Association of Severe Outcomes With Underlying Diseases Among Hospitalized COVID-19 Patients: A Retrospective Cohort Study

In-center hemodialysis (HD) patients face greater communicable disease risks, including drug-resistant bacterial colonization and viral hepatitis, compared with home dialysis patients, who limit these risks, avoiding three-times weekly travel to dialysis clinics for treatments (1,2). Minimizing the high coronavirus disease 2019 (COVID-19) morbidity in dialysis patients is essential (3). We explored severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive rates, COVID-19–related hospitalization, mortality, and intensive care unit (ICU) admission by dialysis modality in Ontario, Canada. Data collection was in accordance with Ontario Health's legislative authority under the Ontario Personal Health Information Protection Act of 2004. We linked seven administrative health databases including the Ontario Renal Reporting System, which captures the modality and treatment changes of all adult (>18 years) home dialysis (peritoneal dialysis or home HD) or center-based HD patients across Ontario. Our observation period was between March 1, 2020 and November 20, 2020. For individuals, demographic data, neighborhood income quintile, location, residence in long-term care, comorbidity, hospitalization, ICU admission, deaths, and SARS-CoV-2 provincial RT-PCR testing and results information was obtained. Assuming a 14-day SARS-CoV-2 incubation period, COVID-19 infection was ascribed to the dialysis modality after 14 consecutive days of a home or in-center modality. Patients were followed until death, kidney transplantation, or study end. Follow-up SARS-CoV-2 tests after initial positive results were excluded in ascertaining testing rates. Long-term care residents and regional programs with no COVID-19 infections during the study period were excluded. Event rates for the following were defined as: (1) SARS-CoV-2 tests; (2) positive SARS-CoV-2 tests; (3) initial COVID-19 hospitalization (hospitalization within 1 week of SARS-CoV-2 positivity and/or hospitalization with an international classification of diseases-10 diagnosis of COVID-19); (4) COVID-19 mortality or ICU admission (admission to an ICU with COVID-19 during the initial COVID-19 hospitalization or death within 30 days of COVID-19 admission or SARS-CoV-2 positivity); (5) non–COVID-19 mortality (deaths during the study period not occurring within 30 days of SARS-CoV-2 positivity or COVID-19 admission; and (6) all-cause mortality. Unadjusted and adjusted rate ratios (ARR) for these events were calculated by dialysis modality using a log-binomial model. Logistic regression was used to calculate the adjusted odds ratio (AOR) of hospitalization and ICU admission and/or 30-day mortality by dialysis modality among those with COVID-19 infection. All models were adjusted for factors as indicated in Table 1. Marginal generalized estimating equations and a working dependence correlation structure were used to account for patients contributing patient-times to both modalities. Analyses were performed using SAS Version 9.4 SAS Institute, Cary, NC). Table 1. - Adjusted rate ratios for SARS-CoV-2 and COVID-19 outcomes by dialysis modality Outcome Number with Outcome/ Person Days Rate (per 100,000 person-days) Unadjusted Rate Ratio(95% CI) Adjusted Rate Ratio(95% CI) SARS-CoV-2 tests In-center HD 20804/2,084,665 998 1.0 (Ref) 1.0 (Ref) Home dialysis 2317/761,059 304 0.35 (0.34 to 0.38) 0.37 (0.35 to 0.38) SARS-CoV-2 positive