance and conscious steps to avoid ‘p hacking’ have also led to better interpretation of quantitative data. At the same time, the appetite for positive novel findings carries predictable risks of publication bias and poor replicability.a priori as either primary or secondary outcomes can limit the risk of populating the literature with misleading results.Even well-designed and properly conducted research is not free from random errors. Randomized trials are generally assumed to be the best way of evaluating clinical interventions. Yet, even in well-designed trials comparing two treatments with 80% power and a 5% level of significance, 1 in 5 studies will fail to detect a true difference between 2 interventions, while 1 in 20 will falsely identify a difference where none exists. Publishing findings other than those identified A striking development in scientific research over the past few decades has been the growth of secondary research in the form of systematic reviews and meta-analyses. Meta-analysis is a powerful tool which allows us to aggregate the results of well-designed but underpowered studies to provide a definitive answer to clinical questions and are often used to inform clinical practice guidelines. At the same time, indiscriminate aggregation of data without careful clinical or methodological considerations can seriously compromise the quality of the output. This can be worrying enough in the context of randomized data with significant clinical or statistical heterogeneity but is much worse in the case of observational studies, where meta-analyses of crude unadjusted results can generate greater degrees of precision around potentially erroneous results. In the absence of the most appropriate research, it is not unreasonable to explore all available data—but of course this needs a more nuanced appraisal of the margin of effect, risks, costs and acceptability associated with alternative interventions.Scientific journals have a clear responsibility in terms of curating high-quality scientific output and making it accessible to consumers. It goes without saying that published research should be genuine and ethical, and journals need to be more proactive in ensuring the provenance of what they publish. Data should be presented in a transparent way and all conclusions drawn from them should be valid. As scientists are just as likely to be wedded to certain preconceptions or beliefs as other humans, it is important that published papers are clear about any confirmation bias. Overstatement of the clinical relevance of the findings is a common fault among researchers which needs to be moderated by peer reviewers. Journals also have a key role in combating publication bias by demonstrating their willingness to publish papers reporting negative results.Through a robust system of supportive peer review, journals need to make sure that readers get a clear sense of the veracity, precision and limitations of published research. While true for all scientific journals, this is especially important for all medical journals which mainly report on clinical evidence which can directly impact on patient care.Journals also have a responsibility in educating readers to become sophisticated consumers by giving them the tools to critically appraise published material and by ensuring that all output is freely accessible. Finally, for maximum impact, medical journals should try to communicate effectively with a mixed audience of scientific and non-scientific readers.HROpen which make scientific findings freely accessible to all, and use a rigorous peer review process to ensure that all evidence is presented in a transparent, unbiased and comprehensible manner.Evidence-based medicine relies on our ability to critically evaluate research findings to inform clinical practice. This is facilitated by open access journals like


Sparse relative effectiveness evidence is a frequent problem in Health Technology Assessment (HTA). Where evidence directly pertaining to the decision problem is sparse, it may be feasible to expand the evidence-base to include studies that relate to the decision problem only indirectly: for instance, when there is no evidence on a comparator, evidence on other treatments of the same molecular class could be used; similarly, a decision on children may borrow-strength from evidence on adults. Usually, in HTA, such indirect evidence is either included by ignoring any differences (‘lumping’) or not included at all (‘splitting’). However, a range of more sophisticated methods exists, primarily in the biostatistics literature. The objective of this study is to identify and classify the breadth of the available information-sharing methods.Forwards and backwards citation-mining techniques were used on a set of seminal papers on the topic of information-sharing. Papers were included if they specified (network) meta-analytic methods for combining information from distinct populations, interventions, outcomes or study-designs.n=79) described methods that shared information on relative treatment effects. Amongst these, there was a strong emphasis on methods for information-sharing across multiple outcomes (n=42) and treatments (n=25), with fewer papers focusing on study-designs (n=23) or populations (n=8). We categorise and discuss the methods under four ’core’ relationships of information-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explain the assumptions made within each of these core approaches.Overall, 89 papers were included. A plethora of evidence synthesis methods have been used for information-sharing. Most