The Impact of Delirium on Recovery in Geriatric Rehabilitation After Acute Infection

OBJECTIVES

Delirium is common during acute infection in older patients and is associated with functional decline. Geriatric rehabilitation (GR) can help older patients to return to their premorbid functional level. It is unknown whether delirium affects GR outcomes in patients with acute infection. We evaluated whether delirium affects trajectories of activities of daily living (ADL) and quality of life (QoL) recovery in GR after COVID-19 infection.

DESIGN

This study was part of the EU-COGER study, a multicenter cohort study conducted between October 2020 and October 2021.

SETTING AND PARTICIPANTS

Participants were recruited after COVID-19 infection from 59 GR centers in 10 European countries.

METHODS

Data were collected at GR admission, discharge, and at the 6-week and 6-month follow-ups. Trajectories of ADL [using the Barthel index (BI)] and QoL [using the EuroQol-5 Dimensions-5 Level (EQ-5D-5L)] recovery were examined using linear mixed models.

RESULTS

Of the 723 patients included (mean age 75.5 ± 9.9 years; 52.4% male), 28.9% had delirium before or during GR admission. Participants with delirium recovered in ADL at approximately the same rate as those without (linear slope effect = -0.13, SE 0.16, P = .427) up to an estimated BI score of 16.1 at 6 months. Similarly, participants with delirium recovered in QoL at approximately the same rate as those without (linear slope effect = -0.017, SE 0.015, P = .248), up to an estimated EQ-5D-5L score of 0.8 at 6 months.

CONCLUSIONS AND IMPLICATIONS

Presence of delirium during the acute phase of infection or subsequent GR did not influence the recovery trajectory of ADL functioning and QoL.

External validation of six COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting

OBJECTIVES

To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care, and nursing homes.

STUDY DESIGN AND SETTING

This retrospective external validation study included 14,092 older individuals of ≥70 years of age with a clinical or polymerase chain reaction-confirmed COVID-19 diagnosis from March 2020 to December 2020. The six validation cohorts include three hospital-based (CliniCo, COVID-OLD, COVID-PREDICT), two primary care-based (Julius General Practitioners Network/Academisch network huisartsgeneeskunde/Network of Academic general Practitioners, PHARMO), and one nursing home cohort (YSIS) in the Netherlands. Based on a living systematic review of COVID-19 prediction models using Prediction model Risk Of Bias ASsessment Tool for quality and risk of bias assessment and considering predictor availability in validation cohorts, we selected six prognostic models predicting mortality risk in adults with COVID-19 infection (GAL-COVID-19 mortality, 4C Mortality Score, National Early Warning Score 2-extended model, Xie model, Wang clinical model, and CURB65 score). All six prognostic models were validated in the hospital cohorts and the GAL-COVID-19 mortality model was validated in all three healthcare settings. The primary outcome was in-hospital mortality for hospitals and 28-day mortality for primary care and nursing home settings. Model performance was evaluated in each validation cohort separately in terms of discrimination, calibration, and decision curves. An intercept update was performed in models indicating miscalibration followed by predictive performance re-evaluation.

MAIN OUTCOME MEASURE

In-hospital mortality for hospitals and 28-day mortality for primary care and nursing home setting.

RESULTS

All six prognostic models performed poorly and showed miscalibration in the older population cohorts. In the hospital settings, model performance ranged from calibration-in-the-large -1.45 to 7.46, calibration slopes 0.24-0.81, and C-statistic 0.55-0.71 with 4C Mortality Score performing as the most discriminative and well-calibrated model. Performance across health-care settings was similar for the GAL-COVID-19 model, with a calibration-in-the-large in the range of -2.35 to -0.15 indicating overestimation, calibration slopes of 0.24-0.81 indicating signs of overfitting, and C-statistic of 0.55-0.71.

CONCLUSION

Our results show that most prognostic models for predicting mortality risk performed poorly in the older population with COVID-19, in each health-care setting: hospital, primary care, and nursing home settings. Insights into factors influencing predictive model performance in the older population are needed for pandemic preparedness and reliable prognostication of health-related outcomes in this demographic.