In-center HD 182/2,084,665 8.7 1.0 (Ref) 1.0 (Ref) Home dialysis 34/761,059 4.5 0.59 (0.41 to 0.86) 0.57 (0.39 to 0.83) COVID-19 Hospitalization In-center HD 177/2,084,665 8.5 1.0 (Ref) 1.0 (Ref) Home dialysis 29/761,059 3.8 0.53 (0.38 to 0.75) 0.57 (0.40 to 0.81) COVID-19 ICU admission 30-day mortality In-center HD 45/2,084,665 2.2 1.0 (Ref) 1.0 (Ref) Home dialysis 6/761,059 0.8 0.37 (0.16 to 0.85) 0.44 (0.18 to 1.09) Overall Mortality In-center HD 1030/2,084,665 49.4 1.0 (Ref) 1.0 (Ref) Home dialysis 283/761,059 37.2 0.75 (0.66 to 0.86) 0.94 (0.82 to 1.08) Non-COVID-19 mortality In-center HD 996/2,084,665 47.8 1.0 (Ref) 1.0 (Ref) Home dialysis 278/761,059 36.5 0.76 (0.67 to 0.87) 0.96 (0.83 to 1.09) Mortality reported over the study period. All models adjusted for age, gender, diabetes, length of time on dialysis, race, neighborhood income quintile, geographic location, and prior kidney transplantation. A total of 587 patients contributed to both modalities during the study period. Linked databases included: The Ontario Renal Reporting System, The Registered Persons Database, The Ontario Laboratory Information System COVID-19 database, The Ontario Renal Network COVID-19 data collection tool, The Canadian Institute for Health Information Discharge Abstract Database, The Ontario Health Insurance Plan (was used to determined residency in long-term care), and the Postal Code Conversion File (Statistics Canada; was linked via postal codes to determine neighborhood income quintiles and geographic location). 95% CI, 95% confidence interval; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; COVID-19, coronavirus disease; HD-hemodialysis; ICU, intensive care unit. We identified 3622 home dialysis (n=2853 peritoneal dialysis, n=769 home HD) and 9890 center-based HD patients (761,059 and 2,084,665 person-days, respectively). In-center patients were older (66.0±15 versus 63±15 years) and of longer dialysis vintage (median interquartile range, 2 [1–4] versus 2 [1–3] years), and a greater proportion had diabetes (53% versus 41%) compared with home dialysis patients. Fifty-three percent and 49% of home dialysis and in-center patients were in the greater Toronto area, respectively. SARS-CoV-2 testing rates were lower in home versus in-center dialysis patients (ARR, 0.37; 95% confidence interval [95% CI], 0.35 to 0.38). Six positive SARS-COV-2 episodes occurring within 14 days of dialysis initiation/modality transition were excluded. Positive SARS-CoV-2 tests and COVID-19 hospitalization rates were lower in home compared with in-center dialysis patients. COVID-19–related ICU admission and mortality (ARR, 0.44; 95% CI, 0.18 to 1.09) was lower in home versus in-center patients but did not reach statistical significance (Table 1). Among COVID-19–infected individuals, hospitalization occurred in 85% (29 of 34) and 86% (177 of 205) of home and in-center patients, respectively. Median length of hospitalization (interquartile range; days) was 13 (3–25) for in-center dialysis patients compared with 12 (11–27) for home dialysis patients. Mortality and/or ICU admission occurred in 18% (6 of 34) and 21% (45 of 205) of infected home and in-center patients, respectively. There were no differences in hospitalization (AOR, 1.3; 95% CI, 0.38 to 4.8) or death and/or ICU admission risks (AOR, 1.3; 95% CI, 0.37 to 4.8) in home compared with in-center COVID-19–infected patients. Non-COVID-19–related and overall mortality rates were similar in home versus center-based patients over the study period. We found a lower