papers . Health Technology Assessment (HTA) is the systematic evaluation of the properties, effects and impact of health technologies with a view to inform decision-making in health care . RegardlDecision analysis provides a quantitative framework that brings together all relevant evidence on the impact of an intervention on health outcomes and costs, whilst making explicit judgements about how different types and sources of evidence are linked together (model structure) and which elements are relevant to decision-making . The outputs of a Decision Analytic Model (DAM) include incremental costs and benefits and can be useful for decision-makers .direct evidence. Hence, direct evidence on relative effectiveness comprises of one or more randomised studies, evaluating the intervention(s) under assessment, recruiting patients from the population of interest, and measuring effects on all relevant outcomes.Each input within a DAM is a parameter and constitutes a potential research question that can be informed by evidence which is typically identified using literature reviews. To assist study selection when identifying evidence for reviews, research questions are defined using the PICOS framework, where P stands for Population, I for Intervention, C for Comparator, O for Outcome, and S for Study-design . TypicalWhere multiple studies exist to inform the same parameter, these can be synthesised to generate a single estimate that represents the evidence-base. To synthesise the evidence base and provide DAMs with relative effectiveness inputs, standard Meta-Analysis (MA) and Network Meta-Analysis (NMA) methods , 7 are cHowever, in HTA, direct evidence may be sparse, heterogeneous, or limited in other ways and synthesis may become problematic. Where evidence is sparse, it may not be possible to obtain the required Relative Treatment Effect (RTE) estimates, and even when they can be obtained, they may be highly uncertain and may not be robust due to assumptions imposed in the analysis , 9. Evid“The evidence needed to address the research questions that are important for marketing authorisation of a given product in the target population might be modified based on what is known for other populations” )The search was conducted in Zotero version 5.0.69 and a link to the included papers Zotero database, where the papers have been grouped according to various tags, is provided in the end of the manuscript. The PRISMA checklist for systematic reviews is provided in Additional file n=79) described methods that shared information on relative treatment effects. Other studies used methods to share information on comparison-specific meta-regression slopes (n=4), comparison-specific between-studies heterogeneities (n=6), or study-specific baselines (n=2). Overall, there was a balance amongst papers that developed methods within MA (n=45) and NMA (n=44). There was a strong emphasis on methods for information-sharing across multiple outcomes (42 papers) and treatments (25 papers), with fewer papers focusing on study-designs (23 papers) or populations (8 papers)  Table . Note thdesigns 2 papers oWe also identified the most common synthesis challenges addressed by the included papers. Amongst papers sharing information across populations, 3 , 55, 56 functional relationships which include deterministic functions among model parameters resulting in a reduced number of parameters that need to be estimated; 2) exchangeability-based relationships which assume that a set of parameters are drawn from a common distribution that allows them to be shrunk towards its mean; 3) prior-based relationships which employ a Bayesian framework to ‘load’ the indirect evidence in prior distributions and 4) multi-variate methods which assume that model parameters are correlated and enable information-sharing through the covariance structure. Figure The methods identified were classified according to the ‘core’ relationship facilitating information-sharing. Four ‘core‘ methods were identified: 1) Table The simplest functional relationship is lumping (i.e. common effects) where all data points inform a single parameter independently of whether the evidence is direct or indirect. Examples include pooling RTEs across time-points , (sub-)pAnother type of functional relationship is a constraint where a strict inequality is imposed among parameters. In a Bayesian framework, information-sharing is facilitated by preventing simulation samples that do not conform to the specified constraint. Such methods have been used to relate RTEs across dosages, expressing that higher dosages are expected to exhibit larger RTE , 44, desMeta-regression-type methods have also been suggested. In the examples found, the relationships were usually linear -on the modelling scale- with one RTE component independent and another RTE component dependent on a particular study characteristic. The most common example in this category is bias-adjustment methods, primarily used to synthesise studies of different designs. Bias-adjustment methods broadly fall into two categories: general frameworks that adjust the RTE for biases affecting internal and external validity provided that the extent of bias can be either estimated from empirical evidence or elicited from experts , 98, 99,Finally, more complex, non-linear, relationships have also been presented in the literature, namely those enabling the synthesis of RTEs across a range of dosages using the Emax model –53 commoThe simplest exchangeability-based relationship uses a random effect to relate a set of parameters; in this way accounting for heterogeneity