scholarly journals Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients

Author(s):  
Flavio Azevedo Figueiredo ◽  
Lucas Emanuel Ferreira Ramos ◽  
Rafael Tavares Silva ◽  
Magda Carvalho Pires ◽  
Daniela Ponce ◽  
...  

Background: Acute kidney injury (AKI) is frequently associated with COVID–19 and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalized COVID–19 patients. Methods: This study is part of the multicentre cohort, the Brazilian COVID–19 Registry. A total of 5,212 adult COVID–19 patients were included between March/2020 and September/2020. We evaluated four categories of predictor variables: (1) demographic data; (2) comorbidities and conditions at admission; (3) laboratory exams within 24 h; and (4) the need for mechanical ventilation at any time during hospitalization. Variable selection was performed using generalized additive models (GAM) and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. The accuracy was assessed using the area under the receiver operating characteristic curve (AUCROC). Risk groups were proposed based on predicted probabilities: non-high (up to 14.9%), high (15.0 to 49.9%), and very high risk (≥ 50.0%). Results: The median age of the model–derivation cohort was 59 (IQR 47–70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalization. The validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in–hospital mortality. Thirty–two variables were tested and four important predictors of the need for KRT during hospitalization were identified using GAM: need for mechanical ventilation, male gender, higher creatinine at admission, and diabetes. The MMCD score had excellent discrimination in derivation (AUROC = 0.929; 95% CI 0.918–0.939) and validation (AUROC = 0.927; 95% CI 0.911–0.941) cohorts an good overall performance in both cohorts (Brier score: 0.057 and 0.056, respectively). The score is implemented in a freely available online risk calculator (https://www.mmcdscore.com/). Conclusion: The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalized COVID–19 patients who may require more intensive monitoring, and can be useful for resource allocation.

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Joao B Andrade ◽  
Gisele S Silva ◽  
Jay P Mohr ◽  
Joao J Carvalho ◽  
Luisa Franciscatto ◽  
...  

Objective: To create an accurate and user-friendly pr edictive sc o re for he morrhagic t ransformation in patients not submitted to reperfusion therapies (PROpHET). Methods: We created a multivariable logistic regression model to assess the prediction of Hemorrhage Transformation (HT) for acute ischemic strokes not treated with reperfusion therapy. One point was assigned for each of gender, cardio-aortic embolism, hyperdense middle cerebral artery sign, leukoaraiosis, hyperglycemia, 2 points for ASPECTS ≤7, and -3 points for lacunar syndrome. Acute ischemic stroke patients admitted to the Fortaleza Comprehensive Stroke Center in Brazil from 2015 to 2017 were randomly selected to the derivation cohort. The validation cohort included similar, but not randomized, cases from 5 Brazilian and one American Comprehensive Stroke Centers. Symptomatic cases were defined as NIHSS ≥4 at 24 hours after the event. Results from the derivation and validation cohorts were assessed with the area under the receiver operating characteristic curve (AUC-ROC). Results: From 2,432 of acute ischemic stroke screened in Fortaleza, 448 were prospectively selected for the derivation cohort and a 7-day follow-up. From 1,847 not selected, 577 underwent reperfusion therapy, 734 were excluded due to inadequate imaging or refusal of consent, and 538 whose data were obtained retrospectively and were selected only for the validation cohort. A score ≥3 had 78% sensitivity and 75% specificity, AUC-ROC 0.82 for all cases of HT, Hosmer-Lemeshow 0.85, Brier Score 0.1, and AUC-ROC 0.83 for those with symptomatic HT. An AUC-ROC of 0.84 was found for the validation cohort of 1,910 from all 6 centers, and a score ≥3 was found in 65% of patients with HT against 11.3% of those without HT. In comparison with 8 published predictive scores of HT, PROpHET was the most accurate (p < 0.01). Conclusions: PROpHET offers a tool simple, quick and easy-to-perform to estimate risk stratification of HT in patients not submitted to RT. A digital version of PROpHET is available in www.score-prophet.com Classification of evidence: This study provides Class I evidence from prospective data acquisition.