burden of COVID-19 infection, hospitalization, mortality, and ICU admission in community-dwelling home dialysis versus in-center patients. Our findings may relate to greater case finding in the in-center population, more frequent health care encounters, and routine screening/outbreak surveillance, which was at the program's discretion. If increased testing among in-center HD patients was the only explanation for the higher rates of COVID-19, one would have expected a disproportionate excess of milder cases (i.e., SARS-CoV-2 positivity not requiring hospital admission) among in-center compared with home dialysis patients. However, among in-center HD patients, we also observed higher rates of COVID-19 hospitalization, mortality, and ICU admission that may have been due to a higher infection rate rather than greater case-associated morbidity. Among COVID-19–infected individuals, we found no differences in the adjusted odds of hospitalization and ICU admission or 30-day mortality by home versus in-center treatment (albeit with limited power owing to low event rates). Our study captured over 90% of SARS-CoV-2 provincial tests. A limitation of this study is residual confounding based on unmeasured differences between in-center and home dialysis patients. One cannot exclude case-mix differences in the in-center versus home patients that may have accounted for the differences in COVID-19–related adverse event risks. We also could not distinguish between asymptomatic and symptomatic outpatient cases. Asymptomatic cases may have not been identified in the absence of mass screening. As community transmission of SARS-CoV-2 increased, and as HD facilities intensified infection prevention and control measures, differences in COVID-19 infection rates by dialysis modality may be attenuated compared with our observed findings over the early pandemic period. In the United States, rates of home dialysis continue to increase following the introduction of favorable reimbursement and policy reform (4,5). In addition to other purported benefits, a major shift to home-based dialysis care could render the ESKD population more resilient to the effects of COVID-19, reducing exposure episodes and total exposure time to SARS-CoV-2 while conferring lower future exposure risks to highly transmissible infections. Disclosures P.G. Blake is a contracted Medical Lead and Medical Director at Ontario Renal Network, Ontario Health, has received honoraria from Baxter Global for speaking engagements, and is on the Editorial Board of American Journal of Nephrology. J. Ip, Y. Tang, D. Thomas, and A. Yeung are salaried employees of Ontario Renal Network, Ontario Health. M. Oliver is a contracted Medical Lead at Ontario Renal Network, Ontario Health and is owner of Oliver Medical Management Inc., which licenses Dialysis Management Analysis and Reporting System software. He has received honoraria for speaking from Baxter Healthcare and participated on Advisory Boards for Janssen and Amgen. J. Perl reports grants from the Agency for Healthcare Research and Quality during the conduct of the study; personal fees from AstraZeneca Canada, Baxter Healthcare, DaVita Healthcare Partners, DCI, Fresenius Medical Care, LiberDi, Otsuka, and US Renal Care; research funding and salary support from Arbor Research Collaborative For Health and Agency for Healthcare Research and Quality; speakers bureau for Baxter Healthcare and Fresenius Medical Care; and is on the advisory board for Liberdi, outside of the submitted work. Funding None.

