The correlation study on chest CT features and kidney injury in severe COVID-19 pneumonia from a multicenter cohort study.

Background: Among confirmed severe COVID-19 patients, although the serum creatinine level is normal, they also have developed kidney injury. Early detection of kidney injury can guide doctors to choose drugs reasonably. Study found that COVID-19 have some special chest CT features. The study aimed to explore which chest CT features are more likely appear in severe COVID-19 and the relationship between related (special) chest CT features and kidney injury or clinical prognosis. Methods: In this retrospective study, 162 patients of severe COVID-19 from 13 medical centers in China were enrolled and divided into three groups according to the estimated glomerular filtration rate (eGFR) level: Group A (eGFR < 60 ml/min/1.73 m2), Group B (60 ml/min/1.73 m2 ≤ eGFR < 90 ml/min/1.73 m2), and Group C (eGFR ≥ 90 ml/min/1.73 m2). The demographics, clinical features, auxiliary examination, and clinical prognosis were collected and compared. The chest CT features and eGFR were assessed using univariate and multivariate Cox regression. The influence of chest CT features on eGFR and clinical prognosis were calculated using the Cox proportional hazards regression model. Results: Demographic and clinical features showed significant differences in age, hypertension, and fatigue among the Group A, Group B, and Group C (all P < 0.05). Auxiliary examination results revealed that leukocyte count, platelet count, C-reactive protein, aspartate aminotransferase, creatine kinase, respiratory rate ≥ 30 breaths/min, and CT images rapid progression (>50%) within 24-48 h among the three groups were significantly different (all P < 0.05). Compared to Group C (all P < 0.017), Groups A and B were more likely to show crazy-paving pattern. Logistic regression analysis indicated that eGFR was an independent risk factor of the appearance of crazy-paving pattern. The eGFR and crazy-paving pattern have a mutually reinforcing relationship, and eGFR (HR = 0.549, 95% CI = 0.331-0.909, P = 0.020) and crazy-paving pattern (HR = 2.996, 95% CI = 1.010-8.714, P = 0.048) were independent risk factors of mortality. The mortality of severe COVID-19 with the appearance of crazy-paving pattern on chest CT was significantly higher than that of the patients without its appearance (all P < 0.05). Conclusions: The crazy-paving pattern is more likely to appear in the chest CT of patients with severe COVID-19. In severe COVID-19, the appearance of the crazy-paving pattern on chest CT indicates the occurrence of kidney injury and proneness to death. The crazy-paving pattern can be used by doctors as an early warning indicator and a guidance of reasonable drug selection.

Kidney Recovery and Death in Critically Ill Patients With COVID-19-Associated Acute Kidney Injury Treated With Dialysis: The STOP-COVID Cohort Study.

RATIONALE & OBJECTIVE: Acute kidney injury treated with kidney replacement therapy (AKI-KRT) occurs frequently in critically ill patients with coronavirus disease 2019 (COVID-19). We examined the clinical factors that determine kidney recovery in this population. STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 4,221 adults not receiving KRT who were admitted to intensive care units at 68 US hospitals with COVID-19 from March 1 to June 22, 2020 (the "ICU cohort"). Among these, 876 developed AKI-KRT after admission to the ICU (the "AKI-KRT subcohort"). EXPOSURE: The ICU cohort was analyzed using AKI severity as the exposure. For the AKI-KRT subcohort, exposures included demographics, comorbidities, initial mode of KRT, and markers of illness severity at the time of KRT initiation. OUTCOME: The outcome for the ICU cohort was estimated glomerular filtration rate (eGFR) at hospital discharge. A 3-level outcome (death, kidney nonrecovery, and kidney recovery at discharge) was analyzed for the AKI-KRT subcohort. ANALYTICAL APPROACH: The ICU cohort was characterized using descriptive analyses. The AKI-KRT subcohort was characterized with both descriptive analyses and multinomial logistic regression to assess factors associated with kidney nonrecovery while accounting for death. RESULTS: Among a total of 4,221 patients in the ICU cohort, 2,361 (56%) developed AKI, including 876 (21%) who received KRT. More severe AKI was associated with higher mortality. Among survivors, more severe AKI was associated with an increased rate of kidney nonrecovery and lower kidney function at discharge. Among the 876 patients with AKI-KRT, 588 (67%) died, 95 (11%) had kidney nonrecovery, and 193 (22%) had kidney recovery by the time of discharge. The odds of kidney nonrecovery was greater for lower baseline eGFR, with ORs of 2.09 (95% CI, 1.09-4.04), 4.27 (95% CI, 1.99-9.17), and 8.69 (95% CI, 3.07-24.55) for baseline eGFR 31-60, 16-30, ≤15 mL/min/1.73 m2, respectively, compared with eGFR > 60 mL/min/1.73 m2. Oliguria at the time of KRT initiation was also associated with nonrecovery (ORs of 2.10 [95% CI, 1.14-3.88] and 4.02 [95% CI, 1.72-9.39] for patients with 50-499 and <50 mL/d of urine, respectively, compared to ≥500 mL/d of urine). LIMITATIONS: Later recovery events may not have been captured due to lack of postdischarge follow-up. CONCLUSIONS: Lower baseline eGFR and reduced urine output at the time of KRT initiation are each strongly and independently associated with kidney nonrecovery among critically ill patients with COVID-19.

Changes in glomerular filtration rate and metabolomic differences in severely ill coronavirus disease survivors 3 months after discharge.

To explore the recovery of renal function in severely ill coronavirus disease (COVID-19) survivors and determine the plasma metabolomic profile of patients with different renal outcomes 3 months after discharge, we included 89 severe COVID-19 survivors who had been discharged from Wuhan Union Hospital for 3 months. All patients had no underlying kidney disease before admission. At patient recruitment, renal function assessment, laboratory examination, chest computed tomography (CT) were performed. Liquid chromatography-mass spectrometry was used to detect metabolites in the plasma. We analyzed the longitudinally change in the estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin-c levels using the CKD-EPI equation and explored the metabolomic differences in patients with different eGFR change patterns from hospitalization to 3 months after discharge. Lung CT showed good recovery; however, the median eGFR significantly decreased at the 3-month follow-up. Among the 89 severely ill COVID-19 patients, 69 (77.5%) showed abnormal eGFR (<90 mL/min per 1.73 m2) at 3 months after discharge. Age (odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.08-1.47, p = 0.003), body mass index (OR = 1.97, 95% CI = 1.20-3.22, p = 0.007), and cystatin-c level (OR = 1.22, 95% CI = 1.07-1.39, p = 0.003) at discharge were independent risk factors for post-discharge abnormal eGFR. Plasma metabolomics at the 3-months follow-up revealed that ß-pseudouridine, uridine, and 2-(dimethylamino) guanosine levels gradually increased with an abnormal degree of eGFR. Moreover, the kynurenine pathway in tryptophan metabolism, vitamin B6 metabolism, cysteine and methionine metabolism, and arginine biosynthesis were also perturbed in survivors with abnormal eGFR.