2015 ◽  
Vol 135 (2) ◽  
pp. 72-78 ◽  
Author(s):  
Sidsel Christy Lindgaard ◽  
Jonas Nielsen ◽  
Anders Lindmark ◽  
Henrik Sengeløv

Background: Allogeneic haematopoietic stem cell transplantation (HSCT) is a procedure with inherent complications and intensive care may be necessary. We evaluated the short- and long-term outcomes of the HSCT recipients requiring admission to the intensive care unit (ICU). Methods: We retrospectively examined the outcome of 54 adult haematological HSCT recipients admitted to the ICU at the University Hospital Rigshospitalet between January 2007 and March 2012. Results: The overall in-ICU, in-hospital, 6-month and 1-year mortality rates were 46.3, 75.9, 79.6 and 86.5%, respectively. Mechanical ventilation had a statistically significant effect on in-ICU (p = 0.02), 6-month (p = 0.049) and 1-year (p = 0.014) mortality. Renal replacement therapy also had a statistically significant effect on in-hospital (p = 0.038) and 6-month (p = 0.026) mortality. Short ICU admissions, i.e. <10 days, had a statistically significant positive effect on in-hospital, 6-month and 1-year mortality (all p < 0.001). The SAPS II, APACHE II and SOFA scoring systems grossly underestimated the actual in-hospital mortality observed for these patients. Conclusion: The poor prognosis of critically ill HSCT recipients admitted to the ICU was confirmed in our study. Mechanical ventilation, renal replacement therapy and an ICU admission of ≥10 days were each risk factors for mortality in the first year after ICU admission.


2021 ◽  
Author(s):  
Gerardo Alvarez-Uria ◽  
Sumanth Gandra ◽  
Venkata R Gurram ◽  
Raghu P Reddy ◽  
Manoranjan Midde ◽  
...  

Previous COVID-19 prognostic models have been developed in hospital settings, and are not applicable to COVID-19 cases in the general population. There is an urgent need for prognostic scores aimed to identify patients at high risk of complications at the time of COVID-19 diagnosis. The RDT COVID-19 Observational Study (RCOS) collected clinical data from patients with COVID-19 admitted regardless of the severity of their symptoms in a general hospital in India. We aimed to develop and validate a simple bedside prognostic score to predict the risk of hypoxaemia or death. 4035 patients were included in the development cohort and 2046 in the validation cohort. The primary outcome occurred in 961 (23.8%) and 548 (26.8%) patients in the development and validation cohorts, respectively. The final model included 12 variables: age, systolic blood pressure, heart rate, respiratory rate, aspartate transaminase, lactate dehydrogenase, urea, C-reactive protein, sodium, lymphocyte count, neutrophil count and neutrophil/lymphocyte ratio. In the validation cohort, the area under the receiver operating characteristic curve (AUROCC) was 0.907 (95% CI, 0.892-0.922) and the Brier Score was 0.098. The decision curve analysis showed good clinical utility in hypothetical scenarios where admission of patients was decided according to the prognostic index. When the prognostic index was used to predict mortality in the validation cohort, the AUROCC was 0.947 (95% CI, 0.925-0.97) and the Brier score was 0.0188. If our results are validated in other settings, the RCOS prognostic index could help improve the decision making in the current COVID-19 pandemic, especially in resource limited-settings.


PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245281
Author(s):  
Bianca Magro ◽  
Valentina Zuccaro ◽  
Luca Novelli ◽  
Lorenzo Zileri ◽  
Ciro Celsa ◽  
...  

Backgrounds Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19. Methods and findings We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07–1.09), male sex (HR 1.62, 95%CI 1.30–2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39–2.12), diabetes (HR 1.21, 95%CI 1.02–1.45), coronary heart disease (HR 1.40 95% CI 1.09–1.80), chronic liver disease (HR 1.78, 95%CI 1.16–2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002–1.0005). The AUC was 0.822 (95%CI 0.722–0.922) in the derivation cohort and 0.820 (95%CI 0.724–0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp). Conclusions A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5987-5987
Author(s):  
Silvia Monsalvo ◽  
Belen Sevillano ◽  
Andrew Innes ◽  
Maialen Lasa ◽  
Laura Skinner ◽  
...  