Despite the initial surge of misinformation, it is of crucial importance to comply with the best clinical practices that have been established for the care of these critically ill patients based on sound clinical research from the past.

COVID-19 in Immunocompromised Children and Adolescents.

Risk factors for hospitalization, intensive care, and mortality among patients with asthma and COVID-19

ObjectivesTo investigate the combined association of obesity, diabetes mellitus (DM) and cardiovascular disease (CVD) with severe COVID-19 outcomes in adult and elderly inpatients.DesignCross-sectional study based on registry data from Brazil’s...

Asthma is associated with increased risk of intubation but not hospitalization or death in coronavirus disease 2019

Head and Neck Cancer: A High-Risk Population for COVID-19

The Utility of CHA(2)DS(2)-VASc Scores as a Risk Assessment Tool in Low-Risk In-Hospital Patients With Coronavirus Disease 2019 Infection

Novel Coronavirus COVID-19: Current Evidence and Evolving Strategies.

At the end of 2019, the Health Committee of Wuhan alerted the World Health Organization (WHO) about a cluster of patients with pneumonia of unknown etiology.1 The etiology turned out to be a novel variant of the Coronaviridae family of viruses, which includes the viruses responsible for severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). Because this new coronavirus (CoV) genetically approximates the virus responsible for the SARS outbreak (severe acute respiratory syndrome coronavirus [SARS-CoV]), the International Committee on Taxonomy of Viruses termed this new virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its associated human illness coronavirus disease 2019 (COVID-19).1 On March 11, 2020, the WHO declared this global health emergency a pandemic.2,3 Until now, clinical and research efforts have focused primarily on the etiology, accurate diagnosis, and effective acute treatment of COVID-19, with few acknowledging, let alone addressing the inevitable long-term consequences of surviving the most severe manifestation of the disease, acute respiratory distress syndrome (ARDS).4 ARDS is characterized by hypoxemic respiratory failure with bilateral lung infiltrates often necessitating tracheal intubation and mechanical ventilation. Approximately 5% of patients who test positive for COVID-19 develop a severe form of the disease that requires intensive care unit (ICU) admission, of whom two-thirds develop ARDS. The survival rate for COVID-19 patients with ARDS and ICU admission is approximately 25%.5 As of April 27, 2020, there are 2,878,196 confirmed cases of COVID-19 in more than 213 countries or areas and 198,668 associated deaths (6.9%) worldwide.6 In the worst-case scenario, as many as 29% of the US population (96 million people) will become infected, and about 1 million will require ICU support.7 If these data are extrapolated, COVID-19 could infect 2.3 billion people worldwide, with 23 million requiring ICU, and about 15 million patients with ARDS.7 If the same 25% of patients with ARDS and ICU admission survive, approximately 3.7 million patients will be discharged from hospital. These survivors will experience the chronic complications that result from the prolonged hospital stay, immobility, long-term mechanical ventilation, and mental health sequelae.7 Survivors of ARDS can develop a disorder that is characterized by persistent fatigue, weakness, and limited exercise tolerance (defined as the distance walked in 6 minutes).8,9 This limited exercise tolerance is related to the use of systemic corticosteroids to treat the disease and multiorgan dysfunction during the ICU stay. Chronic pain and weakness will develop in these survivors.9 To date, resources have been concentrated on efforts to prevent the spread of and to treat COVID-19. Concomitant efforts need to be ramped up to study the epidemiology and treatment of posttraumatic stress disorder (PTSD), chronic pain, sleep disorders, fibromyalgia, and fatigue in COVID-19 survivors. Two possible mechanisms may explain the post-SARS syndrome. The first is the psychological effects of a prolonged ICU admission on sleep and mood/affect. The ICU admission may lead to an exacerbation of patient mental health issues, including a feeling of emptiness due to separation and isolation from family and friends, to prolonged sedation, a breakdown of one's social network, and anxiety about serious health conditions and survival.9 The second is the muscle atrophy due to immobility and general inflammation and neurological tropism with CoV.9,10 As was the case with SARS, COVID-19 has resulted in a large number of patients being admitted to the hospital and developing ARDS. Chronic disorders emerge throughout the first year after acute recovery from ARDS. Chronic pain after recovery from the acute illness may prevent some patients from returning to work, necessitating a need to change their profession or even to withdraw completely from any work.11 Of note, only 16% of ARDS survivors return to work 3 months after ICU discharge, 32% after 6 months, and 49% after 12 months.9 The probability that the patient will become unemployed is determined by patient's age and the duration of hospitalization.8 Furthermore, the mean Barthel Index in ARDS survivors 6 months after ICU discharge (82.3 ± 22.9) is significantly less than that in non-ARDS patients (89.6 ± 23.2) (P = .007).8 Loss of self-sufficiency and self-esteem compound the mental health sequelae. The challenge of reintegrating ARDS survivors from COVID-19 into workplace is vital for the recovery of the local, regional, and national economies. Currently, health care systems and governments are understandably focused on managing the acute phase of the disease, improving the survival rate, and decreasing the rate of disease transmission. However, clinicians and health policymakers must begin to formulate strategies to address and improve the long-term mental health sequelae of COVID-19.12 The first and most immediate strategy is to identify those who are at increased risk for developing PTSD after such a natural disaster (eg, those with chronic health conditions and emotional stress) before the disaster occurs. Then, to target support and resource programs to mitigate the PTSD and other mental health issues, should they develop after the natural disaster like a pandemic.13 Previous experience suggested that up to 30% of survivors of ARDS develop PTSD, with elderly patients with preexisting depression and low socioeconomic groups being the most severely affected.9 In 1 report from Canada, PTSD was greater in health care workers associated with the SARS quarantine orders. This is not surprising considering the enormous stress frontline workers endured during the care of SARS patients, which was compounded by the stress from remaining in strict quarantine between hospital shifts.10 In those who developed these mental health sequelae, symptoms persisted for at least 4 years after the SARS outbreak and other natural disasters―likely a similar pattern will be seen after the COVID-19 pandemic.10 Anticipating the risks posed by a COVID-19 pandemic to both patients and health care workers should prompt authorities to mobilize resources for these purposes and to convene multidisciplinary teams as the pandemic surges and begins to dissipate, to identify the most vulnerable patients and providers, and to longitudinally manage their mental health challenges. The second strategy is to monitor survivors of ARDS from COVID-19 to identify risk factors for the development of PTSD, chronic pain, and a fibromyalgia-like syndrome.14 However, this surveillance must also include therapeutic tools (pharmacological, psychological, and occupational) aimed at attenuating the risk of developing a pain syndrome and its sequelae. During the initial ICU stay, basic opioid sparing is necessary, for example, using α2 agonists to prevent opioid dependence after ICU discharge.15 Other preventive measures include early physical rehabilitation to maintain full range of motion of joints and to mitigate against muscle atrophy, virtual reality to distract patients from pain, and music therapy to improve the endogenous opioid system.15 After discharge from hospital, ARDS survivors must be tracked to ensure that an integrated cognitive therapy plan is instituted for PTSD with medications for depression and sleep disturbances. The third and final strategy must focus on planning multidisciplinary, multicenter studies to identify the prevalence and natural history (clinical trajectory) of physical and psychological disability, including chronic pain and other long-term sequelae, in survivors of ARDS from COVID-19 to assess the effectiveness of the treatments provided. COVID-19 patients who survive ARDS are more likely to be severely affected by chronic pain compared with those who only experience mild-to-moderate infections, but the possible onset of chronic pain should not be underestimated even in those afflicted with milder forms of the disease. The survivors of the COVID-19 will find themselves facing a completely different world, with distorted human relationships and social fabric, along with a totally changed political and economic context. This requires that clinicians globally share their experiences, data, and treatment successes and failures for each of these sequelae. Fortunately, intensivists and pain medicine specialists share many common interests that in many instances are superimposable. The risk that we will face as health care professionals is that once the acute phase of the COVID-19 pandemic wanes, the chronic phase will begin and present very different challenges for which the health care community globally should be prepared and we refer here to a surge in opioid dependency and mental and physical disabilities. DISCLOSURES Name: Alessandro Vittori, MD. Contribution: This author helped with all sections of the manuscript, writing, editing, and submission. Name: Jerrold Lerman, MD, FRCPC, FANZCA. Contribution: This author helped write and revise the manuscript. Name: Marco Cascella, MD. Contribution: This author helped write and revise the manuscript. Name: Andrea D. Gomez-Morad, MD. Contribution: This author helped write and revise the manuscript. Name: Giuliano Marchetti, MD. Contribution: This author helped write and revise the manuscript. Name: Franco Marinangeli, MD, PhD. Contribution: This author helped write and revise the manuscript. Name: Sergio G. Picardo, MD. Contribution: This author helped write and revise the manuscript. This manuscript was handled by: Thomas R. Vetter, MD, MPH.

