Literature DB >> 26715157

Evidence for the low recording of weight status and lifestyle risk factors in the Danish National Registry of Patients, 1999-2012.

Mette Søgaard1, Uffe Heide-Jørgensen2, Mette Nørgaard3, Søren P Johnsen4, Reimar W Thomsen5.   

Abstract

BACKGROUND: To examine the prevalence of lifestyle diagnosis codes recorded in the Danish National Registry of Patients (DNRP).
METHODS: We identified all hospital contacts in Denmark 1999-2012 with a diagnosis of overweight, obesity, physical inactivity, current tobacco smoking, and/or excessive alcohol consumption. We computed the annual prevalence per 1000 hospital contacts of these diagnoses overall and by baseline characteristics.
RESULTS: Among 56,665,048 hospital contacts, the overall prevalence of recording per 1000 hospital contacts was 4.87 for a diagnosis of obesity, 2.36 for overweight, 2.90 for smoking, 0.39 for excessive alcohol consumption, and 0.47 for physical inactivity. Between 1999 and 2012, marked increases were noted for the prevalence of recorded obesity (30-fold, from 0.26 to 8.02), smoking (26-fold, from 0.18 to 4.88), and overweight (14-fold, from 0.23 to 3.52). Diagnosis coding of excessive alcohol consumption and physical inactivity remained at a very low level. The prevalence of recorded lifestyle risk factors varied substantially according to geographical regions, type of hospital contact, patient age, sex and underlying disease. In 2012, the prevalence of codes for obesity were highest among patients with diabetes (15.64 per 1000), COPD (12.95 per 1000), and congestive heart failure (11.24 per 1000). Codes for smoking were prevalent among patients with COPD (14.11 per 1000), liver disease (12.68 per 1000), and peripheral vascular disease (8.52 per 1000).
CONCLUSION: Despite increasing prevalence of adverse lifestyle risk factors recorded in the DNRP, the much higher prevalence of similar lifestyle risk factors in health surveys suggests that the completeness of coding in the DNRP remains poor.

Entities:  

Mesh:

Year:  2015        PMID: 26715157      PMCID: PMC4696325          DOI: 10.1186/s12889-015-2670-9

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   3.295


Background

During the last decades, the global disease burden has shifted from communicable to noncommunicable diseases including cardiovascular diseases, diabetes, cancers, and chronic respiratory diseases [1]. Worldwide, noncommunicable diseases were responsible for 54 % of all disability-adjusted life years [2] and 65 % of all deaths in 2010 [3]. Smoking, excessive alcohol use, unhealthy diet, and physical inactivity/obesity are the “big four” modifiable risk factors of this epidemic of noncommunicable diseases [4]. Therefore, strategies for prevention include lifestyle modification and adoption of healthy behaviors. In this context, physicians can play an important role through raising awareness and providing advice to patients with unhealthy behaviors. Nonetheless, prior studies suggest that physicians generally counsel only a minority of patients [5-8]. According to Hospital Accreditation Standards in Denmark and elsewhere, all inpatients and outpatients should be screened with regard to unhealthy lifestyle factors and offered intervention if their adverse lifestyle may influence treatment outcome or otherwise pose a risk for the patient [9]. Yet, it is unclear whether such screening actually occurs at hospitals and to which extent the results are recorded in hospital patient registries over time. Documentation of life style risk factors is important in order to provide continuity in care and to facilitate awareness of these factors during transitions of patient care. Therefore, we examined the prevalence of hospital contacts with a recorded diagnosis code for overweight, obesity, physical inactivity, tobacco, or alcohol consumption in the Danish National Registry of Patients (DNRP) from 1999 through 2012 and assessed whether this registration varied across Denmark’s geographical regions, by type of hospital contact, and according to patient age, sex, and underlying disease.

