Predictive Admission Risk Factors, Clinical Features and Kidney Outcomes in Covid-19 Hospitalised Patients with Acute Kidney Injury

Introduction: In COVID-19 patients, acute kidney injury (AKI) is recognized as a cause of high mortality. The aim of our study was to assess the rate and the predictors of AKI as well as survival among COVID-19 patients. Methods: We analyzed clinical and laboratory admission data, predictors of AKI and outcomes including the need for renal replacement therapy (RRT) and mortality at 30 days. Results: Out of 115 patients, 62 (53.9%) presented with AKI: 21 (33.9%) at stage 1, 7(11.3%) at stage 2, and 34 (54.8%) at stage 3. RRT was required in 22.6% of patients and was resolved in 76%. Pre-existing CKD was associated with a 13-fold risk of AKI (p= 0.0001). Low albumin (p = 0.017), thrombocytopenia (p = 0.022) and increase of creatine kinase over 350UI (p = 0.024) were independently associated with a higher risk for AKI. Mortality rates were significantly higher among patients who developed AKI compared to those without (59.6% vs 30.2%, p= 0.003). Low oxygen blood saturation at admission and albumin were found as powerful independent predictors of mortality (OR 0.937; 95%CI: 0.917 - 0.958, p = 0.000; OR 0.987; 95%CI: 0.885-0.991, p= 0.024, respectively). Longer survival was observed in patients without AKI compared to patients with AKI (22.01± 1.703 vs 16.69 ± 1.54, log rank p= 0.009). Conclusion: Renal impairment is significant in hospitalized COVID-19 patients. The severity of the disease itself is emphasized as main contributing mechanism in the occurrence of AKI, and lower blood saturation at admission is the strongest mortality predictor, surpassing the significance of the AKI itself.

Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study

Background

The SARS-CoV-2 pandemic is a worldwide challenge. The CRIT-CoV-U pilot study generated a urinary proteomic biomarker consisting of 50 peptides (COV50), which predicted death and disease progression from SARS-CoV-2. After the interim analysis presented for the German Government, here, we aimed to analyse the full dataset to consolidate the findings and propose potential clinical applications of this biomarker.

Methods

CRIT-CoV-U was a prospective multicentre cohort study. In eight European countries (Austria, France, Germany, Greece, North Macedonia, Poland, Spain, and Sweden), 1012 adults with PCR-confirmed COVID-19 were followed up for death and progression along the 8-point WHO scale. Capillary electrophoresis coupled with mass spectrometry was used for urinary proteomic profiling. Statistical methods included logistic regression and receiver operating characteristic curve analysis with a comparison of the area under curve (AUC) between nested models. Hospitalisation costs were derived from the care facility corresponding with the Markov chain probability of reaching WHO scores ranging from 3 to 8 and flat-rate hospitalisation costs adjusted for the gross per capita domestic product of each country.

Findings

From June 30 to Nov 19, 2020, 228 participants were recruited, and from April 30, 2020, to April 14, 2021, 784 participants were recruited, resulting in a total of 1012 participants. The entry WHO scores were 1–3 in 445 (44%) participants, 4–5 in 529 (52%) participants, and 6 in 38 (4%) participants; and of all participants, 119 died and 271 had disease progression. The odds ratio (OR) associated with COV50 in all 1012 participants for death was 2·44 (95% CI 2·05–2·92) unadjusted and 1·67 (1·34–2·07) when adjusted for sex, age, BMI, comorbidities, and baseline WHO score; and for disease progression, the OR was 1·79 (1·60–2·01) when unadjusted and 1·63 (1·41–1·91) when adjusted (p<0·0001 for all). The predictive accuracy of the optimised COV50 thresholds was 74·4% (71·6–77·1%) for mortality (threshold 0·47) and 67·4% (64·4–70·3%) for disease progression (threshold 0·04). When adjusted for covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·033) for death and from 0·697 to 0·730 (p=0·0008) for progression. Of 196 participants who received ambulatory care, 194 (99%) did not reach the 0·04 threshold. The cost reductions associated with 1 day less hospitalisation per 1000 participants were million Euro (M€) 0·887 (5–95% percentile interval 0·730–1·039) in participants at a low risk (COV50 <0·04) and M€2·098 (1·839-2·365) in participants at a high risk (COV50 ≥0·04).

