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1.
J Med Internet Res ; 23(2): e26107, 2021 02 22.
Artigo em Inglês | MEDLINE | ID: mdl-33529156

RESUMO

BACKGROUND: Changes in autonomic nervous system function, characterized by heart rate variability (HRV), have been associated with infection and observed prior to its clinical identification. OBJECTIVE: We performed an evaluation of HRV collected by a wearable device to identify and predict COVID-19 and its related symptoms. METHODS: Health care workers in the Mount Sinai Health System were prospectively followed in an ongoing observational study using the custom Warrior Watch Study app, which was downloaded to their smartphones. Participants wore an Apple Watch for the duration of the study, measuring HRV throughout the follow-up period. Surveys assessing infection and symptom-related questions were obtained daily. RESULTS: Using a mixed-effect cosinor model, the mean amplitude of the circadian pattern of the standard deviation of the interbeat interval of normal sinus beats (SDNN), an HRV metric, differed between subjects with and without COVID-19 (P=.006). The mean amplitude of this circadian pattern differed between individuals during the 7 days before and the 7 days after a COVID-19 diagnosis compared to this metric during uninfected time periods (P=.01). Significant changes in the mean and amplitude of the circadian pattern of the SDNN was observed between the first day of reporting a COVID-19-related symptom compared to all other symptom-free days (P=.01). CONCLUSIONS: Longitudinally collected HRV metrics from a commonly worn commercial wearable device (Apple Watch) can predict the diagnosis of COVID-19 and identify COVID-19-related symptoms. Prior to the diagnosis of COVID-19 by nasal swab polymerase chain reaction testing, significant changes in HRV were observed, demonstrating the predictive ability of this metric to identify COVID-19 infection.

2.
Blood Purif ; : 1-7, 2021 Feb 25.
Artigo em Inglês | MEDLINE | ID: mdl-33631752

RESUMO

BACKGROUND/AIMS: Acute kidney injury (AKI) in critically ill patients is common, and continuous renal replacement therapy (CRRT) is a preferred mode of renal replacement therapy (RRT) in hemodynamically unstable patients. Prediction of clinical outcomes in patients on CRRT is challenging. We utilized several approaches to predict RRT-free survival (RRTFS) in critically ill patients with AKI requiring CRRT. METHODS: We used the Medical Information Mart for Intensive Care (MIMIC-III) database to identify patients ≥18 years old with AKI on CRRT, after excluding patients who had ESRD on chronic dialysis, and kidney transplantation. We defined RRTFS as patients who were discharged alive and did not require RRT ≥7 days prior to hospital discharge. We utilized all available biomedical data up to CRRT initiation. We evaluated 7 approaches, including logistic regression (LR), random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), multilayer perceptron (MLP), and MLP with long short-term memory (MLP + LSTM). We evaluated model performance by using area under the receiver operating characteristic (AUROC) curves. RESULTS: Out of 684 patients with AKI on CRRT, 205 (30%) patients had RRTFS. The median age of patients was 63 years and their median Simplified Acute Physiology Score (SAPS) II was 67 (interquartile range 52-84). The MLP + LSTM showed the highest AUROC (95% CI) of 0.70 (0.67-0.73), followed by MLP 0.59 (0.54-0.64), LR 0.57 (0.52-0.62), SVM 0.51 (0.46-0.56), AdaBoost 0.51 (0.46-0.55), RF 0.44 (0.39-0.48), and XGBoost 0.43 (CI 0.38-0.47). CONCLUSIONS: A MLP + LSTM model outperformed other approaches for predicting RRTFS. Performance could be further improved by incorporating other data types.

