SUPPLEMENTAL DIGITAL CONTENT to:
Risk of dementia and structural brain changes following non-neurological infections during 9-year follow-up
Annemieke M. Peters van Ton MD1, Esther M.C. Meijer-van Leijsen PhD2, Mayra I. Bergkamp MD2, Ewald M.
Bronkhorst PhD3, Peter Pickkers MD PhD1, Frank-Erik de Leeuw MD PhD2, Anil M. Tuladhar MD PhD2, Wilson F. Abdo MD PhD1
Corresponding author:
Dr. W.F. Abdo MD PhD
Radboud university medical center Department of Intensive Care Medicine Postbus 9101
6500 HB Nijmegen The Netherlands
Email: [email protected] Phone: +0031 (0) 243617273
Contents:
EXTENDED MATERIALS AND METHODS ON:
1. Neuropsychological examinations 2. Dementia diagnosis
3. The data collection of infectious events 4. Multiple imputation
5. Multivariable linear regression SUPPLEMENTAL FIGURES
Figure 1: Dementia incidence in the three infectious groups (A) and forest plots of the risk to develop dementia within 10 years (B).
Figure 2: Trajectory of cognitive (domain) scores during 9-year follow-up.
Figure 3: Trajectory of structural changes to the brain on cerebral MRI during 9-year follow-up.
Figure 4: Dementia subtypes
SUPPLEMENTAL REFERENCES
EXTENDEND MATERIALS AND METHODS
1. Neuropsychological examination
Verbal memory function was assessed by the three-trial version of the Rey Auditory Verbal Learning Test (RAVLT)(1). Visuospatial memory was assessed by the Rey’s Complex Figure Test (RCFT)(2). The Stroop test(3), the Paper and Pencil Memory Scanning Task(4), the Symbol-Digit Substitution Task, which is modified from the Symbol Digit Modalities Test(5), and a verbal fluency task(6) were used to evaluate speed of mental processes. And finally, attention was evaluated by the verbal series attention test (VSAT)(7). Speed-Accuracy Trade- Off (SAT) scores (accuracy (%)/reaction time) were calculated where appropriate to adjust for faults. Z-transformation was performed on raw test scores to compare performance across tests. Subsequently, compound scores for global cognitive function (cognitive index), memory (verbal and visuospatial memory), executive function (fluency, attention and concept shifting) and psychomotor speed were calculated as described previously(8).
2. Dementia diagnosis
Dementia diagnoses were not directly or solely based on the neuropsychological examinations performed within this study. Some participants (or family or caregivers) experienced cognitive complaints and were referred to the memory clinic of the Radboud Alzheimer Center, where patients were analyzed by a multidisciplinary team, and where diagnosis was based on DSM-IV criteria after thorough examinations. Others were invited to this center for the same evaluation, based on the findings within the study. The Mini-Mental State Examination (MMSE) was used as a first dementia screening tool and a MMSE score below 26, or a decline of 3 points or more from baseline was considered screen positive. A minority refused referral to the memory clinic, and in these cases, a panel consisting of a neurologist, clinical neuropsychologist, and geriatrician, reviewed all medical records, cognitive
assessments, and available MRI-scans, to evaluate whether a participant fulfilled the DSM-IV criteria for dementia. Age, educational level, and interference with daily living, confirmed by family or caregivers, were taken into account. For participants who were not available for follow-up assessments, medical records were reviewed and, additionally, we contacted their general practitioners and medical specialists for information on their cognitive status. If potential dementia was suspected, the panel members performed a similar review of all available data to evaluate whether participants fulfilled the DSM-IV criteria for dementia.