Abstract Introduction: Critically ill onco-hematology patients (pts) admitted to intensive care units (ICU) have poor prognosis. Mechanical ventilation, multiple organ failures and severe sepsis are factors associated with high mortality. Current literature identifies day 5 in ICU as a specific time point at which ceilings of care should be re-addressed. Patients and methods: We retrospectively reviewed all consecutive onco-haematology patients admitted to the ICU between October 2010 and December 2015. We classified pts according to the reason for ICU admission in 5 groups: a) respiratory failure without mechanical ventilation during the first 24h; b) respiratory failure and mechanical ventilation in the first 24h; c) sepsis without respiratory failure and without renal replacement therapy in the first 24h; d) renal replacement therapy without respiratory failure regardless of septic status; and e) needing hemodynamic support without respiratory failure, sepsis or renal replacement therapy in the first 24h. After 5 days of full intensive therapy we defined a successful 5-day ICU trial for each of the five groups as follows: a) no mechanical ventilation during 5 days; b) neutrophils > 1.0 or ² 2 organ failures by day 5; c) C-reactive protein decreased by 50% or normalised lactate by day 5; d) off renal replacement therapy by day 5; and e) no inotropic support on day 5. Patients who died during the first 5 days of ICU admission were considered failures and pts who were discharged from the ICU before day 5 were considered successes. Results: 166 pts were identified, with 202 ICU admissions. The median number of ICU admissions was 1 (1-4), with 138 (84%) having 1 admission, 20 (12%) 2 admissions, 4 (2.4%) had 3 admissions and 3 (2%) 4 admissions respectively. The median length of stay in ICU was 6 days (1-95). The median duration of hospital stay prior to ICU admission was 14 days (0-104). The diagnoses were: AML 28% (n= 57), ALL 8% (n=16), CML 8% (n=16), myelofibrosis 4% (n=7), MDS 4% (n=7), myeloma 11% (n=23), NHL 30% (n=61) and Hodgkin's lymphoma 2% (n=4). Regarding pre ICU treatment, 44% (n=88) received chemotherapy, 11% (n=22) underwent autologous stem cell transplantation and 40% (n=81) allogeneic stem cell transplantation. Of those, 30% had myeloablative and 70% reduced intensity conditioning and 29 (35%) were from HLA identical sibling, 47 (58%) unrelated and 6 (7%) haplo-identical donors. The disease status was complete remission (n=77, 38%), partial remission (n=28, 14%) and stable disease (n=96, 48%). The reason for admission to ICU was respiratory failure in 53% (n=107), 19% sepsis (n=39), 16% renal failure (n=32) and 11% hemodynamic failure (n=22). The median APACHE II score was 24 (10-51), the median SOFA score was 10 (2-21) and the median SAPS-II score was 45 (0-100). APACHE II and SOFA scores were significantly greater in non-survivors vs survivors (p<0.0001). Overall 101(50%) pts survived their ICU admission and were discharged to the hematology ward. Of these, 31 (30%) died in hospital and 70 (70%) were discharged home. Estimated overall survival was 15% (95% CI 10-23) at 3 years post ICU admission. For the 5-day ICU trial we selected 138 pts with one admission. The distribution according to the different groups was: a) 56; b) 34; c) 17; d) 17 and e) 14. Overall 58 (42%) successfully passed the trial: a) 30 (53%); b) 14 (41%); c) 4 (23%); d) 7 (41%) and e) 3 (21%). Overall 41 (30%) pts failed the trial and were alive on day 5 and 39 (28%) died before day 5. The overall survival (Figure 1) for the 58 pts who passed the trial was 28% at 3 years. The overall mortality in ICU was 33% (19/58) for those who successfully passed the 5-day ICU trial, and was 71% (29/41) for those who failed. The overall survival for pts that successfully completed the 5-day ICU trial and were discharged to the hematology ward (n=39), was 49% at 3 years. Conclusions: In this study, 50% of onco-hematologic patients survived their ICU admission. The long-term overall survival was 15% at 3 years. Patients could be stratified according to the reason for admission and given an individualised 5-day trial: those who successfully completed their trial (42%) had a low ICU mortality (33%) and those who were subsequently discharged home had a long-term survival of 49% at 3 years. This study raises the possibility of offering a short-term ICU trial to onco-hematologic patients and perhaps allows for the ceiling of intensive care for those who fail the trial. Figure Figure. Disclosures MacDonald: Gilead Sciences: Speakers Bureau. Milojkovic:Ariad: Honoraria; Novartis: Honoraria; BMS: Honoraria; Pfizer: Honoraria. Apperley:Incyte: Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Ariad: Honoraria, Speakers Bureau; Bristol Myers Squibb: Honoraria, Speakers Bureau.