without explicitly modelling its source(s). The random effect assumes that all parameters are drawn from a distribution, implying that individual parameters are shrunken towards the random effect mean; this can happen to a greater or lesser extent, depending on the precision and discrepancy of each individual estimate in relation to the random effect mean. Examples of parameters to which random-effects have been applied include: comparison-specific meta-regression slopes , 42, 50,Random-walks are another form of exchangeability relationship. They assume that data points which are more similar with respect to a particular characteristic are expected to exhibit more similar RTEs. Examples include approaches assuming that the RTE of a particular dosage or follow-up period is drawn from a distribution centred around the RTE of its adjacently lower or higher dosage  or folloMulti-level models also use exchangeability, but apply it to the hierarchical/clustered structure of the available data. As such, exchangeability is applied at a first level within specific groups of parameters  and at a second level across the group-specific hyper-parameters. This is shown in Fig. Direct and indirect evidence can also be combined through the use of prior distributions. The process usually consists of two-steps where initially the indirect evidence is analysed and subsequently the resulting distribution is used as a prior in the analysis of the direct evidence. Of note is that this approach is mathematically equivalent to lumping, which was described under functional relationships. Examples include the combination of adult and paediatric evidence  or rando‘adaptive’ information-sharing whereby information-sharing is stronger when the direct and indirect evidence are in agreement and weaker when they conflict [More nuanced prior-based approaches such as mixtures of priors have also been used. Here, the informative prior (distribution representing the indirect evidence) is not used at face value, but instead mixed with a vague prior according to weights that may be specified by the analyst or estimated within the synthesis model. The resulting informative prior is typically heavy-tailed, and allows for conflict . Mixtureconflict  and to aconflict . The useconflict .a≤1 which reflects the perceived similarity between the two sources of evidence. When a=1 the results are equivalent to ‘lumping’ and when a=0 results are identical to ‘splitting’. The power parameter, a, needs to be specified, and it has been proposed to be elicited [Finally, a flexible method that has been proposed is the power-prior . In thiselicited  or varieelicited . Power pelicited  and for elicited .Multi-variate relationships have primarily been used to share information across multiple outcomes. Multivariate meta-analysis correlates the various outcomes and may separate within- and between-studies correlations . At the Multivariate methods have been developed to consider two , 83, 84,To accommodate cases where the within-trials correlations are unavailable and cannot be otherwise obtained, alternative methods, which require the same data as a univariate approach and do not separate within- and between-trials correlations have been suggested for MA , 82 and Finally, some methods only account for either the within- or the between- studies correlations. For example, to model mutually exclusive outcomes, it has been suggested to only account for the within-trials negative correlations which are induced by the competing risks structure of the data  . Also, oThe aim of this review was to identify and classify evidence synthesis methods that have been used to combine evidence from sources that relate directly and indirectly to a particular research question. A wide range of methods have been developed to share information between populations, treatments, outcomes and study-designs. We found that across the breadth of methods identified, four ‘core’ relationships are used to facilitate information-sharing. These are functional, exchangeability-based, prior-based, and multivariate relationships and are illustrated in Fig. This review highlights the breadth of methodological options that can facilitate information-sharing. Although, typically, particular relationships are used preferentially to share information on specific information-sharing contexts, it is likely that several methods are applicable and analysts would need to choose which method is more appropriate. This paper highlights that appropriate considerations need to be made when choosing ‘core’ relationships and methods because choices are likely to influence the degree of information-sharing. Specifically, method selection may be informed by the following considerations; the first is the plausibility of the assumptions imposed by the methods in the context of interest. By classifying methods according to the ‘core‘ relationship that enables information-sharing, we hope to facilitate a clearer discussion about the plausibility of these assumptions in the decision context of interest.The second is the degree of information-sharing that is imposed between direct and indirect evidence. Within the literature, there is limited exploration of how much different methods borrow-strength from indirect evidence, though for multivariate methods, it has been noted that information-sharing is ‘usually modest’ , 66 and,α which determines the extent of information-sharing.Finally, decision-makers may be interested in exploring different levels of information-sharing. One way to do that is by using prior-based methods that