Interpretation

The urinary proteomic COV50 marker might be predictive of adverse COVID-19 outcomes. Even in people with mild-to-moderate PCR-confirmed infections (WHO scores 1–4), the 0·04 COV50 threshold justifies earlier drug treatment, thereby potentially reducing the number of days in hospital and associated costs.

Funding

German Federal Ministry of Health.

A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients

BACKGROUND

COVID-19 prediction models based on clinical characteristics, routine biochemistry and imaging, have been developed, but little is known on proteomic markers reflecting the molecular pathophysiology of disease progression.

METHODS

The multicentre (six European study sites) Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection Study (Crit-COV-U) is recruiting consecutive patients (≥ 18 years) with PCR-confirmed SARS-CoV-2 infection. A urinary proteomic biomarker (COV50) developed by capillary-electrophoresis-mass spectrometry (CE-MS) technology, comprising 50 sequenced peptides and identifying the parental proteins, was evaluated in 228 patients (derivation cohort) with replication in 99 patients (validation cohort). Death and progression along the World Health Organization (WHO) Clinical Progression Scale were assessed up to 21 days after the initial PCR test. Statistical methods included logistic regression, receiver operating curve (ROC) analysis and comparison of the area under the curve (AUC).

FINDINGS

In the derivation cohort, 23 patients died, and 48 developed worse WHO scores. The odds ratios (OR) for death per 1 standard deviation (SD) increment in COV50 were 3·52 (95% CI, 2·02-6·13, p <0·0001) unadjusted and 2·73 (1·25-5·95, p = 0·012) adjusted for sex, age, baseline WHO score, body mass index (BMI) and comorbidities. For WHO scale progression, the corresponding OR were 2·63 (1·80-3·85, p<0·0001) and 3·38 (1·85-6·17, p<0·0001), respectively. The area under the curve (AUC) for COV50 as a continuously distributed variable was 0·80 (0·72-0·88) for mortality and 0·74 (0·66-0·81) for worsening WHO score. The optimised COV50 thresholds for mortality and worsening WHO score were 0·47 and 0·04 with sensitivity/specificity of 87·0 (74·6%) and 77·1 (63·9%), respectively. On top of covariates, COV50 improved the AUC, albeit borderline for death, from 0·78 to 0·82 (p = 0·11) and 0·84 (p = 0·052) for mortality and from 0·68 to 0·78 (p = 0·0097) and 0·75 (p = 0·021) for worsening WHO score. The validation cohort findings were confirmatory.

INTERPRETATION

This first CRIT-COV-U report proves the concept that urinary proteomic profiling generates biomarkers indicating adverse COVID-19 outcomes, even at an early disease stage, including WHO stages 1-3. These findings need to be consolidated in an upcoming final dataset.

FUNDING

The German Federal Ministry of Health funded the study.

Excess Mortality in a Nephrology Clinic during First Months of Coronavirus Disease-19 Pandemic: A Pragmatic Approach

BACKGROUND: Excess mortality is defined as mortality above what would be expected based on the non-crisis mortality rate in the population of interest. AIM: In this study, we aimed to access weather the coronavirus disease (COVID)-19 pandemic had impact on the in-hospital mortality during the first 6 months of the year and compare it with the data from the previous years. METHODS: A retroprospective study was conducted at the University Clinic of Nephrology Skopje, Republic of Macedonia. In-hospital mortality rates were calculated for the first half of the year (01.01–30.06) from 2015 until 2020, as monthly number of dead patients divided by the number of non-elective hospitalized patents in the same period. The excess mortality rate (p-score) was calculated as ratio or percentage of excess deaths relative to expected average deaths: (Observed mortality rate–expected average death rate)/expected average death rate *100%. RESULTS: The expected (average) overall death mortality rate for the period 2015–2019 was 8.9% and for 2020 was 15.3%. The calculated overall excess mortality in 2020 was 72% (pscore 0.72). CONCLUSION: In this pragmatic study, we have provided clear evidence of high excess mortality at our nephrology clinic during the 1st months of the COVID-19 pandemic. The delayed referral of patients due to the patient and health care system-related factors might partially explain the excess mortality during pandemic crises. Further analysis is needed to estimate unrecognized probable COVID-19 deaths.