Neurology ◽  
2019 ◽  
Vol 92 (13) ◽  
pp. e1517-e1525 ◽  
Author(s):  
Gian Marco De Marchis ◽  
Theresa Dankowski ◽  
Inke R. König ◽  
Joachim Fladt ◽  
Felix Fluri ◽  
...  

ObjectivesTo derive and externally validate a copeptin-based parsimonious score to predict unfavorable outcome 3 months after an acute ischemic stroke (AIS).MethodsThe derivation cohort consisted of patients with AIS enrolled prospectively at the University Hospital Basel, Switzerland. The validation cohort was prospectively enrolled after the derivation cohort at the University Hospital of Bern and University Hospital Basel, Switzerland, as well as Frankfurt a.M., Germany. The score components were copeptin levels, age, NIH Stroke Scale, and recanalization therapy (CoRisk score). Copeptin levels were measured in plasma drawn within 24 hours of AIS and before any recanalization therapy. The primary outcome of disability and death at 3 months was defined as modified Rankin Scale score of 3 to 6.ResultsOverall, 1,102 patients were included in the analysis; the derivation cohort contributed 319 patients, and the validation cohort contributed 783. An unfavorable outcome was observed among 436 patients (40%). For the 3-month prediction of disability and death, the CoRisk score was well calibrated in the validation cohort, for which the area under the receiver operating characteristic curve was 0.819 (95% confidence interval [CI] 0.787–0.849). The calibrated CoRisk score correctly classified 75% of patients (95% CI 72–78). The net reclassification index between the calibrated CoRisk scores with and without copeptin was 46% (95% CI 32–60).ConclusionsThe biomarker-based CoRisk score for the prediction of disability and death was externally validated, was well calibrated, and performed better than the same score without copeptin.ClinicalTrials.gov identifierNCT00390962 (derivation cohort) and NCT00878813 (validation cohort).


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniela Ponce ◽  
Luís Gustavo Modelli de Andrade ◽  
Rolando Claure-Del Granado ◽  
Alejandro Ferreiro-Fuentes ◽  
Raul Lombardi

AbstractAcute kidney injury (AKI) is frequently associated with COVID-19 and it is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting in-hospital mortality in COVID-19 patients with AKI (AKI-COV score). This was a cross-sectional multicentre prospective cohort study in the Latin America AKI COVID-19 Registry. A total of 870 COVID-19 patients with AKI defined according to the KDIGO were included between 1 May 2020 and 31 December 2020. We evaluated four categories of predictor variables that were available at the time of the diagnosis of AKI: (1) demographic data; (2) comorbidities and conditions at admission; (3) laboratory exams within 24 h; and (4) characteristics and causes of AKI. We used a machine learning approach to fit models in the training set using tenfold cross-validation and validated the accuracy using the area under the receiver operating characteristic curve (AUC-ROC). The coefficients of the best model (Elastic Net) were used to build the predictive AKI-COV score. The AKI-COV score had an AUC-ROC of 0.823 (95% CI 0.761–0.885) in the validation cohort. The use of the AKI-COV score may assist healthcare workers in identifying hospitalized COVID-19 patients with AKI that may require more intensive monitoring and can be used for resource allocation.