allow some control on the degree of information-sharing. For instance, an informative prior may use either the posterior distribution of the mean, or the predictive distribution of the indirect evidence. The former is equivalent to lumping, whilst the latter imposes less information-sharing. Similarly, mixture priors can regulate the weight that is placed on the informative component, and power-priors allow a range of values to be used for Whilst our literature search was systematic in its methods and conduct, it is unlikely to have been fully comprehensive. The use of citation-mining techniques, while efficient and necessary for this search, may have missed relevant methods. This is because the sensitivity of citation-mining methods depends on the existence and identification of seminal papers  and on pThis paper is the first to summarise and categorise the existing literature by classifying methods according to the ‘core’ assumption that they use to facilitate information-sharing. Further research could explore the following questions: first, how can we determine whether indirect evidence is relevant? Second, how can the appropriateness of each information-sharing method be assessed for the synthesis problem at hand? Finally, can the extent of information-sharing be quantified to assist transparent decision-making?We conclude that a plethora of methods has been used to facilitate information-sharing. These can be categorised according to the main assumption they impose into functional, exchangeability-based, prior-based, and multivariate relationships. Despite the wide range of available methods, these are often used preferentially without ensuring that all options have been explored. Given that methods may differ in the degree of information-sharing they impose, the implication is that the chosen method may impose stronger or weaker information-sharing that what is considered appropriate by policy-makers. Further research should investigate ways of judging the appropriateness of the degree of information-sharing imposed by each method, and assess the impact of using different methods on decisions.Additional file 1 Search strategy. A description of the inclusion and exclusion criteria of the search as well as the number of citations for each one of the seminal papers and the number of times it has been cited.Additional file 2 PRISMA checklist for systematic reviews. The PRISMA checklist for systematic reviews, indicating the page at which each characteristic of the review is described.Additional file 3 Brief summary of each included study. Multi-page tables including a brief description of how each of the included papers shared information between direct and indirect information, on which PICOS dimension and its main characteristics.


Background: There is a significant lack of consistency used to determine the scientific validity of nutrigenetic research. The aims of this study were to examine existing frameworks used for determining scientific validity in nutrition and/or genetics and to determine which framework would be most appropriate to evaluate scientific validity in nutrigenetics in the future.Methods: A systematic review (PROSPERO registration: CRD42021261948) was conducted up until July 2021 using Medline, Embase, and Web of Science, with articles screened in duplicate. Gray literature searches were also conducted (June-July 2021), and reference lists of two relevant review articles were screened. Included articles provided the complete methods for a framework that has been used to evaluate scientific validity in nutrition and/or genetics. Articles were excluded if they provided a framework for evaluating health services/systems more broadly. Citing articles of the included articles were then screened in Google Scholar to determine if the framework had been used in nutrition or genetics, or both; frameworks that had not were excluded. Summary tables were piloted in duplicate and revised accordingly prior to synthesizing all included articles. Frameworks were critically appraised for their applicability to nutrigenetic scientific validity assessment using a predetermined categorization matrix, which included key factors deemed important by an expert panel for assessing scientific validity in nutrigenetics.Results: Upon screening 3,931 articles, a total of 49 articles representing 41 total frameworks, were included in the final analysis . Factors deemed important for evaluating nutrigenetic evidence related to study design and quality, generalizability, directness, consistency, precision, confounding, effect size, biological plausibility, publication/funding bias, allele and nutrient dose-response, and summary levels of evidence. Frameworks varied in the components of their scientific validity assessment, with most assessing study quality. Consideration of biological plausibility was more common in frameworks used in genetics. Dose-response effects were rarely considered. Two included frameworks incorporated all but one predetermined key factor important for nutrigenetic scientific validity assessment.Discussion/Conclusions: A single existing framework was highlighted as optimal for the rigorous evaluation of scientific validity in nutritional genomics, and minor modifications are proposed to strengthen it further.