Methods

Setting and study population

Denmark has 5.6 million inhabitants, and the National Health Service provides universal tax-supported health care for all residents, including free access to primary care and hospitals. The country is divided into five regions which have the main responsibility for the provision of public hospital services – both somatic and psychiatric hospitals. Since 1977 the DNRP has tracked each hospital admission in Denmark and recorded dates of admission and discharge and up to 20 discharge diagnoses. The registry covers 99.4 % of all discharge records from Danish hospitals [10]. It allows for one principal diagnosis code given to the condition that prompted the patient’s admission and the main condition responsible for the completed diagnosis and treatment course and up to 20 secondary codes. The secondary diagnoses are given to conditions that coexist at the time of hospital admission or that develop during the hospital stay with no information as to which disease occurred first. The diagnoses are coded by physicians using the Danish version of the International Classification of Diseases, 8th revision (ICD-8) (1977–1993) and 10th revision (1994 onward). Since 1995, visits at hospital outpatient clinics and emergency rooms have been recorded in addition to the inpatient hospital stays.

Assessment of lifestyle risk factors

Data for this study were obtained for the period from 1999 through 2012. We identified all inpatient and outpatient hospital contacts with a recorded ICD-10 code for overweight, obesity, smoking, excessive alcohol consumption, and physical inactivity in the DNRP. Information on the patient’s lifestyle risk factors are usually obtained by physicians or nurses through patient interview and examination at the time of hospital admission. In 2005, the Danish National Board of Health initiated a project aiming to strengthen the prevention of lifestyle-related diseases through systematic registration of lifestyle risk factors [11]. In relation to this project, additional codes for recording of lifestyle risk factors were implemented along with a list of clinical questions and definitions for the individual risk factors in order to guide physicians and nurses when obtaining this information.

Statistical analysis

We computed the prevalence of all contacts (e.g., patients could be included in both the numerator and denominator more than once) with one or more of these codes recorded either as primary or secondary diagnoses per 1000 hospital contacts. We computed the prevalence overall and according to study year, health care region, contact type (inpatient vs. outpatient), age, gender, and underlying disease defined as the principal discharge diagnosis recorded in the DNRP. We assessed the recording of lifestyle risk factors in relation to the following underlying diseases: Myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, chronic obstructive pulmonary disease (COPD), diabetes, cancer, and liver disease. These diseases were chosen because they are strongly associated with the examined lifestyle risk factors. We would therefore expect one or more of the lifestyle risk factors to be prevalent in patients with these underlying diseases. To examine to which extent lifestyle risk factors were coded at first hospital contacts, we further restricted the analyses to patients with no hospital contacts within 10 years preceding the date of index admission. The ICD-10 codes used in the study appear in Additional file 1: Table S1. Analyses were performed using Statistical Analysis Software (v 9.2; SAS Institute, Inc, Cary, NC, USA).

Results

From 1999 through 2012, 56,665,048 hospital contacts occurred among 6,664,495 individual patients in Denmark, of which 39,244,611 (69 %) were outpatient clinic contacts and 17,420,437 (31 %) were inpatient hospitalization contacts. Figure 1 shows the annual prevalence of lifestyle risk factors recorded in the DNRP per 1,000 hospital contacts overall (Fig. 1a) and for first-time contacts in 10 years (Fig. 1b). As appears, obesity was by far the most frequently diagnosed lifestyle risk factor with a marked 30-fold increase over time from 0.26 per 1,000 contacts in 1999 to 8.02 in 2012. This increase was particularly steep between 2003 and 2007, with an 8-fold increase from 0.86 per 1000 contacts in 2003 to 7.88 in 2007. Over the study period, we also noted a 26-fold increase in the diagnosis coding of smoking (from 0.18 to 4.88 per 1000 contacts) and a 14-fold increase in the coding of overweight (from 0.23 to 3.52 per 1000 contacts). Similar to obesity, the increase was steepest between 2003 and 2007. Thereafter, increases appeared to level off. In comparison, diagnosis codes for excessive alcohol consumption remained at a very low level around 0.40–0.50 per 1000 hospital contacts throughout the study period. Codes for physical inactivity were infrequently used but increased in the latter half of the study period from 0.39 per 1,000 contacts in 2005 to 0.73 in 2011.
Fig. 1

Annual prevalence of codes for overweight, physical inactivity, smoking or excessive alcohol consumption in the Danish National Registry of Patients per 1,000 hospital contacts overall (a) and for first-time contacts within 10 years, 1999–2012 (b)