Limited incremental predictive value of the frailty index and other vulnerability measures from routine care data for mortality risk prediction in older patients with COVID-19 in primary care

BACKGROUND

During the COVID-19 pandemic, older patients in primary care were triaged based on their frailty or assumed vulnerability for poor outcomes, while evidence on the prognostic value of vulnerability measures in COVID-19 patients in primary care was lacking. Still, knowledge on the role of vulnerability is pivotal in understanding the resilience of older people during acute illness, and hence important for future pandemic preparedness. Therefore, we assessed the predictive value of different routine care-based vulnerability measures in addition to age and sex for 28-day mortality in an older primary care population of patients with COVID-19.

METHODS

From primary care medical records using three routinely collected Dutch primary care databases, we included all patients aged 70 years or older with a COVID-19 diagnosis registration in 2020 and 2021. All-cause mortality was predicted using logistic regression based on age and sex only (basic model), and separately adding six vulnerability measures: renal function, cognitive impairment, number of chronic drugs, Charlson Comorbidity Index, Chronic Comorbidity Score, and a Frailty Index. Predictive performance of the basic model and the six vulnerability models was compared in terms of area under the receiver operator characteristic curve (AUC), index of prediction accuracy and the distribution of predicted risks.

RESULTS

Of the 4,065 included patients, 9% died within 28 days after COVID-19 diagnosis. Predicted mortality risk ranged between 7-26% for the basic model including age and sex, changing to 4-41% by addition of comorbidity-based vulnerability measures (Charlson Comorbidity Index, Chronic Comorbidity Score), more reflecting impaired organ functioning. Similarly, the AUC of the basic model slightly increased from 0.69 (95%CI 0.66 - 0.72) to 0.74 (95%CI 0.71 - 0.76) by addition of either of these comorbidity scores. Addition of a Frailty Index, renal function, the number of chronic drugs or cognitive impairment yielded no substantial change in predictions.

CONCLUSION

In our dataset of older COVID-19 patients in primary care, the 28-day mortality fraction was substantial at 9%. Six different vulnerability measures had little incremental predictive value in addition to age and sex in predicting short-term mortality.

Frailty in Non-geriatric Patients With Head and Neck cancer

OBJECTIVE

Patients with head and neck cancer (HNC) are characterized by a poor lifestyle and comorbidity. The Geriatric 8 (G8) is an established screening tool to identify frail older patients with cancer. However, studies evaluating frailty in younger HNC patients are lacking. The aim of this study is to evaluate if the G8 can identify frailty and if it is related to mortality in younger HNC patients.

STUDY DESIGN

Case-control study design.

SETTING

Tertiary cancer center.

METHODS

We studied patients <70 years with HNC. Patients with G8 ≤ 14 were considered frail. Patients were matched to nonfrail (G8 > 14) control patients. Patients were matched according to sex, age, smoking, tumor location, and period of first consultation. Baseline health characteristics were compared between frail patients and nonfrail controls. Second, the treatment plan and adverse outcomes were compared.

RESULTS

Forty-five patients with G8 ≤ 14 were included and matched to 90 nonfrail controls. The median follow-up time was 357 days. Frail patients had a significantly lower body mass index and level of education, a worse World Health Organization performance status, and reported lower experienced overall health. 28.9% of the frail patients died after 1 year versus 10% of the nonfrail control patients (hazard ratio: 3.87 [95% confidence interval: 1.32-11.36], p = 0.014).

CONCLUSION

The G8 is a valid screening tool to identify frail patients in younger HNC patients.

Delirium in older patients with COVID-19: Prevalence, risk factors and clinical outcomes across the first three waves of the pandemic

OBJECTIVES

Delirium is a serious condition, which poses treatment challenges during hospitalisation for COVID-19. Improvements in testing, vaccination and treatment might have changed patient characteristics and outcomes through the pandemic. We evaluated whether the prevalence and risk factors for delirium, and the association of delirium with in-hospital mortality changed through the pandemic.