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=261948, PROSPERO [CRD42021261948]. It has been suggested for decades that optimal strategies for managing health and disease should be personalized. In 1903, Dr. William Osler stated that “variability is the law of life and no two individuals react alike and behave alike under the abnormal conditions which we know as disease. The good [healthcare provider] treats the disease, the great one treats the patient . While tSeveral methods exist for evaluating the scientific validity in the fields of nutrition –13 and gTherefore, the aim of this study was to first provide a systematic overview of evidence evaluation frameworks used to assess scientific validity in the fields of both nutrition and genetics. We further aimed to determine if a framework exists that is appropriate for evaluating scientific validity in nutritional genomics. Lastly, we aimed to propose a framework  for use specifically in determining scientific validity in nutritional genomics. The proposed framework is intended to stimulate discussions in the scientific community and form the foundation for future refinement.https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=261948. The review process was guided by previously established methods for conducting rigorous systematic reviews (This systematic review was registered with PROSPERO CRD42021261948) and the protocol can be accessed at 21261948 First, a systematic search was undertaken by two investigators using three search engines: Embase, Web of Science, and Medline. The search terms are outlined in Data extraction templates were piloted in duplicate on 10 included articles, with one author completing the remaining data extraction (JK). The final data extraction template included the following headings: first author name and year, framework title, included study designs for evidence evaluation, main scientific validity evaluation components described in the tool, categories for levels of evidence, a brief description of the framework and whether the framework has been used in nutrition and/or genetics. Data was also extracted for completion of the categorization matrix, further described below.The included frameworks were then critically appraised for their appropriateness for evaluating the quality of nutrigenetic research. A categorization matrix was used to guide the appraisal process; matrix headings were developed within the context of key factors to consider in determining levels of evidence for nutrigenetic study findings. These factors (matrix headings) were drafted collaboratively by the expert working group . The first draft was developed based on a review of the literature on standard items included in evidence evaluation tools, critiques of existing evidence evaluation tools and special considerations for evidence evaluation of nutrigenetic research. Following this, an external panel of experts in nutritional genomics and/or knowledge translation (either in nutrition or genetics) reviewed/revised the draft categorization matrix and provided comments. The external panel is listed in the acknowledgments section. Following revisions, all authors and members of the external panel approved the final categorization matrix.nutrigenetic evidence evaluation specifically. Based on the results of the categorization matrix, a framework was recommended, with minor revisions, for use in analyzing the scientific validity of gene-diet interactions/associations.Each included framework was then added to the categorization matrix, and data were extracted to evaluate the suitability of the framework for evaluating evidence in nutrigenetics. Checkmarks indicated that a factor was considered in the framework, whereas an “X” indicated that the factor was not considered in that particular framework. For example, frameworks that incorporated evidence of biological plausibility . One framework that has been used for evidence evaluation in both nutrition and genetics has further been used for evidence evaluation in nutritional genomics  identified by the expert working group and external expert panel for evaluating nutrigenetic evidence related to: study design and quality, generalizability, directness, consistency, precision, confounding, effect size, biological plausibility, publication/funding bias, allele and nutrient dose-response, as well as summary levels of evidence. The categorization matrix is detailed in It should be noted that only brief descriptions are provided in The categorization matrix was used to determine which, if any, of the existing might be most appropriate for comprehensive nutrigenetic evidence evaluation. Significantly, this systematic review did not identify any frameworks that considered all the factors deemed important by the expert group in evidence evaluation for nutritional genomics. However, there were two identified tools that considered all but one key factor relevant to evidence evaluation in nutritional genomics—the methods used by the World Cancer Research Fund (WCRF) and the gene-environment interaction framework developed by Boffetta et al. , 72. TheWe propose the use of Boffetta et al.'s framework , with soFour minor modifications to this framework are suggested. First, (i) evidence of allele-dose responses should increase our confidence in a gene-diet interaction effect. This could be integrated into Step 4 of the framework as it is considered an “additional support for [the] interaction” . AdditioThis review provides an overview of one key aspect to consider when evaluating the suitability of nutrigenetic tests for clinical practice—scientific validity. While we propose that Boffetta et al.  have devFTO genetic variation on weight and body composition responses to dietary protein intake  , 94. TheThere are some limitations and strengths of the present review. While we systematically searched the evidence, we