3.
PLoS One ; 16(2): e0247366, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33626098

RESUMO

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the associated Coronavirus Disease 2019 (COVID-19) is a public health emergency. Acute kidney injury (AKI) is a common complication in hospitalized patients with COVID-19 although mechanisms underlying AKI are yet unclear. There may be a direct effect of SARS-CoV-2 virus on the kidney; however, there is currently no data linking SARS-CoV-2 viral load (VL) to AKI. We explored the association of SARS-CoV-2 VL at admission to AKI in a large diverse cohort of hospitalized patients with COVID-19. METHODS AND FINDINGS: We included patients hospitalized between March 13th and May 19th, 2020 with SARS-CoV-2 in a large academic healthcare system in New York City (N = 1,049) with available VL at admission quantified by real-time RT-PCR. We extracted clinical and outcome data from our institutional electronic health records (EHRs). AKI was defined by KDIGO guidelines. We fit a Fine-Gray competing risks model (with death as a competing risk) using demographics, comorbidities, admission severity scores, and log10 transformed VL as covariates and generated adjusted hazard ratios (aHR) and 95% Confidence Intervals (CIs). VL was associated with an increased risk of AKI (aHR = 1.04, 95% CI: 1.01-1.08, p = 0.02) with a 4% increased hazard for each log10 VL change. Patients with a viral load in the top 50th percentile had an increased adjusted hazard of 1.27 (95% CI: 1.02-1.58, p = 0.03) for AKI as compared to those in the bottom 50th percentile. CONCLUSIONS: VL is weakly but significantly associated with in-hospital AKI after adjusting for confounders. This may indicate the role of VL in COVID-19 associated AKI. This data may inform future studies to discover the mechanistic basis of COVID-19 associated AKI.

5.
Europace ; 2021 Feb 10.
Artigo em Inglês | MEDLINE | ID: mdl-33564873

RESUMO

In the recent decade, deep learning, a subset of artificial intelligence and machine learning, has been used to identify patterns in big healthcare datasets for disease phenotyping, event predictions, and complex decision making. Public datasets for electrocardiograms (ECGs) have existed since the 1980s and have been used for very specific tasks in cardiology, such as arrhythmia, ischemia, and cardiomyopathy detection. Recently, private institutions have begun curating large ECG databases that are orders of magnitude larger than the public databases for ingestion by deep learning models. These efforts have demonstrated not only improved performance and generalizability in these aforementioned tasks but also application to novel clinical scenarios. This review focuses on orienting the clinician towards fundamental tenets of deep learning, state-of-the-art prior to its use for ECG analysis, and current applications of deep learning on ECGs, as well as their limitations and future areas of improvement.

6.
Sci Transl Med ; 13(576)2021 Jan 13.
Artigo em Inglês | MEDLINE | ID: mdl-33441424

RESUMO

More than 800 million people in the world suffer from chronic kidney disease (CKD). Genome-wide association studies (GWAS) have identified hundreds of loci where genetic variants are associated with kidney function; however, causal genes and pathways for CKD remain unknown. Here, we performed integration of kidney function GWAS and human kidney-specific expression quantitative trait analysis and identified that the expression of beta-mannosidase (MANBA) was lower in kidneys of subjects with CKD risk genotype. We also show an increased incidence of renal failure in subjects with rare heterozygous loss-of-function coding variants in MANBA using phenome-wide association analysis of 40,963 subjects with exome sequencing data. MANBA is a lysosomal gene highly expressed in kidney tubule cells. Deep phenotyping revealed structural and functional lysosomal alterations in human kidneys from subjects with CKD risk alleles and mice with genetic deletion of Manba Manba heterozygous and knockout mice developed more severe kidney fibrosis when subjected to toxic injury induced by cisplatin or folic acid. Manba loss altered multiple pathways, including endocytosis and autophagy. In the absence of Manba, toxic acute tubule injury induced inflammasome activation and fibrosis. Together, these results illustrate the convergence of common noncoding and rare coding variants in MANBA in kidney disease development and demonstrate the role of the endolysosomal system in kidney disease development.

8.
JMIR Med Inform ; 9(1): e24207, 2021 Jan 27.
Artigo em Inglês | MEDLINE | ID: mdl-33400679

RESUMO

BACKGROUND: Machine learning models require large datasets that may be siloed across different health care institutions. Machine learning studies that focus on COVID-19 have been limited to single-hospital data, which limits model generalizability. OBJECTIVE: We aimed to use federated learning, a machine learning technique that avoids locally aggregating raw clinical data across multiple institutions, to predict mortality in hospitalized patients with COVID-19 within 7 days. METHODS: Patient data were collected from the electronic health records of 5 hospitals within the Mount Sinai Health System. Logistic regression with L1 regularization/least absolute shrinkage and selection operator (LASSO) and multilayer perceptron (MLP) models were trained by using local data at each site. We developed a pooled model with combined data from all 5 sites, and a federated model that only shared parameters with a central aggregator. RESULTS: The LASSOfederated model outperformed the LASSOlocal model at 3 hospitals, and the MLPfederated model performed better than the MLPlocal model at all 5 hospitals, as determined by the area under the receiver operating characteristic curve. The LASSOpooled model outperformed the LASSOfederated model at all hospitals, and the MLPfederated model outperformed the MLPpooled model at 2 hospitals. CONCLUSIONS: The federated learning of COVID-19 electronic health record data shows promise in developing robust predictive models without compromising patient privacy.