3. Infectious events
This additional data collection started in July 2016. Hospital medical records were screened for possible infections, antibiotics or antiviral medication use. In cases with possible infections, complete medical records were analyzed including physical exams and results from diagnostic testing. Furthermore, we contacted every patient’s general practitioner (GP) in order to retrieve information about infections which were diagnosed and treated in other hospitals or in the general practice. The GPs in The Netherlands act as gatekeepers within the healthcare system and always receive medical information of their patients concerning admission and discharge medical letters on hospitalizations. Antibiotics can only be prescribed by physicians (over the counter sale of antibiotics is not possible in The Netherlands). As such, the medical records of GPs will normally contain all information about hospitalizations or infections treated outside the hospital. GPs were asked to complete a questionnaire and if this was not possible a physician from the study team (APvT) visited the general practice to collect the required information from the patient’s medical file. As clinical diagnoses of sepsis were made up to 2015, the international criteria before 2016(9) were used by clinicians. For participants treated in our institute, or in the visited general practices, we verified the testament of the treating doctor with physiological parameters. Date and duration of the infectious episode, hospital admission, admission to the intensive care unit (ICU),
length of stay (both hospital and ICU), and culture results were recorded. Immune status was obtained from the patients’ medical files and by screening the pharmacy records for use of immunosuppressive drugs. Delirium episodes were based on the DSM-IV criteria.(10)
4. Multiple imputation
Multiple imputation was used to fill missing datapoints by using the mice library (version 3.6.3) in R (https://stefvanbuuren.name/mice/). In addition to the imputed variables necessary for the analyses, auxiliary variables were added to the imputation process as well. To this end, variables were selected that were correlated to the variables that were to be analyzed, such as measurements at other points in time and results from related outcomes. In the prediction process of missing values, predictive mean matching was used for numerical variables and logistic regression for dichotomous variables. The number of imputed datasets was 25.
In case of missing data, restricting the analyses to those cases with complete data generally leads to biased results. Under the condition that the value of the observation missing is not related to the missingness itself, correlations seen in the database within other patients can be used to fill in the gaps. Although mathematically it is a complicated process, it can be adequately described as an educated guess. By repeating this imputation process multiple times and synthesizing the analyses on the individual imputed datasets, a more powerful and less biased result is obtained than from analyses based on complete cases only.
5. Multivariable linear regression
To study the effects of infections on cognition and brain structure, multivariable linear regression was performed for continuous outcomes for each follow-up interval: 2006-2011, 2011-2015, and 2006-2015. The following independent variables were entered simultaneously: age, cognitive index, total brain, WMH, and hippocampal volume at baseline,
and the dichotomous variable cerebrovascular events during follow-up. To study the effect of infections, a nominal variable was added that discriminates the effect of “severe infection” vs
“no infection” and “mild infection” vs “no infection” for that specific follow-up interval.
To study the bidirectional interplay between infections and the brain, we performed multivariable linear regression in order to find factors associated with the susceptibility to develop a severe infection. Age, sex, the calendar month in which the baseline assessment took place, comorbidities at baseline (history of TIA, ischemic or hemorrhagic stroke, carotid endarterectomy, myocardial infarction, cancer, or ICU admission), immunocompromised state during follow-up, baseline total brain, WMH and hippocampal volume, baseline MD and FA of white matter, and baseline cognitive index were entered simultaneously as independent variables.
Supplemental Digital Content - Figure 1. Dementia incidence in the three infectious groups (A) and forest plots of the risk to develop dementia within 10 years (B).
B: Forest plots present the odds ratio with 95% confidence interval. Adjusted odds are adjusted for age, baseline cognitive index and baseline total brain volume; * p<0.05.
Abbreviations: OR: odds ratio.
Supplemental Digital Content - Figure 2. Trajectory of cognitive (domain) scores during 9-
year follow-up.
Medians are depicted with interquartile range (IQR); * p<0.05 according to Kruskal-Wallis test; MMSE: mini-mental state examination.
Supplemental Digital Content - Figure 3. Trajectory of structural changes to the brain on cerebral MRI during 9-year follow-up.
Medians are depicted with interquartile range (IQR). Kruskal-Wallis performed on deltas or ratios between follow-up intervals, none significant; NAWM: normal appearing white matter;
WMH: white matter hyperintensities.
Supplemental Digital Content – Figure 4. Dementia subtypes
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