P1551FAMILY SUPPORT IS CRUCIAL FOR DIALYSIS PATIENTS TREATMENT ADHERENCE AND QUALITY OF LIFE

Background and Aims

Non-compliant dialysis patients are at increased risk of mortality. Compliance depends on patient demographics, educational level and income. Family support and marital status might also influence the patients compliance, as well as the quality of life. Missed/shortened dialysis sessions, adherence to prescribed medications, excessive phosphate serum values and interdialytic weigh gain, smoking and adherence to medical investigations provide indicators of non-compliance. Aim: To assess the impact of family support on different compliance indicators in the dialysis patients.

Method

In this observational study 134 dialysis patients were scored for different indicators of compliance from 0-2 and summary scores of compliance were assessed. Clinical and laboratory data were obtained from the previous two years. Patients with mean IDWGs &gt;4.5% of body weight (BW) and/or phosphorous level above 1.6 mmol/L were scored with 1, patients with IDWG/BW more than 5.7% and/or 2.0 for mean phosphorous level were scored with 2. Summary scores of non-compliance were also assessed. Patients were scored for quality of life with SF-36 questionnaire. Patients non-adherence was analysed for predictors in multivariate analysis.

Results

Estimated rates of noncompliance varied: Medical investigations 63%, phosphorous 33, IDWG 22, therapy 14%, HD treatment 9%. When the complete dietary fluid, medications and treatment regimen were studied noncompliance rate was 73%, and when adherence to medical investigations was added the rate rose up to 87%. Patients with family support above median level (≥25) were significantly more often men (0.049), with diabetes (p=0.014), lower socioeconomic status (0.001) and married (0.003). The quality of life scores were significantly worse in the low family supported patients (56.73±26.15 vs 39.23±24.05, p=0.0001). They also scored worse in overall non-compliance scores 2.04±1.71 vs 2.97±2.06, p= 0.007). In the multivariate analysis the non-compliance was predicted most powerfully in patients with younger age, low social status and lower family support (β=-0.202, p=0.023, β=0.220, p=0.036, β=-0.175, p=0.019, respectively).

Conclusion

Family support is crucial for dialysis patients adherence to treatment and Quality of life. Efforts should be done to recognize the patients real needs and adequately help those confronting dialysis burden and improve their quality of life.

P1505COMORBIDITY AND AGE OF DIALYSIS PATIENTS OUTPERFORMS FRAILTY BURDEN AS A PREDICTOR FOR MORTALITY

Background and Aims

The life expectancy in dialysis patients depends on patients’ age and comorbidities. Frailty in elderly patients is a state of impaired homeostasis with loss of physiologic reserve and a consequent impaired responses to dialysis burden. In this study we assessed the impact of age, comorbidities and frailty on dialysis patients’ survival.

Method

The study enrolled 162 prevalent patients on chronic hemodialysis with mean dialysis vintage of 100 months, 55% were women and 21 % had diabetes. Patients were divided into three groups by the Khan Comorbidity index score, highest score was considered worse. Frailty was assessed by presence of 3 or more symptoms (unintentional weight loss, feeling exhausted, weak grip strength, slow walking speed and low physical activity) and expressed as absolute number. Estimates of five years life expectancy were assessed by Kaplan Meier survival log-rank test and Cox regression hazard model.

Results

There were 26 (16%) with lowest score, 85 (52%) with medium score and worst highest score in 51 (31%). During the 5 years of follow up 69(43%) patients died of all-cause mortality. There were no deaths in the group with lowest score and mortality rates in the intermediate and worse score group increased by double (0; 30%; 69%, respectively). Significantly higher mean life expectancy was found in lower Khan Score groups: 60mo; 48.40 ± 18.51; 32.44 ± 22.06, log-rank: p &lt; 0.012. Patients that scored worse had four folds higher risk for death HR 4.2 (95% CI: 2.72 – 6.36), p=0.0001. In the multivariate model Khan Score was a more powerful predictor of mortality than frailty in elderly, with HR 3.2 (95% CI: 2.88 – 5.41), p=0.0001.

Conclusion

Comorbidities and age outperforms frailty burden as a predictor of mortality in dialysis patients.

P0316RELATION OF RENAL ULTRASONOGRAPHIC MEASUREMENTS WITH BODY HEIGHT

Background and Aims

Kidney size has been found to be correlated with anthropometric features and is different among different ethnicities. In this study, we used ultrasonography for measurement of kidney volumes in healthy individuals and evaluated the relationships with body height, age and gender.