9.
Nat Med ; 27(1): 66-72, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33432171

RESUMO

The clinical impact of rare loss-of-function variants has yet to be determined for most genes. Integration of DNA sequencing data with electronic health records (EHRs) could enhance our understanding of the contribution of rare genetic variation to human disease1. By leveraging 10,900 whole-exome sequences linked to EHR data in the Penn Medicine Biobank, we addressed the association of the cumulative effects of rare predicted loss-of-function variants for each individual gene on human disease on an exome-wide scale, as assessed using a set of diverse EHR phenotypes. After discovering 97 genes with exome-by-phenome-wide significant phenotype associations (P < 10-6), we replicated 26 of these in the Penn Medicine Biobank, as well as in three other medical biobanks and the population-based UK Biobank. Of these 26 genes, five had associations that have been previously reported and represented positive controls, whereas 21 had phenotype associations not previously reported, among which were genes implicated in glaucoma, aortic ectasia, diabetes mellitus, muscular dystrophy and hearing loss. These findings show the value of aggregating rare predicted loss-of-function variants into 'gene burdens' for identifying new gene-disease associations using EHR phenotypes in a medical biobank. We suggest that application of this approach to even larger numbers of individuals will provide the statistical power required to uncover unexplored relationships between rare genetic variation and disease phenotypes.


Assuntos
Registros Eletrônicos de Saúde , Exoma , Genótipo , Fenótipo , Idoso , Biologia Computacional , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Polimorfismo de Nucleotídeo Único , Sequenciamento Completo do Exoma
10.
12.
Clin J Am Soc Nephrol ; 16(1): 37-47, 2020 Dec 31.
Artigo em Inglês | MEDLINE | ID: mdl-33380473

RESUMO

BACKGROUND AND OBJECTIVES: Genetic variants in NAT8, a liver- and kidney-specific acetyltransferase encoding gene, have been associated with eGFR and CKD in European populations. Higher circulating levels of two NAT8-associated metabolites, N-δ-acetylornithine and N-acetyl-1-methylhistidine, have been linked to lower eGFR and higher risk of incident CKD in the Black population. We aimed to expand upon prior studies to investigate associations between rs13538, a missense variant in NAT8, N-acetylated amino acids, and kidney failure in multiple, well-characterized cohorts. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We conducted analyses among participants with genetic and/or serum metabolomic data in the African American Study of Kidney Disease and Hypertension (AASK; n=962), the Atherosclerosis Risk in Communities (ARIC) study (n=1050), and BioMe, an electronic health record-linked biorepository (n=680). Separately, we evaluated associations between rs13538, urinary N-acetylated amino acids, and kidney failure in participants in the German CKD (GCKD) study (n=1624). RESULTS: Of 31 N-acetylated amino acids evaluated, the circulating and urinary levels of 14 were associated with rs13538 (P<0.05/31). Higher circulating levels of five of these N-acetylated amino acids, namely, N-δ-acetylornithine, N-acetyl-1-methylhistidine, N-acetyl-3-methylhistidine, N-acetylhistidine, and N2,N5-diacetylornithine, were associated with kidney failure, after adjustment for confounders and combining results in meta-analysis (combined hazard ratios per two-fold higher amino acid levels: 1.48, 1.44, 1.21, 1.65, and 1.41, respectively; 95% confidence intervals: 1.21 to 1.81, 1.22 to 1.70, 1.08 to 1.37, 1.29 to 2.10, and 1.17 to 1.71, respectively; all P values <0.05/14). None of the urinary levels of these N-acetylated amino acids were associated with kidney failure in the GCKD study. CONCLUSIONS: We demonstrate significant associations between an NAT8 gene variant and 14 N-acetylated amino acids, five of which had circulation levels that were associated with kidney failure.