cannot preclude the possibility that some evidence evaluation frameworks were missed. This is a possible limitation. In addition, while our methods were sound for developing the categories within the matrix, this is only a first iteration, and it is possible that future iterations may include different categories. For example, researchers have pointed out that genetic architecture matters in terms of the effect size of SNPs; ancestry-informative markers can provide a more detailed characterization of populations . Thus, cOverall, we have provided a synthesis of 49 articles representing 41 total frameworks that have been used to evaluate scientific validity in nutrition and genetics. Based on our evaluation of existing frameworks, it appears that Boffetta et al. have developed the most suitable and rigorous framework for use in evaluating the scientific validity of various gene-diet associations and interactions . Some miThe original contributions presented in the study are included in the article/M-CV, RG, and JK conceptualized the review and developed the methods. M-CV and RG provided supervision for the project. DZ-M took primary responsibility on developing the search strategy, with guidance from JK. JK and VG were responsible for article screening and selection, as well as summarizing included articles and completing the categorization matrix, with assistance from EG and JM-B. JK wrote the first article draft. RH, DZ-M, VG, M-CV, RG, and JK revised the manuscript. All authors approved the final manuscript.JK received postdoctoral fellowships from the Canadian Institutes of Health Research, INAF, and NUTRISS. M-CV holds a Tier 1 Canada Research Chair in Nutrition Applied to Genetics and Metabolic Health.RH was employed by company Human Longevity, Inc. RG has received compensation for advising the following companies: AIA, Embryome, Genomic Life, Grail, Humanity, Kneed Media, OptumLabs, Plumcare, Verily; and is co-founder of Genome Medical, Inc, a technology and services company providing genetics expertise to patients, providers, employers and care systems. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In typical development, infants form predictions about future events based on incoming sensory information, which is essential for perception and goal-directed action. It has been suggested that individuals with autism spectrum disorder (ASD) make predictions differently compared to neurotypical individuals. We investigated how infants who later received an ASD diagnosis and neurotypical infants react to temporarily occluded moving objects that violate initial expectations about object motion. Our results indicate that infants regardless of clinical outcome react similarly to unexpected object motion patterns, both in terms of gaze shift latencies and pupillary responses. These findings indicate that the ability to update representations about such regularities in light of new information may not differ between typically developing infants and those with later ASD.The online version of this article (10.1007/s10803-021-04876-2) contains supplementary material, which is available to authorized users. Acting efficiently in an ever changing, dynamic environment requires individuals to actively make predictions about upcoming events. From early on, infants learn to perceive and understand others’ actions and the regularities of objects in the world surrounding them  have been put forward that all underline the importance of prediction, and the adaptation of predictions to changes in the environment. It is assumed that humans constantly make predictions about the environment and these predictions are integrated and compared with incoming sensory information to form a percept, which is needed to be able to act efficiently in the world  and infants at low likelihood for ASD  from 10 to 36 months of age, when a clinical diagnostic assessment was performed. The recurrence rate of ASD in full siblings is around 20% on average . Secondly, we investigated potential differences in adaptation rates in the 10–18 months range between infants with later ASD and neurotypical infants, taking into account the potential effect of age. In addition, we specifically analyzed the gaze shift and pupillary response to the first trial . Here too, we examined potential differences between infants with a subsequent diagnosis of ASD and neurotypically developing infants in terms of gaze shift latency and change in pupil size in response to the first occlusion trial across ages. Given the notion that individuals with ASD have an atypical balance between bottom-up and top-down processes, which is essential for forming predictions in new situations, we expected group differences in this task. However, to our knowledge, no one has studied the update of expectations in the current context of infants with later ASD, we refrained from making specific predictions about the direction of the putative effects.Assessment at 10, 14 and 18 months of age for the amount of valid gaze data per assessment and Table http://www.earlyautism.se). The EASE study is a prospective longitudinal study of infant siblings at elevated likelihood of ASD. At the time of enrollment, the clinical outcome is unknown; thus, infants with an older sibling diagnosed with ASD represent the “elevated likelihood” group, while infant siblings with no familial history of ASD represent the “low likelihood” group. At 36 months of age, a clinical diagnostic assessment was conducted and children were assigned to (1) an elevated likelihood group with ASD (EL-ASD); (2) an elevated likelihood