2020 ◽  
Author(s):  
Lars Christian Lund ◽  
Kasper Bruun Kristensen ◽  
Mette Reilev ◽  
Steffen Christensen ◽  
Reimar W. Thomsen ◽  
...  

Background Concerns over the safety of non-steroidal anti-inflammatory drug (NSAID) use during SARS-CoV-2 infection have been raised. Objectives To study whether use of NSAIDs is associated with adverse outcomes and mortality during SARS-CoV-2 infection. Design Population based cohort study Setting Danish administrative and health registries. Participants Individuals tested positive for SARS-CoV-2 during Feb 27, 2020 to Apr 29, 2020. Treated individuals (defined as a filled NSAID prescription up to 30 days before the SARS-CoV-2 test) were matched to up to 4 non-treated individuals on propensity scores based on age, sex, relevant comorbidities and prescription fills. Outcome measures The main outcome was 30-day mortality and treated individuals were compared to untreated individuals using risk ratios (RR) and risk differences (RD). Secondary outcomes included hospitalisation, intensive care unit (ICU) admission, mechanical ventilation and acute renal replacement therapy. Results A total of 9236 SARS-CoV-2 PCR positive individuals were eligible for inclusion. Of these, 248 (2.7%) had filled a prescription for NSAIDs and 535 (5.8%) died within 30 days. In the matched analyses, treatment with NSAIDs was not associated with 30-day mortality (RR 1.02, 95% CI 0.57 to 1.82; RD 0.1%, -3.5% to 3.7%), increased risk of hospitalisation (RR 1.16, 0.87 to 1.53; RD 3.3%, -3.4% to 10%), ICU-admission (RR 1.04, 0.54 to 2.02; RD 0.2%, -3.0% to 3.4%), mechanical ventilation (RR 1.14, 0.56 to 2.30; RD 0.5%, -2.5% to 3.6%), or renal replacement therapy (RR 0.86, 0.24 to 3.09; RD -0.2%, -2.0% to 1.6%). Conclusion Use of NSAIDs was not associated with 30-day mortality, hospitalisation, ICU-admission, mechanical ventilation or renal replacement therapy in Danish individuals tested positive for SARS-CoV-2. Registration: The European Union electronic Register of Post-Authorisation Studies, EUPAS-34734 (http://www.encepp.eu/encepp/viewResource.htm?id=34735)


2021 ◽  
Author(s):  
Yuichiro Shimoyama ◽  
Osamu Umegaki ◽  
Noriko Kadono ◽  
Toshiaki Minami

Abstract This study aimed to determine whether presepsin can predict the progression of septic subclinical acute kidney injury (AKI) to septic AKI among intensive care unit (ICU) patients. Presepsin values were measured immediately after ICU admission (baseline) and on Days 2, 3, and 5 after ICU admission. Glasgow Prognostic Score, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio (PLR), Prognostic Index, and Prognostic Nutritional Index were measured at baseline. Presepsin values and these indices were compared between septic AKI and septic subclinical AKI patients. There were 38 septic AKI patients and 21 septic subclinical AKI patients. Receiver operating characteristic curve analyses revealed the following cut-off values for AKI (relative to subclinical AKI): 708.0 (pg/ml) for presepsin on Day 1 (AUC, 0.69; sensitivity, 82%; specificity, 52%), 1283.0 (pg/ml) for presepsin on Day 2 (AUC, 0.69; sensitivity, 55%; specificity, 80%), and 368.66 for PLR (AUC, 0.67; sensitivity, 71%; specificity, 62%). Multivariate logistic regression analyses revealed PLR to be a predictor of septic subclinical AKI (odds ratio, 1.0023; 95% confidence interval, 1.0000-1.0046; p=0.046). Presepsin and PLR predicted the progression of septic subclinical AKI to septic AKI and the prognosis of subclinical septic AKI patients.


2020 ◽  
Vol 76 (3) ◽  
pp. 444-446
Author(s):  
Shilpanjali Jesudason ◽  
Alyssa Fitzpatrick ◽  
Aarti Gulyani ◽  
Christopher E. Davies ◽  
Erandi Hewawasam ◽  
...  

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