13.
BMJ Open ; 10(11): e039119, 2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33148746

RESUMO

OBJECTIVE: Multiple clinical trials fail to identify clinically measurable health benefits of daily multivitamin and multimineral (MVM) consumption in the general adult population. Understanding the determinants of widespread use of MVMs may guide efforts to better educate the public about effective nutritional practices. The objective of this study was to compare self-reported and clinically measurable health outcomes among MVM users and non-users in a large, nationally representative adult civilian non-institutionalised population in the USA surveyed on the use of complementary health practices. DESIGN: Cross-sectional analysis of the effect of MVM consumption on self-reported overall health and clinically measurable health outcomes. PARTICIPANTS: Adult MVM users and non-users from the 2012 National Health Interview Survey (n=21 603). PRIMARY AND SECONDARY OUTCOME MEASURES: Five psychological, physical, and functional health outcomes: (1) self-rated health status, (2) needing help with routine needs, (3) history of 10 chronic diseases, (4) presence of 19 health conditions in the past 12 months, and (5) Kessler 6-Item (K6) Psychological Distress Scale to measure non-specific psychological distress in the past month. RESULTS: Among 4933 adult MVM users and 16 670 adult non-users, MVM users self-reported 30% better overall health than non-users (adjusted OR 1.31; 95% CI 1.17 to 1.46; false discovery rate adjusted p<0.001). There were no differences between MVM users and non-users in history of 10 chronic diseases, number of present health conditions, severity of current psychological distress on the K6 Scale and rates of needing help with daily activities. No effect modification was observed after stratification by sex, education, and race. CONCLUSIONS: MVM users self-reported better overall health despite no apparent differences in clinically measurable health outcomes. These results suggest that widespread use of multivitamins in adults may be a result of individuals' positive expectation that multivitamin use leads to better health outcomes or a self-selection bias in which MVM users intrinsically harbour more positive views regarding their health.

14.
Int J Nephrol Renovasc Dis ; 13: 281-296, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33149657

RESUMO

Purpose of Review: Type 2 diabetes mellitus (T2DM) is a prevalent disease with the severe clinical implications including myocardial infarction, stroke, and kidney disease. Therapies focusing on glycemic control in T2DM such as biguanides, sulfonylureas, thiazolidinediones, and insulin-based regimens have largely failed to substantially improve cardiovascular and kidney outcomes. We review the recent findings on sodium-glucose co-transporter type 2 (SGLT2) inhibitors which have shown to have beneficial cardiovascular and kidney-related effects. Recent Findings: SGLT2 inhibitors are a new class of diabetic medications that reduce the absorption of glucose in the kidney, decrease proteinuria, control blood pressure, and are associated with weight loss. SGLT2 inhibitors provide complementary therapy independent of insulin secretion or action with proved glucose-lowering effects. Recent placebo-controlled clinical trials have demonstrated that these medications can decrease cardiovascular death, progression of kidney disease, and all-cause mortality in diabetic and non-diabetic patients. Interestingly, SGT2 inhibitors such as dapagliflozin have also proven to decrease heart failure admissions and cardiovascular endpoints in non-diabetic patients, suggesting pleiotropic effects. The exact mechanisms responsible for reductions in atherosclerotic heart disease, need for kidney replacement therapy, and progressive kidney disease remain unknown. While regulation of glomerular hyperfiltration, albuminuria, and natriuresis may be part of the explanation, it is possible that complex cellular effects including energy balance optimization, downregulation of oxidative stress, and modulation of pro-inflammatory signaling pathways are associated with favorable outcomes observed in large clinical studies. Conclusion: SGLT2 inhibitors are novel antidiabetic medications with immense utility in the management of patients with T2DM. Furthermore, SGLT2 inhibitors have demonstrated to reduce the progression to advanced forms of kidney disease and its associated complications. These medications should be front and center in the management of patients with diabetic kidney disease with and without chronic kidney disease as they confer protection against cardiovascular/renal death and improve all-cause mortality. Future studies should evaluate the benefits and implications of early initiation of SGLT2 inhibitors, as well as the long-term effects of this therapy.

15.
EClinicalMedicine ; 27: 100552, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-33150324

RESUMO

Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. "CKD Patch" is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures. Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several "CKD Patches" incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch. Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018-0.036] and 0.010 [0.007-0.013] and categorical net reclassification improvement 0.080 [0.032-0.127] and 0.056 [0.044-0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89-3.40) in very high-risk CKD (e.g., eGFR 30-44 ml/min/1.73m2 with albuminuria ≥30 mg/g), 1.86 (1.48-2.44) in high-risk CKD (e.g., eGFR 45-59 ml/min/1.73m2 with albuminuria 30-299 mg/g), and 1.37 (1.14-1.69) in moderate risk CKD (e.g., eGFR 60-89 ml/min/1.73m2 with albuminuria 30-299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37-1.81), 1.24 (1.10-1.54), and 1.21 (0.98-1.46). Interpretation: The "CKD Patch" can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available. Funding: US National Kidney Foundation and the NIDDK.