group without ASD (EL-no-ASD); or (3) a low likelihood group with neurotypical outcome (LL), with the characteristics summarized in Table After exclusion, the final sample included 91 infants, with data from assessments performed at 10, 14, and 18 months of age  and no infant had any confirmed or suspected medical problems .All families provided written informed consent and the study was approved by the Regional Ethical Board in Stockholm. The study was conducted in accordance with the standards specified in the 1964 Declaration of Helsinki.n = 70), at 14 month of age 70.0% provided valid gaze data , and at 18 months of age 80.5% of infants provided valid gaze data .Participants in the EASE study undergo multiple measures and assessments including eye tracking  including other experiments  were defined. These included four oblong rectangles for each possible direction of the moving object and one AOI for the occluder. The size of each AOI was kept constant throughout the experiment see Fig. .n = 19). Next, we interpolated gaze data linearly over gaps shorter than 15 samples (i.e. 50 ms). All trials underwent visual inspection, blinded for infant identity and group status, in order to remove trials containing movement artefacts, noisy data, or missing data close to the occlusion event. Visual inspection was done by plotting the two-dimensional gaze data over time and included the AOIs for the trajectory of the moving object and the occluder . Gaze data were manually transposed so that the AOIs covered as much gaze as possible and accounted for gaze calibration drifts during the recording. Then, gaze velocity was calculated and plotted in order to identify the gaze shift latency towards an AOI after occlusion.Raw gaze coordinates were analyzed in MATLAB  using custom written scripts. First, we measured the time the object was completely occluded and time the object started to reappear again. These timestamps were then used to define a window of interest for the analysis. Occlusion always occurred 1120 ms before reappearance, and the former was defined as time point 0. Trials with less than 50% gaze data prior the event  were automatically discarded. Infants contributing with less than 4 trials were excluded from the analysis , and converted a percentage . All pupil measurements were taken from the left eye instead of the average of both eyes to avoid artifacts if the eye tracker lost track of one of the eyes.t-tests against 0 including the average adaptation rate and the first trial response were conducted in order to detect general effects regarding gaze shift latency and pupillary responses.The behavioral measures of the study were gaze shift latencies and pupillary responses as described above, which were measured both across trials within each testing session and across the three different time points . Individual trial values were used as the most basic dependent variables, and performance on the first trial was of particular interest. In a first step, we were interested in general effects in the entire sample, regardless of group and age. Bayesian one sample adaptation rates across trials for gaze shift latency and pupillary responses. Adaptation rate was operationalized as the slope of a linear regression within each participant with at least 4 valid trials  for each infant and measure, which is hereafter, termed The approach of testing regression slopes  instead of performing repeated measures analyses, makes it possible to include participants which had missing data for one of the time points. Testing the slope between groups is similar to testing the interaction effect between age and group in a repeated measures ANOVA, but does allow for missing data. An option would be to use Linear Mixed Models (LMMs), but because we use Bayesian statistics (see our motivation below) our approach provides a mathematically easier solution than using Bayesian LMMs. It is not possible to test for “main effects” of group when comparing slopes, but testing the average values across ages provides equivalent results. Together, the first trial values (similar to an intercept), the slope , and the average across ages, give thorough information about the collected data. For completeness, we also show data from specific ages.In the results section we present all statistical tests using the subsections (1) first trial gaze shift latency, (2) adaptation rate of gaze shift latency, (3) first trial pupil response, and (4) adaptation rate of pupil response.t-tests and ANOVAs implemented in JASP . The support for our hypotheses is described by the Bayes factor (BF). The BF10 describes the ratio between the evidence for the hypothesis H1 relative to another hypothesis H0, where the latter typically is the null hypothesis. For example, when using a Bayesian t-test, BF10 = 5 denotes that the data are five times more likely under the hypothesis H1 (i.e. that there is an effect) than under H0 (i.e. no effect). Conversely, the BF01 describes the likelihood of the data under H0. The strength of evidence is interpreted as follows: BF10 < 1, no evidence; BF10 = 1–3, anecdotal evidence for H1; BF10 = 3–10, moderate evidence for H1; BF10 = 10–30, strong evidence for H1; BF10 = 30–100, very strong evidence for H1; and BF10 > 100, extreme evidence for H1. The equivalent applies when reporting BF01 for H0.The data was analyzed using Bayesian t-tests and ANOVAs because Bayesian statistics can give the strength of evidence for the null hypothesis, which frequentist tests do not provide. In addition, using Bayesian statistic, we are provided with richer