Annual prevalence of codes for overweight, physical inactivity, smoking or excessive alcohol consumption in the Danish National Registry of Patients per 1,000 hospital contacts overall (a) and for first-time contacts within 10 years, 1999–2012 (b) The presence of lifestyle risk factors was less frequently recoded at first vs. subsequent hospital contacts (Fig. 1b). For first contacts, the prevalence of obesity increased by 36 fold (from 0.11 per 1000 in 1999 to 4.05 in 2012), overweight by 14 fold (from 0.18 to 2.63), and smoking by 23 fold (from 0.14–3.32). For first contacts, the increases did not level off after 2007. Table 1 displays the prevalence of lifestyle risk factors recorded in the DNRP in 2012 according to type of hospital contact, geographical region, and patient age, sex and underlying disease. Most lifestyle factors were coded twice as often at inpatient than outpatient contacts. Overall, the prevalence of diagnosis coding varied by geographical region. In 2012 for instance, the prevalence of codes for obesity varied from 3.31 per 1000 contacts in the North Denmark Region to 21.37 per 1000 in Region Zealand. The prevalence of codes for obesity was markedly higher among females compared with males (10.76 per 1000 for obesity and 4.98 per 1,000 for overweight among females in 2012 vs. 4.22 and 1.50, respectively among males) whereas the prevalence of excessive alcohol intake was substantially higher among males (0.31 vs. 0.10 in females in 2012). Smoking codes were only slightly more prevalent among males (5.22 vs. 4.64 in 2012). For all lifestyle risk factors, the prevalence of recording was highest among adults below 50 years of age (Table 1).
Table 1

Annual prevalence of codes for overweight, physical inactivity, smoking, or excessive alcohol consumption in the Danish National Registry of Patients per 1,000 hospital contacts in 2012

ObesityOverweightSmokingAlcohol consumptionPhysical inactivity
Overall8.023.524.880.190.39
Type of contact
 Outpatient5.192.393.280.120.33
 Inpatient16.717.009.750.400.58
Health care region
 Capital Region of Denmark6.404.497.620.210.37
 Region Zealand21.374.934.640.140.04
 Region of Southern Denmark7.284.454.610.160.05
 Central Denmark Region4.831.231.880.250.78
 North Denmark Region3.311.854.970.110.83
Age group
 16–3410.226.824.510.070.15
 35–4910.233.725.870.190.34
 50–646.071.345.300.220.46
 65–796.942.854.640.260.58
 80+6.913.992.840.190.30
Sex
 Female10.764.984.640.100.36
 Male4.221.505.200.310.42
Underlying diseasea
 Myocardial infarction9.012.435.600.240.91
 Congestive heart failure11.243.155.550.450.41
 Peripheral vascular disease9.542.438.520.350.64
 Cerebrovascular disease7.812.805.810.400.34
 Chronic obstructive pulmonary disease12.955.7414.110.440.46
 Diabetes15.643.205.900.300.46
 Cancer6.592.234.820.200.41
 Liver disease8.732.0612.681.150.25

aThe underlying disease is defined as the principal discharge diagnosis recorded in the Danish National Registry of Patients

Annual prevalence of codes for overweight, physical inactivity, smoking, or excessive alcohol consumption in the Danish National Registry of Patients per 1,000 hospital contacts in 2012 aThe underlying disease is defined as the principal discharge diagnosis recorded in the Danish National Registry of Patients In 2012, codes for obesity were prevalent among patients with diabetes (15.64 per 1000), COPD (12.95 per 1000), and congestive heart failure (11.24 per 1000). Codes for smoking were prevalent among patients with COPD (14.11 per 1000), liver disease (12.68 per 1000), and peripheral vascular disease (8.52 per 1000) (Table 1).