METHODS

This study was part of the COVID-OLD study in 19 Dutch hospitals including patients ≥70 years in the first (spring 2020), second (autumn 2020) and third wave (autumn 2021). Multivariable logistic regression models were used to study risk factors for delirium, and in-hospital mortality. Differences in effect sizes between waves were studied by including interaction terms between wave and risk factor in logistic regression models.

RESULTS

1540, 884 and 370 patients were included in the first, second and third wave, respectively. Prevalence of delirium in the third wave (12.7%) was significantly lower compared to the first (22.5%) and second wave (23.5%). In multivariable-adjusted analyses, pre-existing memory problems was a consistent risk factor for delirium across waves. Previous delirium was a risk factor for delirium in the first wave (OR 4.02), but not in the second (OR 1.61) and third wave (OR 2.59, p-value interaction-term 0.028). In multivariable-adjusted analyses, delirium was not associated with in-hospital mortality in all waves.

CONCLUSION

Delirium prevalence declined in the third wave, which might be the result of vaccination and improved treatment strategies. Risk factors for delirium remained consistent across waves, although some attenuation was seen in the second wave.

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.

Cardiovascular Risk Management for All Older Patients?

Current guidelines on cardiovascular risk management are extrapolated to all older adults. It is, however, highly debatable whether recommendations also apply for patients with dementia since previous studies have not included this specific population. Time to benefit as well as higher risk of adverse events play a crucial role in the decision process of prescribing or deprescribing. Regular monitoring is needed in older patients with dementia, in order to make individual-based treatment strategies. Cardiovascular risk management in older patients with dementia should focus on quality of life, preventing cognitive and functional deterioration, and maintaining independence.

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting

BACKGROUND

The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting.

METHODS

Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated.

DISCUSSION

Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

Atypical presentation of COVID-19 in older patients is associated with frailty but not with adverse outcomes

PURPOSE

Older patients with COVID-19 can present with atypical complaints, such as falls or delirium. In other diseases, such an atypical presentation is associated with worse clinical outcomes. However, it is not known whether this extends to COVID-19. We aimed to study the association between atypical presentation of COVID-19, frailty and adverse outcomes, as well as the incidence of atypical presentation.

METHODS

We conducted a retrospective observational multi-center cohort study in eight hospitals in the Netherlands. We included patients aged ≥ 70 years hospitalized with COVID-19 between February 2020 until May 2020. Atypical presentation of COVID-19 was defined as presentation without fever, cough and/or dyspnea. We collected data concerning symptoms on admission, demographics and frailty parameters [e.g., Charlson Comorbidity Index (CCI) and Clinical Frailty Scale (CFS)]. Outcome data included Intensive Care Unit (ICU) admission, discharge destination and 30-day mortality.

RESULTS

We included 780 patients, 9.5% (n = 74) of those patients had an atypical presentation. Patients with an atypical presentation were older (80 years, IQR 76-86 years; versus 79 years, IQR 74-84, p = 0.044) and were more often classified as severely frail (CFS 6-9) compared to patients with a typical presentation (47.6% vs 28.7%, p = 0.004). Overall, there was no significant difference in 30-day mortality between the two groups in univariate analysis (32.4% vs 41.5%; p = 0.173) or in multivariate analysis [OR 0.59 (95% CI 0.34-1.0); p = 0.058].

CONCLUSIONS

In this study, patients with an atypical presentation of COVID-19 were more frail compared to patients with a typical presentation. Contrary to our expectations, an atypical presentation was not associated with worse outcomes.

A prospective, multicentre study to assess frailty in elderly patients with leg ulcers (GERAS study)

BACKGROUND

Although leg ulcers are a burdensome disease most common in those aged 65 years and older, frailty in this population has not yet been well established.

OBJECTIVES

The aim of this study was to prospectively explore and compare the presence of frailty in elderly patients with chronic leg or foot ulcers by applying different validated frailty screening methods in three healthcare settings and to assess the feasibility of frailty screening.

METHODS

We compared frailty of leg ulcer patients referred to an academic hospital with a non-academic hospital, leg ulcer patients receiving (primary) homecare, and a dermato-oncology patient population (control group). Frailty and quality of life were assessed using four validated questionnaires: the Groninger Frailty Indicator, Geriatric-8, Mini-Cog and Wound Quality of Life. To analyse data multiple (non)-parametric tests were performed.