Prevalence of obesity among adult inpatients with COVID-19 in France

Background and ObjectivesPeople with multiple sclerosis (MS) are a vulnerable group for severe coronavirus disease 2019 (COVID-19), particularly those taking immunosuppressive disease-modifying therapies (DMTs). We examined the characteristics of COVID-19 severity in an international sample of people with MS.MethodsData from 12 data sources in 28 countries were aggregated (sources could include patients from 1–12 countries). Demographic (age, sex), clinical (MS phenotype, disability), and DMT (untreated, alemtuzumab, cladribine, dimethyl fumarate, glatiramer acetate, interferon, natalizumab, ocrelizumab, rituximab, siponimod, other DMTs) covariates were queried, along with COVID-19 severity outcomes, hospitalization, intensive care unit (ICU) admission, need for artificial ventilation, and death. Characteristics of outcomes were assessed in patients with suspected/confirmed COVID-19 using multilevel mixed-effects logistic regression adjusted for age, sex, MS phenotype, and Expanded Disability Status Scale (EDSS) score.ResultsSix hundred fifty-seven (28.1%) with suspected and 1,683 (61.9%) with confirmed COVID-19 were analyzed. Among suspected plus confirmed and confirmed-only COVID-19, 20.9% and 26.9% were hospitalized, 5.4% and 7.2% were admitted to ICU, 4.1% and 5.4% required artificial ventilation, and 3.2% and 3.9% died. Older age, progressive MS phenotype, and higher disability were associated with worse COVID-19 outcomes. Compared to dimethyl fumarate, ocrelizumab and rituximab were associated with hospitalization (adjusted odds ratio [aOR] 1.56, 95% confidence interval [CI] 1.01–2.41; aOR 2.43, 95% CI 1.48–4.02) and ICU admission (aOR 2.30, 95% CI 0.98–5.39; aOR 3.93, 95% CI 1.56–9.89), although only rituximab was associated with higher risk of artificial ventilation (aOR 4.00, 95% CI 1.54–10.39). Compared to pooled other DMTs, ocrelizumab and rituximab were associated with hospitalization (aOR 1.75, 95% CI 1.29–2.38; aOR 2.76, 95% CI 1.87–4.07) and ICU admission (aOR 2.55, 95% CI 1.49–4.36; aOR 4.32, 95% CI 2.27–8.23), but only rituximab was associated with artificial ventilation (aOR 6.15, 95% CI 3.09–12.27). Compared to natalizumab, ocrelizumab and rituximab were associated with hospitalization (aOR 1.86, 95% CI 1.13–3.07; aOR 2.88, 95% CI 1.68–4.92) and ICU admission (aOR 2.13, 95% CI 0.85–5.35; aOR 3.23, 95% CI 1.17–8.91), but only rituximab was associated with ventilation (aOR 5.52, 95% CI 1.71–17.84). Associations persisted on restriction to confirmed COVID-19 cases. No associations were observed between DMTs and death. Stratification by age, MS phenotype, and EDSS score found no indications that DMT associations with COVID-19 severity reflected differential DMT allocation by underlying COVID-19 severity.DiscussionUsing the largest cohort of people with MS and COVID-19 available, we demonstrated consistent associations of rituximab with increased risk of hospitalization, ICU admission, and need for artificial ventilation and of ocrelizumab with hospitalization and ICU admission. Despite the cross-sectional design of the study, the internal and external consistency of these results with prior studies suggests that rituximab/ocrelizumab use may be a risk factor for more severe COVID-19.