information on the difference of means and standard deviations, the influence of outliers, and power of the test.We chose to use Bayesian statistics instead of traditional frequentist A Bayesian ANOVAs revealed no indication of group differences in gaze shift latencies of the first trial at the different time points. Instead, there was moderate evidence for the null hypothesis (i.e. no group differences) at 10 and 14 months of age. At 18 months, we found anecdotal evidence for the null hypothesis.Regarding developmental change, there was moderate evidence for the null hypothesis in a Bayesian ANOVA. The finding suggests that infants with a subsequent diagnosis of ASD did not differ from neurotypically developing infants in terms of the change of first trial gaze shift latency across ages. In addition, we found anecdotal evidence for the null hypothesis regarding the average across ages, which further indicates that the gaze shift latencies on the first trial were similar in all groups .First, a Bayesian one sample BF01 = 4.718, see Table BF10 = 8.256, anecdotal evidence for differences between the EL-no-ASD and LL groups, BF10 = 1.214, and anecdotal evidence for the null hypothesis when comparing LL and EL-ASD, BF01 = 1.701.In a next step, Bayesian ANOVAs gave a similar result for the adaptation rate of gaze shift latencies at the different time points, with most support for the null hypothesis. We found anecdotal evidence for no group differences at 10 months of age and moderate evidence the null hypothesis at 14 months of age  suggesting that the first trial pupil response did not differ from baseline.Unexpectedly, testing the average across ages against the baseline value (100%) gave anecdotal evidence for the null hypothesis .First, a Bayesian one sample In a next step, we used Bayesian ANOVAs to test for group differences of the adaptation rates of pupillary responses at the different time points. The results showed moderate evidence for the null hypothesis at 10, 14 and 18 month of age.BFs > 3, see Table Regarding developmental change and average across ages, the results were similar, providing moderate evidence for the null hypothesis . In addition, we found moderate support for the null hypothesis, suggesting that there were no group differences in this measure . This result provide evidence in favor of the view that indeed there is pupil dilation to the first unexpected object reappearance.Given the surprising null effect for overall effect on pupil dilation on the first trial and the lack of overall adaptation, we used a Bayesian one sample BF01 = 6.37, moderate evidence for H0, see Table BF01 = 7.30, moderate evidence for H0, see Table BF01 = 2.68, see Table BF1o = 1.53, see Table BF10 = 1.498, anecdotal evidence for differences between the EL-ASD and the LL group, BF10 = 1. 131, and anecdotal evidence for the null hypothesis when comparing LL and EL-no-ASD groups, BF01 = 1.232. While there was some support for group differences, these differences were rather small and inconclusive. A Bayesian one-sample t-test against 0 revealed that the developmental change of pupillary responses after the direction reversal was no different than 0 .To further investigate how previous experiences influence expectations in the three groups, we used a similar approach to analyze another event within the stimuli. Specifically, when the moving object in reversed direction Fig. , observeThis longitudinal study compared infants who subsequently were diagnosed with ASD and neurotypical infants when reacting to unexpected object motion, using gaze shift latencies and pupillary responses. Young infants can to a large extent control their eyes, and both pupil size and eye movements are easy to measure reliably. By using a visual motion paradigm including temporary occlusion, we examined expectations of the directionality of moving objects and how these expectations were updated with respect to new, incoming information. Our findings suggest that, at least within the context studied here, updating predictive models of object motion appears to be intact in ASD at an early age, as all infants regardless of clinical outcome showed similar first trial responses and adaptation rates over time, both in terms of gaze shift latencies and pupillary responses. Across the various measures, we mostly found moderate support for the null-hypothesis, using Bayesian statistics. The only exception was that the adaptation rate of gaze shift latency at 18 months showed moderate evidence for a difference between the EL-no-ASD and the EL-ASD groups. With respect to this, the first trial gaze shift latency was highest in the EL-no-ASD group , suggesting that the adaptation rate in this group may reflect high initial values. Nevertheless, we noted that the adaptation rate was positive in the EL-ASD group and negative in the two other groups at this age. A future direction for research could be to include older children, as differences in the adaptation rates of gaze shift latency may only be visible at a later age. Relatedly, we also noted that descriptively, the developmental change of gaze shift latency was positive in the EL-ASD group and negative in the two other groups; however, there is no statistical evidence for a difference between groups. Rather, the null hypothesis received moderate support.In our visual motion task, the object moved along an unexpected trajectory, urging infants to update their predictions based on experiences from seeing the object on previous trials Below is the link to the electronic supplementary material. (PDF 669 kb)