RESULTS

Fifty of 60 included leg ulcer patients (83%) scored "frail" on at least one frailty questionnaire (GFI, G8 or Mini-Cog). The number of patients scoring "frail" on two or three out of three applied frailty questionnaires were significantly higher in the academic and homecare ulcer population compared with the non-academic ulcer population and control group (p = 0.002). In the academic ulcer population mean Wound Quality of Life scores were 30.2 (SD 17.6), compared with 17.7 (SD 13.1) in the non-academic and 15.0 (SD 10.4) in the homecare ulcer population (p = 0.002).

CONCLUSION

The majority of patients suffering from leg ulcers in this study was frail. The highest frailty prevalence was observed in the academic and homecare ulcer populations. The largest impaired quality of life was reported in the academic ulcer population. In dermatology practice, implementing frailty screening and initiating appropriate (paramedical) supportive care should be considered to improve patient outcomes.

The Multidimensional Prognostic Index Predicts Mortality in Older Outpatients with Cognitive Decline

Since the heterogeneity of the growing group of older outpatients with cognitive decline, it is challenging to evaluate survival rates in clinical shared decision making. The primary outcome was to determine whether the Multidimensional Prognostic Index (MPI) predicts mortality, whilst assessing the MPI distribution was considered secondary. This retrospective chart review included 311 outpatients aged ≥65 years and diagnosed with dementia or mild cognitive impairment (MCI). The MPI includes several domains of the comprehensive geriatric assessment (CGA). All characteristics and data to calculate the risk score and mortality data were extracted from administrative information in the database of the Alzheimer’s Center and medical records. The study population (mean age 76.8 years, men = 51.4%) was divided as follows: 34.1% belonged to MPI category 1, 52.1% to MPI category 2 and 13.8% to MPI category 3. Patients with dementia have a higher mean MPI risk score than patients with MCI (0.47 vs. 0.32; p < 0.001). The HRs and corresponding 95% CIs for mortality in patients in MPI categories 2 and 3 were 1.67 (0.81−3.45) and 3.80 (1.56−9.24) compared with MPI category 1, respectively. This study shows that the MPI predicts mortality in outpatients with cognitive decline.

Characteristics and outcomes of older patients hospitalised for COVID-19 in the first and second wave of the pandemic in The Netherlands: the COVID-OLD study

Background

as the coronavirus disease of 2019 (COVID-19) pandemic progressed diagnostics and treatment changed.

Objective

to investigate differences in characteristics, disease presentation and outcomes of older hospitalised COVID-19 patients between the first and second pandemic wave in The Netherlands.

Methods

this was a multicentre retrospective cohort study in 16 hospitals in The Netherlands including patients aged ≥ 70 years, hospitalised for COVID-19 in Spring 2020 (first wave) and Autumn 2020 (second wave). Data included Charlson comorbidity index (CCI), disease severity and Clinical Frailty Scale (CFS). Main outcome was in-hospital mortality.

Results

a total of 1,376 patients in the first wave (median age 78 years, 60% male) and 946 patients in the second wave (median age 79 years, 61% male) were included. There was no relevant difference in presence of comorbidity (median CCI 2) or frailty (median CFS 4). Patients in the second wave were admitted earlier in the disease course (median 6 versus 7 symptomatic days; P < 0.001). In-hospital mortality was lower in the second wave (38.1% first wave versus 27.0% second wave; P < 0.001). Mortality risk was 40% lower in the second wave compared with the first wave (95% confidence interval: 28–51%) after adjustment for differences in patient characteristics, comorbidity, symptomatic days until admission, disease severity and frailty.

Conclusions

compared with older patients hospitalised in the first COVID-19 wave, patients in the second wave had lower in-hospital mortality, independent of risk factors for mortality.

The better prognosis likely reflects earlier diagnosis, the effect of improvement in treatment and is relevant for future guidelines and treatment decisions.