Walking the line between benefit and harm from tracheostomy in COVID-19

BackgroundAcute kidney injury (AKI) is one of the most common and significant problems in patients with Coronavirus Disease 2019 (COVID-19). However, little is known about the incidence and impact of AKI occurring in the community or early in the hospital admission. The traditional Kidney Disease Improving Global Outcomes (KDIGO) definition can fail to identify patients for whom hospitalisation coincides with recovery of AKI as manifested by a decrease in serum creatinine (sCr). We hypothesised that an extended KDIGO (eKDIGO) definition, adapted from the International Society of Nephrology (ISN) 0by25 studies, would identify more cases of AKI in patients with COVID-19 and that these may correspond to community-acquired AKI (CA-AKI) with similarly poor outcomes as previously reported in this population.Methods and findingsAll individuals recruited using the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC)–World Health Organization (WHO) Clinical Characterisation Protocol (CCP) and admitted to 1,609 hospitals in 54 countries with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection from February 15, 2020 to February 1, 2021 were included in the study. Data were collected and analysed for the duration of a patient’s admission. Incidence, staging, and timing of AKI were evaluated using a traditional and eKDIGO definition, which incorporated a commensurate decrease in sCr. Patients within eKDIGO diagnosed with AKI by a decrease in sCr were labelled as deKDIGO. Clinical characteristics and outcomes—intensive care unit (ICU) admission, invasive mechanical ventilation, and in-hospital death—were compared for all 3 groups of patients. The relationship between eKDIGO AKI and in-hospital death was assessed using survival curves and logistic regression, adjusting for disease severity and AKI susceptibility. A total of 75,670 patients were included in the final analysis cohort. Median length of admission was 12 days (interquartile range [IQR] 7, 20). There were twice as many patients with AKI identified by eKDIGO than KDIGO (31.7% versus 16.8%). Those in the eKDIGO group had a greater proportion of stage 1 AKI (58% versus 36% in KDIGO patients). Peak AKI occurred early in the admission more frequently among eKDIGO than KDIGO patients. Compared to those without AKI, patients in the eKDIGO group had worse renal function on admission, more in-hospital complications, higher rates of ICU admission (54% versus 23%) invasive ventilation (45% versus 15%), and increased mortality (38% versus 19%). Patients in the eKDIGO group had a higher risk of in-hospital death than those without AKI (adjusted odds ratio: 1.78, 95% confidence interval: 1.71 to 1.80, p-value < 0.001). Mortality and rate of ICU admission were lower among deKDIGO than KDIGO patients (25% versus 50% death and 35% versus 70% ICU admission) but significantly higher when compared to patients with no AKI (25% versus 19% death and 35% versus 23% ICU admission) (all p-values <5 × 10−5). Limitations include ad hoc sCr sampling, exclusion of patients with less than two sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis.ConclusionsAn extended KDIGO definition of AKI resulted in a significantly higher detection rate in this population. These additional cases of AKI occurred early in the hospital admission and were associated with worse outcomes compared to patients without AKI.

Background The association between anemia and severity of infection as well as mortality rates among patients infected with COVID-19 has scarcely been studied. This is the first study UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate. Methods A retro-prospective chart review of hospitalized COVID-19 patients was conducted in a large COVID-19 referral hospital in UAE. The study included adult patients with confirmed COVID-19. Clinical and laboratory data, severity of the disease, ICU admissions, and mortality rates were analyzed and correlated to the presence of anemia among the patients. Results A total of 3092 patients were included. 362 patients (11.7%) were anemic and most of the cases were between asymptomatic and mild COVID-19 (77.4%, n=2393). Among patients with anemia, 30.1% (n=109) had moderate to severe COVID-19. Statistically, anemia was associated significantly with a higher risk for severe COVID-19 outcome compared to nonanemic patients (AOR:1.59, 95% CI:1.24-2.04, p&lt;0.001). Intensive care unit (ICU) admission was almost 3 times higher among anemic patients compared to nonanemic (AOR:2.83,95% CI:1.89-4.25, p&lt;0.001). In addition, the overall mortality rate of 2.8% (n=87) was 2.5-fold higher in anemic than nonanemic patients (OR:2.56, CI: 1.49-4.06, p&lt;0.001). Moreover, older age (≥48-year-old) and male gender were independent predictors for severe illness (Age: OR=1.26, CI:1.07-1.51, p=0.006; Gender: OR:1.43,CI:1.15-1.78, p&lt;0.001)) and ICU admission (Age: OR:2.08, CI:1.47-2.94, p&lt;0.001; Gender: OR: 1.83, CI:1.12-3.00, p=0.008) whereas only age ≥48 years old contributed to higher mortality rate (OR:1.60, CI:1.04-2.46, p=0.034). Conclusion Anemia was a major risk factor for severe COVID-19, ICU admission and mortality among hospitalized COVID-19 patients. Thus, healthcare providers should be aware of monitoring the hematological parameters among hospitalized patients with COVID-19 and anemia to reduce the risk of disease complications and mortality. This association should also be considered in other infectious diseases.