Discussion

Our findings demonstrate that the nationwide recording of lifestyle risk factors in the DNRP is low but has increased substantially over the last 15 years, in particular for obesity, overweight, and smoking. Our study design only allowed us to examine the recording of lifestyle in the DNRP. The optimal study would also examine sensitivity and specificity of the registrations, i.e., compared with a gold standard for presence or absence of each lifestyle factor in a given patient. Our estimates may reflect both changes in the actual prevalence of these lifestyle habits in the Danish population and the physician’s changing use of the available codes. Recent survey data showed that 47 % of the Danish general population are overweight and 14 % are obese, 17 % smoke daily, 16 % are physical inactive to a degree that may adversely affect their health, and 9 % drink more than the latest recommended maximum levels provided by The Danish Health and Medicines Authority [12]. Thus, in comparison our estimates suggest that the completeness of registration of lifestyle habits in Danish hospitals is very low, not least because patients with hospital contact with acute and chronic diseases generally have a higher prevalence of unhealthy lifestyle factors than the general population [13-15]. This low completeness is especially troubling given the increasing prevalence of obesity, sedentary lifestyle, and lifestyle related chronic noncommunicable diseases nationally [16, 17]. For example, primary data show that 88 % of patients with newly diagnosed type 2 diabetes in Denmark are either overweight or obese [18], compared with 2 % of patients with diabetes coded with overweight per DNRP contact in our study. Among patients with COPD seen in Danish outpatient clinics, 33 % are known to be active smokers and 64 % are former smokers [19], compared with a prevalence of recorded tobacco smoking in the DNRP in 2012 of only 14.11 per 1000 contacts among patients with COPD in our study. Systematic patient assessment and documentation is important to ensure that risk factors are identified and that all patients are offered relevant counselling and intervention when needed. The documentation is vital to inform subsequent investigations, treatment, care and follow up [20]. The recording of lifestyle risk factors is a simple means to ensure communication across the health care system (e.g., when discharging a patient from hospital with referral to primary care). Failure to record and communicate information about a patient’s adverse lifestyle at hospital level could in this context be seen as a missed opportunity for ensuring continuity in care in general and in risk factor management in particular. In worst case, primary care physicians may perceive this lack of attention to life style factors as an indication that the hospital does not endorse risk-lowering interventions. This could potentially have serious implications since the primary care sector, due to the high population reach [21] and the patients’ general acceptance of the role of primary care providers in preventive care [22], play a key role in implementing life style modifying interventions. The Danish National Board of Health has aimed at strengthening the prevention of lifestyle-related diseases through systematic registration of overweight, smoking, excessive alcohol use, and physical inactivity in hospital medical records of hospitalized patients [11]. Subsequently, the screening was also included in the Danish accreditation standards, which have been mandatory at all public hospitals since 2009 [9]. The increasing use of codes for obesity, overweight, and smoking since 2003 may reflect these initiatives, although increases in the underlying prevalence of e.g. overweight among patients with hospital contacts may also have contributed. However, despite the formal requirements and the existing knowledge on the importance of lifestyle risk factors for treatment and prognosis, systematic recording of lifestyle in the hospital setting remain underutilized. A range of factors may explain this phenomenon. First, the physician and hospital department treating the patient may be reluctant to prioritize the recording due to time constraints and existing demands for recording of a widespread range of other data in relation to each patient contact. Second, the low priority given to recording of lifestyle risk factors may be supported by the fact that individual physician or hospital department will not experience any immediate benefit from their efforts. Third, there are no financial incentives to record the information. A more complete recording in the DNRP will require that these challenges are addressed, e.g., by ensuring more simple and user-friendly IT systems and a revision of the hospital reimbursement system to take into account individual patient characteristics such as adverse lifestyle that may prolong hospital care, complicate treatment, and ultimately influence patient outcomes. We were unable to assess whether physicians, nurses, or other caregivers actually had asked for lifestyle risk factors and offered counseling to their patients, without coding the presence of any lifestyle risk factor in the DNRP. Since the early 2000s, the Danish health care authorities have initiated continuous monitoring of the quality of care provided by all Danish public hospitals to patients with a number of important diseases, including diabetes, COPD, heart failure, stroke, and cancer [23]. Nationwide clinical quality of care databases now exist for more than 60 different diseases and conditions in Denmark [24]. At least 10–15 of these quality databases systematically collect primary data on body mass index, smoking, and alcohol intake for most (>80 %) of their patients. The databases include patients with any hospital contact with e.g. diabetes in the Danish Diabetes Database for Adults [25], stroke in the Danish Stroke Registry [26], and outpatients with COPD in the Danish Clinical Register of COPD [19]. For a few of these conditions (e.g. COPD outpatients, or patients with hip fracture), selected lifestyle data are actually recorded directly via codes in the DNRP. This fact likely explains the increasing prevalence of e.g. diagnosis codes for tobacco smoking observed in patients with COPD in our study. For other conditions, the nationwide set-up with good coverage of several lifestyle risk factors for the patients in dedicated clinical databases illustrate the discrepancy between the assessment of lifestyle risk factors in everyday clinical practice, and the recording of this information in the DNRP.