The Multidimensional Prognostic Index as a Measure of Frailty in Elderly Patients with Head and Neck Cancer

Purpose

The multidimensional prognostic index (MPI) is a prognostic model derived from the comprehensive geriatric assessment (CGA) which can predict 1-year mortality risk in elderly individuals. We hypothesized that the MPI also reflects the degree of frailty and thus will correlate with established measures of frailty. Therefore, the aim of this study is to explore whether the MPI-score is a measure of frailty in older head and neck cancer patients and is associated with several physical functioning measurements.

Patients and Methods

From November 2019 to July 2020, a prospective cohort study enrolled patients with head and neck cancer aged ≥70 years, and patients <70 years with an abnormal G8 score. The MPI-score ranged from 0 to 1 and was categorized in MPI-stage 1 (≤0.33, non-frail); MPI-stage 2 (0.34-0.66, mildly frail), and MPI-stage 3 (≥0.67, severe frail). Pearson's correlation coefficient and multivariable linear regression were used to study the association between MPI-score and the physical functioning measurements handgrip strength, gait speed, and the timed up and go test (TUGT).

Results

A total of 163 patients were included. One hundred four (63.8%) patients were categorized as non-frail according MPI-stage 1, and 59 (36.2%) patients as mildly or severe frail (n=55 MPI-stage 2; n=4 MPI-stage 3, respectively). A higher MPI-score was significantly associated with lower hand grip strength (B -0.49 [95% CI -0.71; -0.28] p<0.001), lower gait speed (B -0.41 [95% CI -0.55; -0.25] p<0.001), and a slower TUGT (B 0.53 [95% CI 0.66; 0.85] p<0.001).

Conclusion

Almost one-third of the included patients with head and neck cancer was mild or severe frail. A higher MPI-score, indicating higher degree of frailty, was associated with worse physical performance by lower handgrip strength, gait speed, and a slower TUGT. Thus, the MPI reflects the degree of frailty.

Frailty is associated with in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands: the COVID-OLD study

Background

During the first wave of the coronavirus disease 2019 (COVID-19) pandemic, older patients had an increased risk of hospitalisation and death. Reports on the association of frailty with poor outcome have been conflicting.

Objective

The aim of the present study was to investigate the independent association between frailty and in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands.

Methods

This was a multicentre retrospective cohort study in 15 hospitals in the Netherlands, including all patients aged ≥70 years, who were hospitalised with clinically confirmed COVID-19 between February and May 2020. Data were collected on demographics, co-morbidity, disease severity and Clinical Frailty Scale (CFS). Primary outcome was in-hospital mortality.

Results

A total of 1,376 patients were included (median age 78 years (interquartile range 74–84), 60% male). In total, 499 (38%) patients died during hospital admission. Parameters indicating presence of frailty (CFS 6–9) were associated with more co-morbidities, shorter symptom duration upon presentation (median 4 versus 7 days), lower oxygen demand and lower levels of C-reactive protein. In multivariable analyses, the CFS was independently associated with in-hospital mortality: compared with patients with CFS 1–3, patients with CFS 4–5 had a two times higher risk (odds ratio (OR) 2.0 (95% confidence interval (CI) 1.3–3.0)) and patients with CFS 6–9 had a three times higher risk of in-hospital mortality (OR 2.8 (95% CI 1.8–4.3)).

Conclusions

The in-hospital mortality of older hospitalised COVID-19 patients in the Netherlands was 38%. Frailty was independently associated with higher in-hospital mortality, even though COVID-19 patients with frailty presented earlier to the hospital with less severe symptoms.