Method

We conducted a cross-sectional observational study and evaluated 108 healthy individuals whose serum creatinine level was within reference range. Patients’ medical clinical and laboratory records were reviewed. Age, gender and height were recorded. Pearson correlation coefficients were used to evaluate the strength of association between ultrasonographic parameters with each other and with other parameters, and were expressed as r2. Variations in left and right renal dimensions between various age groups were compared using a one-way analysis of variance, followed by a post-hoc Tukey's test.

Results

Subjects’ age ranged from 16 to 84 years and the mean age was over 50 years. There was an equal distribution among genders. Strong and positive correlations were seen for the measured length, parenchyma thickness and also for both total and parenchymal volumes with subjects’ height for both kidneys. The strongest correlations were observed for the left and right kidney length and also for the right kidney parenchymal volume (r=0.536, p=0.001; r=0.469, p=0.001; r=0.44, p=0.001). On the opposite, most of the relations with age were negative, but week and insignificant. When we divided the study subjects into three age groups and compared them for the height, there was no significant difference among them. Regarding the parenchymal and total kidney volumes of both kidneys, the different age groups showed similar findings in the ultrasonographic measurements. The mean calculated volumes were slightly declining with age and showed the largest values in the first group of patients under 30 years and lowest values in patients over 70 years old. Ultrasonographic measurements were also compared among the two genders. Both (men and women) showed similar age (53.55 ± 18.22 vs. 50.79 ± 18.13 p= 0.430, respectively). As for the height, men were significantly taller than women (1.734 ± 0.007 vs.1.637 ± 0.005, p= 0.001). The kidney length, volume and parenchymal volumes of both kidneys were significantly larger in men.

Conclusion

Renal length and volume are strongly correlated with body height. This relation must be considered in clinical decisions on further investigations regarding kidney disease progression.

P1250LOW SERUM URIC ACID LEVEL AND LEFT VENTRICULAR HYPERTROPHY : THE NEW PARADOXICAL ASSOCIATION IN HEMODIALYSIS PATIENTS

Background and Aims

The association between serum uric acid (UA) and left ventricular hypertrophy (LVH) is controversial in chronic kidney disease, whereas in hemodialysis (HD) patients has not been studied until now. Thus, we evaluated the relationship of baseline and time-averaged UA with echocardiographic LVH over a 5-year period in HD patients.

Method

This longitudinal study was conducted on 225 prevalent HD patients over a 5-year period. Patients were stratified into 3 groups according to their baseline and time-averaged UA levels: lower group (UA&lt;400µmmol/l), intermediate/reference group (UA between 400-450µmol/l) and higher group (UA&gt;450µmol/l). Echocardiography was performed on a non-dialysis day and the presence of LVH was defined based on the left ventricular mass index (LVMI) &gt;131 and &gt;100 g/m2, for men and women, respectively. The patients were followed during a 60 month period.

Results

During the 5-year follow-up, 81 patients died (36%), and the main causes of death were cardiovascular (CV) related (70%). Survival analysis show that patients with time-averaged UA&lt;400 µmmol/l had a significantly higher all cause (log rank, p=0.003) and CV mortality (log rank, p=0.004) rate, compared to those with time-averaged UA between 400-450 µmmol/l and time-averaged UA&gt;450µmol/l, but this difference was not statistically significant in terms of baseline UA level. A negative correlation was observed between LVH and time-averaged UA (r=-0.26, p=0.001), but not with LVH and baseline UA. Patients in lower time-averaged UA group had significantly higher LVMI compared to patients in intermediate and higher group (153.10± 59.89, 131.62±40.99, 131.19±44.49 g/m2, p=0.029), but from the lowest to the highest baseline UA levels, LVH was not significantly different (146.99±59.20, 141.38±37.52, 126.85±42.48 g/m2, p=0.07). Unadjusted odd ratio of LVH risk in the lower time-averaged UA compared to the reference time-averaged UA group was 3.11 (95% CI=1.38-7.05; p=0.006); and after adjustment for age, gender, diabetes and CV disease, ORs for LVH persisted significant only in the lower time-averaged UA group (OR = 2.82, 95% CI = 1.16–6.88, P = 0.002). On the contrary, baseline UA did not affect unadjusted and adjusted LVH.

Conclusion

In HD patients the prolonged exposure to hypouricemia is associated with LVH. This paradoxical association can only be explained by the hypothesis that uremic milieu in HD patients changes the influence of uric acid. However, these results should be the subject of further research.