Conclusion

In conclusion, our study shows that – compared with knowledge from population surveys and clinical quality databases – the completeness of diagnosis codes for lifestyle risk factors recorded in the DNRP is very low. Since unhealthy and modifiable lifestyle risk factors are strong determinants for the incidence and development of leading causes of morbidity and mortality, more complete data on these factors should be a national health care priority as it may assist in targeting preventive efforts.
  20 in total

1.  Defining and classifying clinical indicators for quality improvement.

Authors:  Jan Mainz
Journal:  Int J Qual Health Care       Date:  2003-12       Impact factor: 2.038

2.  Lifestyle profile among statin users.

Authors:  Reimar Wernich Thomsen; Rikke Beck Nielsen; Mette Nørgaard; Henriette Thisted Horsdal; Til Stürmer; Finn Breinholt Larsen; Henrik Toft Sørensen
Journal:  Epidemiology       Date:  2013-07       Impact factor: 4.822

3.  Rates of U.S. physicians counseling adolescents about smoking.

Authors:  A N Thorndike; T G Ferris; R S Stafford; N A Rigotti
Journal:  J Natl Cancer Inst       Date:  1999-11-03       Impact factor: 13.506

4.  The Danish National Health Survey 2010. Study design and respondent characteristics.

Authors:  Anne Illemann Christensen; Ola Ekholm; Charlotte Glümer; Anne Helms Andreasen; Michael Falk Hvidberg; Peter Lund Kristensen; Finn Breinholt Larsen; Britta Ortiz; Knud Juel
Journal:  Scand J Public Health       Date:  2012-06       Impact factor: 3.021

5.  A silent response to the obesity epidemic: decline in US physician weight counseling.

Authors:  Jennifer L Kraschnewski; Christopher N Sciamanna; Heather L Stuckey; Cynthia H Chuang; Erik B Lehman; Kevin O Hwang; Lisa L Sherwood; Harriet B Nembhard
Journal:  Med Care       Date:  2013-02       Impact factor: 2.983

6.  Estimating prevalence of common chronic morbidities in Australia.

Authors:  Stephanie A Knox; Christopher M Harrison; Helena C Britt; Joan V Henderson
Journal:  Med J Aust       Date:  2008-07-21       Impact factor: 7.738

7.  Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010.