Changes in cerebral oxygenation and cerebral blood flow during hemodialysis - A simultaneous near-infrared spectroscopy and positron emission tomography study

Near-infrared spectroscopy (NIRS) is used to monitor cerebral tissue oxygenation (rSO₂) depending on cerebral blood flow (CBF), cerebral blood volume and blood oxygen content. We explored whether NIRS might be a more easy applicable proxy to [¹⁵O]H₂O positron emission tomography (PET) for detecting CBF changes during hemodialysis. Furthermore, we compared potential determinants of rSO₂ and CBF. In 12 patients aged ≥ 65 years, NIRS and PET were performed simultaneously: before (T1), early after start (T2), and at the end of hemodialysis (T3). Between T1 and T3, the relative change in frontal rSO₂ (ΔrSO₂) was -8 ± 9% (P = 0.001) and -5 ± 11% (P = 0.08), whereas the relative change in frontal gray matter CBF (ΔCBF) was -11 ± 18% (P = 0.009) and -12 ± 16% (P = 0.007) for the left and right hemisphere, respectively. ΔrSO₂ and ΔCBF were weakly correlated for the left (ρ 0.31, P = 0.4), and moderately correlated for the right (ρ 0.69, P = 0.03) hemisphere. The Bland-Altman plot suggested underestimation of ΔCBF by NIRS. Divergent associations of pH, pCO₂ and arterial oxygen content with rSO₂ were found compared to corresponding associations with CBF. In conclusion, NIRS could be a proxy to PET to detect intradialytic CBF changes, although NIRS and PET capture different physiological parameters of the brain.

Lower body mass index and mortality in older adults starting dialysis

Lower body mass index (BMI) has consistently been associated with mortality in elderly in the general and chronic disease populations. Remarkably, in older incident dialysis patients no association of BMI with mortality was found. We performed an in-depth analysis and explored possible time-stratified effects of BMI. 908 incident dialysis patients aged ≥65 years of the NECOSAD study were included, and divided into tertiles by baseline BMI (<23.1 (lower), 23.1–26.0 (reference), ≥26.0 (higher) kg/m²). Because the hazards changed significantly during follow-up, the effect of BMI was modeled for the short-term (<1 year) and longer-term (≥1 year after dialysis initiation). During follow-up (median 3.8 years) 567 deaths occurred. Lower BMI was associated with higher short-term mortality risk (adjusted-HR 1.63 [1.14–2.32] P = 0.007), and lower longer-term mortality risk (adjusted-HR 0.81 [0.63–1.04] P = 0.1). Patients with lower BMI who died during the first year had significantly more comorbidity, and worse self-reported physical functioning compared with those who survived the first year. Thus, lower BMI is associated with increased 1-year mortality, but conditional on surviving the first year, lower BMI yielded a similar or lower mortality risk compared with the reference. Those patients with lower BMI, who had limited comorbidity and better physical functioning, had better survival.

Hemodialysis Induces an Acute Decline in Cerebral Blood Flow in Elderly Patients

The initiation of hemodialysis is associated with an accelerated decline of cognitive function and an increased incidence of cerebrovascular accidents and white matter lesions. Investigators have hypothesized that the repetitive circulatory stress of hemodialysis induces ischemic cerebral injury, but the mechanism is unclear. We studied the acute effect of conventional hemodialysis on cerebral blood flow (CBF), measured by [¹⁵O]H₂O positron emission tomography-computed tomography (PET-CT). During a single hemodialysis session, three [¹⁵O]H₂O PET-CT scans were performed: before, early after the start of, and at the end of hemodialysis. We used linear mixed models to study global and regional CBF change during hemodialysis. Twelve patients aged ≥65 years (five women, seven men), with a median dialysis vintage of 46 months, completed the study. Mean (±SD) arterial BP declined from 101±11 mm Hg before hemodialysis to 93±17 mm Hg at the end of hemodialysis. From before the start to the end of hemodialysis, global CBF declined significantly by 10%±15%, from a mean of 34.5 to 30.5 ml/100g per minute (difference, -4.1 ml/100 g per minute; 95% confidence interval, -7.3 to -0.9 ml/100 g per minute; P=0.03). CBF decline (20%) was symptomatic in one patient. Regional CBF declined in all volumes of interest, including the frontal, parietal, temporal, and occipital lobes; cerebellum; and thalamus. Higher tympanic temperature, ultrafiltration volume, ultrafiltration rate, and pH significantly associated with lower CBF. Thus, conventional hemodialysis induces a significant reduction in global and regional CBF in elderly patients. Repetitive intradialytic decreases in CBF may be one mechanism by which hemodialysis induces cerebral ischemic injury.