16.
J Am Coll Cardiol ; 76(20): 2334-2348, 2020 11 17.
Artigo em Inglês | MEDLINE | ID: mdl-33129663

RESUMO

BACKGROUND: Patients with pre-existing heart failure (HF) are likely at higher risk for adverse outcomes in coronavirus disease-2019 (COVID-19), but data on this population are sparse. OBJECTIVES: This study described the clinical profile and associated outcomes among patients with HF hospitalized with COVID-19. METHODS: This study conducted a retrospective analysis of 6,439 patients admitted for COVID-19 at 1 of 5 Mount Sinai Health System hospitals in New York City between February 27 and June 26, 2020. Clinical characteristics and outcomes (length of stay, need for intensive care unit, mechanical ventilation, and in-hospital mortality) were captured from electronic health records. For patients identified as having a history of HF by International Classification of Diseases-9th and/or 10th Revisions codes, manual chart abstraction informed etiology, functional class, and left ventricular ejection fraction (LVEF). RESULTS: Mean age was 63.5 years, and 45% were women. Compared with patients without HF, those with previous HF experienced longer length of stay (8 days vs. 6 days; p < 0.001), increased risk of mechanical ventilation (22.8% vs. 11.9%; adjusted odds ratio: 3.64; 95% confidence interval: 2.56 to 5.16; p < 0.001), and mortality (40.0% vs. 24.9%; adjusted odds ratio: 1.88; 95% confidence interval: 1.27 to 2.78; p = 0.002). Outcomes among patients with HF were similar, regardless of LVEF or renin-angiotensin-aldosterone inhibitor use. CONCLUSIONS: History of HF was associated with higher risk of mechanical ventilation and mortality among patients hospitalized for COVID-19, regardless of LVEF.

17.
Am J Public Health ; : e1-e5, 2020 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-33211588

RESUMO

In April 2020, in light of COVID-19-related blood shortages, the US Food and Drug Administration (FDA) reduced the deferral period for men who have sex with men (MSM) from its previous duration of 1 year to 3 months.Although originally born out of necessity, the decades-old restrictions on MSM donors have been mitigated by significant advancements in HIV screening, treatment, and public education. The severity of the ongoing COVID-19 pandemic-and the urgent need for safe blood products to respond to such crises-demands an immediate reconsideration of the 3-month deferral policy for MSM.We review historical HIV testing and transmission evidence, discuss the ethical ramifications of the current deferral period, and examine the issue of noncompliance with donor deferral rules. We also propose an eligibility screening format that involves an individual risk-based screening protocol and, unlike current FDA guidelines, does not effectively exclude donors on the basis of gender identity or sexual orientation. Our policy proposal would allow historically marginalized community members to participate with dignity in the blood donation process without compromising blood donation and transfusion safety outcomes. (Am J Public Health. Published online ahead of print November 19, 2020: e1-e5. https://doi.org/10.2105/AJPH.2020.305974).

18.
Res Sq ; 2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33173861

RESUMO

Epidemiological studies suggest that men exhibit a higher mortality rate to COVID-19 than women, yet the underlying biology is largely unknown. Here, we seek to delineate sex differences in the expression of entry genes ACE2 and TMPRSS2 , host responses to SARS-CoV-2, and in vitro responses to sex steroid hormone treatment. Using over 220,000 human gene expression profiles covering a wide range of age, tissues, and diseases, we found that male samples show higher expression levels of ACE2 and TMPRSS2 , especially in the older group (>60 years) and in the kidney. Analysis of 6,031 COVID-19 patients at Mount Sinai Health System revealed that men have significantly higher creatinine levels, an indicator of impaired kidney function. Further analysis of 782 COVID-19 patient gene expression profiles taken from upper airway and blood suggested men and women present profound expression differences in responses to SARS-CoV-2. Computational deconvolution analysis of these profiles revealed male COVID-19 patients have enriched kidney-specific mesangial cells in blood compared to healthy patients. Finally, we observed selective estrogen receptor modulators, but not other hormone drugs (agonists/antagonists of estrogen, androgen, and progesterone), could reduce SARS-CoV-2 infection in vitro.

19.
BMJ Open ; 10(11): e040736, 2020 11 27.
Artigo em Inglês | MEDLINE | ID: mdl-33247020

RESUMO

OBJECTIVE: The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive. DESIGN: Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive. SETTING: All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system. PARTICIPANTS: Participants over the age of 18 years were included. PRIMARY OUTCOMES: We investigated in-hospital mortality during the study period. RESULTS: A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 µg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 µg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL. CONCLUSIONS: In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.

20.
Kidney Int ; 98(5): 1347-1348, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-33126979
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