Authors:  Christopher J L Murray; Theo Vos; Rafael Lozano; Mohsen Naghavi; Abraham D Flaxman; Catherine Michaud; Majid Ezzati; Kenji Shibuya; Joshua A Salomon; Safa Abdalla; Victor Aboyans; Jerry Abraham; Ilana Ackerman; Rakesh Aggarwal; Stephanie Y Ahn; Mohammed K Ali; Miriam Alvarado; H Ross Anderson; Laurie M Anderson; Kathryn G Andrews; Charles Atkinson; Larry M Baddour; Adil N Bahalim; Suzanne Barker-Collo; Lope H Barrero; David H Bartels; Maria-Gloria Basáñez; Amanda Baxter; Michelle L Bell; Emelia J Benjamin; Derrick Bennett; Eduardo Bernabé; Kavi Bhalla; Bishal Bhandari; Boris Bikbov; Aref Bin Abdulhak; Gretchen Birbeck; James A Black; Hannah Blencowe; Jed D Blore; Fiona Blyth; Ian Bolliger; Audrey Bonaventure; Soufiane Boufous; Rupert Bourne; Michel Boussinesq; Tasanee Braithwaite; Carol Brayne; Lisa Bridgett; Simon Brooker; Peter Brooks; Traolach S Brugha; Claire Bryan-Hancock; Chiara Bucello; Rachelle Buchbinder; Geoffrey Buckle; Christine M Budke; Michael Burch; Peter Burney; Roy Burstein; Bianca Calabria; Benjamin Campbell; Charles E Canter; Hélène Carabin; Jonathan Carapetis; Loreto Carmona; Claudia Cella; Fiona Charlson; Honglei Chen; Andrew Tai-Ann Cheng; David Chou; Sumeet S Chugh; Luc E Coffeng; Steven D Colan; Samantha Colquhoun; K Ellicott Colson; John Condon; Myles D Connor; Leslie T Cooper; Matthew Corriere; Monica Cortinovis; Karen Courville de Vaccaro; William Couser; Benjamin C Cowie; Michael H Criqui; Marita Cross; Kaustubh C Dabhadkar; Manu Dahiya; Nabila Dahodwala; James Damsere-Derry; Goodarz Danaei; Adrian Davis; Diego De Leo; Louisa Degenhardt; Robert Dellavalle; Allyne Delossantos; Julie Denenberg; Sarah Derrett; Don C Des Jarlais; Samath D Dharmaratne; Mukesh Dherani; Cesar Diaz-Torne; Helen Dolk; E Ray Dorsey; Tim Driscoll; Herbert Duber; Beth Ebel; Karen Edmond; Alexis Elbaz; Suad Eltahir Ali; Holly Erskine; Patricia J Erwin; Patricia Espindola; Stalin E Ewoigbokhan; Farshad Farzadfar; Valery Feigin; David T Felson; Alize Ferrari; Cleusa P Ferri; Eric M Fèvre; Mariel M Finucane; Seth Flaxman; Louise Flood; Kyle Foreman; Mohammad H Forouzanfar; Francis Gerry R Fowkes; Marlene Fransen; Michael K Freeman; Belinda J Gabbe; Sherine E Gabriel; Emmanuela Gakidou; Hammad A Ganatra; Bianca Garcia; Flavio Gaspari; Richard F Gillum; Gerhard Gmel; Diego Gonzalez-Medina; Richard Gosselin; Rebecca Grainger; Bridget Grant; Justina Groeger; Francis Guillemin; David Gunnell; Ramyani Gupta; Juanita Haagsma; Holly Hagan; Yara A Halasa; Wayne Hall; Diana Haring; Josep Maria Haro; James E Harrison; Rasmus Havmoeller; Roderick J Hay; Hideki Higashi; Catherine Hill; Bruno Hoen; Howard Hoffman; Peter J Hotez; Damian Hoy; John J Huang; Sydney E Ibeanusi; Kathryn H Jacobsen; Spencer L James; Deborah Jarvis; Rashmi Jasrasaria; Sudha Jayaraman; Nicole Johns; Jost B Jonas; Ganesan Karthikeyan; Nicholas Kassebaum; Norito Kawakami; Andre Keren; Jon-Paul Khoo; Charles H King; Lisa Marie Knowlton; Olive Kobusingye; Adofo Koranteng; Rita Krishnamurthi; Francine Laden; Ratilal Lalloo; Laura L Laslett; Tim Lathlean; Janet L Leasher; Yong Yi Lee; James Leigh; Daphna Levinson; Stephen S Lim; Elizabeth Limb; John Kent Lin; Michael Lipnick; Steven E Lipshultz; Wei Liu; Maria Loane; Summer Lockett Ohno; Ronan Lyons; Jacqueline Mabweijano; Michael F MacIntyre; Reza Malekzadeh; Leslie Mallinger; Sivabalan Manivannan; Wagner Marcenes; Lyn March; David J Margolis; Guy B Marks; Robin Marks; Akira Matsumori; Richard Matzopoulos; Bongani M Mayosi; John H McAnulty; Mary M McDermott; Neil McGill; John McGrath; Maria Elena Medina-Mora; Michele Meltzer; George A Mensah; Tony R Merriman; Ana-Claire Meyer; Valeria Miglioli; Matthew Miller; Ted R Miller; Philip B Mitchell; Charles Mock; Ana Olga Mocumbi; Terrie E Moffitt; Ali A Mokdad; Lorenzo Monasta; Marcella Montico; Maziar Moradi-Lakeh; Andrew Moran; Lidia Morawska; Rintaro Mori; Michele E Murdoch; Michael K Mwaniki; Kovin Naidoo; M Nathan Nair; Luigi Naldi; K M Venkat Narayan; Paul K Nelson; Robert G Nelson; Michael C Nevitt; Charles R Newton; Sandra Nolte; Paul Norman; Rosana Norman; Martin O'Donnell; Simon O'Hanlon; Casey Olives; Saad B Omer; Katrina Ortblad; Richard Osborne; Doruk Ozgediz; Andrew Page; Bishnu Pahari; Jeyaraj Durai Pandian; Andrea Panozo Rivero; Scott B Patten; Neil Pearce; Rogelio Perez Padilla; Fernando Perez-Ruiz; Norberto Perico; Konrad Pesudovs; David Phillips; Michael R Phillips; Kelsey Pierce; Sébastien Pion; Guilherme V Polanczyk; Suzanne Polinder; C Arden Pope; Svetlana Popova; Esteban Porrini; Farshad Pourmalek; Martin Prince; Rachel L Pullan; Kapa D Ramaiah; Dharani Ranganathan; Homie Razavi; Mathilda Regan; Jürgen T Rehm; David B Rein; Guiseppe Remuzzi; Kathryn Richardson; Frederick P Rivara; Thomas Roberts; Carolyn Robinson; Felipe Rodriguez De Leòn; Luca Ronfani; Robin Room; Lisa C Rosenfeld; Lesley Rushton; Ralph L Sacco; Sukanta Saha; Uchechukwu Sampson; Lidia Sanchez-Riera; Ella Sanman; David C Schwebel; James Graham Scott; Maria Segui-Gomez; Saeid Shahraz; Donald S Shepard; Hwashin Shin; Rupak Shivakoti; David Singh; Gitanjali M Singh; Jasvinder A Singh; Jessica Singleton; David A Sleet; Karen Sliwa; Emma Smith; Jennifer L Smith; Nicolas J C Stapelberg; Andrew Steer; Timothy Steiner; Wilma A Stolk; Lars Jacob Stovner; Christopher Sudfeld; Sana Syed; Giorgio Tamburlini; Mohammad Tavakkoli; Hugh R Taylor; Jennifer A Taylor; William J Taylor; Bernadette Thomas; W Murray Thomson; George D Thurston; Imad M Tleyjeh; Marcello Tonelli; Jeffrey A Towbin; Thomas Truelsen; Miltiadis K Tsilimbaris; Clotilde Ubeda; Eduardo A Undurraga; Marieke J van der Werf; Jim van Os; Monica S Vavilala; N Venketasubramanian; Mengru Wang; Wenzhi Wang; Kerrianne Watt; David J Weatherall; Martin A Weinstock; Robert Weintraub; Marc G Weisskopf; Myrna M Weissman; Richard A White; Harvey Whiteford; Natasha Wiebe; Steven T Wiersma; James D Wilkinson; Hywel C Williams; Sean R M Williams; Emma Witt; Frederick Wolfe; Anthony D Woolf; Sarah Wulf; Pon-Hsiu Yeh; Anita K M Zaidi; Zhi-Jie Zheng; David Zonies; Alan D Lopez; Mohammad A AlMazroa; Ziad A Memish
Journal:  Lancet       Date:  2012-12-15       Impact factor: 79.321

8.  The Danish Centre for Strategic Research in Type 2 Diabetes (DD2): organization of diabetes care in Denmark and supplementary data sources for data collection among DD2 study participants.

Authors:  Reimar Wernich Thomsen; Søren Friborg; Jens Steen Nielsen; Henrik Schroll; Søren Paaske Johnsen
Journal:  Clin Epidemiol       Date:  2012-09-21       Impact factor: 4.790

9.  The Danish Centre for Strategic Research in Type 2 Diabetes (DD2) study: Collection of baseline data from the first 580 patients.

Authors:  Reimar Wernich Thomsen; Jens Steen Nielsen; Sinna Pilgaard Ulrichsen; Lars Pedersen; Anne-Marie Sigsgaard Hansen; Tove Nilsson
Journal:  Clin Epidemiol       Date:  2012-09-21       Impact factor: 4.790

10.  The new global health.

Authors:  Kevin M De Cock; Patricia M Simone; Veronica Davison; Laurence Slutsker
Journal:  Emerg Infect Dis       Date:  2013-08       Impact factor: 6.883

View more
  9 in total

1.  Mortality after Transplantation for Hepatocellular Carcinoma: A Study from the European Liver Transplant Registry.

Authors:  Hans-Christian Pommergaard; Andreas Arendtsen Rostved; René Adam; Allan Rasmussen; Mauro Salizzoni; Miguel Angel Gómez Bravo; Daniel Cherqui; Paolo De Simone; Pauline Houssel-Debry; Vincenzo Mazzaferro; Olivier Soubrane; Juan Carlos García-Valdecasas; Joan Fabregat Prous; Antonio D Pinna; John O'Grady; Vincent Karam; Christophe Duvoux; Lau Caspar Thygesen
Journal:  Liver Cancer       Date:  2020-05-12       Impact factor: 11.740

2.  Hospital contacts with alcohol problems prior to liver cirrhosis or pancreatitis diagnosis.

Authors:  Gro Askgaard; Søren Neermark; David A Leon; Mette S Kjær; Janne S Tolstrup
Journal:  World J Hepatol       Date:  2017-12-28

3.  Risk of cardiovascular events and pulmonary hypertension following splenectomy - a Danish population-based cohort study from 1996-2012.

Authors:  Marianne Rørholt; Waleed Ghanima; Dora Körmendiné Farkas; Mette Nørgaard
Journal:  Haematologica       Date:  2017-06-01       Impact factor: 9.941

4.  Effect modification, interaction and mediation: an overview of theoretical insights for clinical investigators.

Authors:  Priscila Corraini; Morten Olsen; Lars Pedersen; Olaf M Dekkers; Jan P Vandenbroucke
Journal:  Clin Epidemiol       Date:  2017-06-08       Impact factor: 4.790

5.  Confounding in observational studies based on large health care databases: problems and potential solutions - a primer for the clinician.

Authors:  Mette Nørgaard; Vera Ehrenstein; Jan P Vandenbroucke
Journal:  Clin Epidemiol       Date:  2017-03-28       Impact factor: 4.790

6.  Partner Bereavement and Risk of Herpes Zoster: Results from Two Population-Based Case-Control Studies in Denmark and the United Kingdom.

Authors:  Sigrun A J Schmidt; Mogens Vestergaard; Henrik S Pedersen; Henrik C Schønheyder; Sara L Thomas; Liam Smeeth; Kathryn E Mansfield; Henrik T Sørensen; Harriet J Forbes; Sinéad M Langan
Journal:  Clin Infect Dis       Date:  2017-03-01       Impact factor: 9.079

7.  Validity of ICD-10 diagnoses of overweight and obesity in Danish hospitals.

Authors:  Sigrid Bjerge Gribsholt; Lars Pedersen; Bjørn Richelsen; Reimar Wernich Thomsen
Journal:  Clin Epidemiol       Date:  2019-09-11       Impact factor: 4.790

8.  Metformin use and long-term risk of benign prostatic hyperplasia: a population-based cohort study.

Authors:  Mette Nørgaard; Bianka Darvalics; Reimar Wernich Thomsen
Journal:  BMJ Open       Date:  2020-12-22       Impact factor: 2.692

9.  Use of histamine H2 receptor antagonists and outcomes in patients with heart failure: a nationwide population-based cohort study.

Authors:  Kasper Adelborg; Jens Sundbøll; Morten Schmidt; Hans Erik Bøtker; Noel S Weiss; Lars Pedersen; Henrik Toft Sørensen
Journal:  Clin Epidemiol       Date:  2018-05-07       Impact factor: 4.790

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.