Characteristics of COVID-19 patients with multiorgan injury across the pandemic in a large academic health system in the Bronx, New York.

Purpose: To investigate the evolution of COVID-19 patient characteristics and multiorgan injury across the pandemic. Methods: This retrospective cohort study consisted of 40,387 individuals tested positive for SARS-CoV-2 in the Montefiore Health System in Bronx, NY, between March 2020 and February 2022, of which 11,306 were hospitalized. Creatinine, troponin, and alanine aminotransferase were used to define acute kidney injury (AKI), acute cardiac injury (ACI) and acute liver injury, respectively. Demographics, comorbidities, emergency department visits, hospitalization, intensive care utilization, and mortality were analyzed across the pandemic. Results: COVID-19 positive cases, emergency department visits, hospitalization and mortality rate showed four distinct waves with a large first wave in April 2020, two small (Alpha and Delta) waves, and a large Omicron wave in December 2021. Omicron was more infectious but less lethal (p = 0.05). Among hospitalized COVID-19 patients, age decreased (p = 0.014), female percentage increased (p = 0.023), Hispanic (p = 0.028) and non-Hispanic Black (p = 0.05) percentages decreased, and patients with pre-existing diabetes (p = 0.002) and hypertension (p = 0.04) decreased across the pandemic. More than half (53.1%) of hospitalized patients had major organ injury. Patients with AKI, ACI and its combinations were older, more likely males, had more comorbidities, and consisted more of non-Hispanic Black and Hispanic patients (p = 0.005). Patients with AKI and its combinations had 4-9 times higher adjusted risk of mortality than those without. Conclusions: There were shifts in demographics toward younger age and proportionally more females with COVID-19 across the pandemic. While the overall trend showed improved clinical outcomes, a substantial number of COVID-19 patients developed multi-organ injuries over time. These findings could bring awareness to at-risk patients for long-term organ injuries and help to better inform public policy and outreach initiatives.

Incidence of new-onset in-hospital and persistent diabetes in COVID-19 patients: comparison with influenza.

BACKGROUND: This study investigated the incidences and risk factors associated with new-onset persistent type-2 diabetes during COVID-19 hospitalization and at 3-months follow-up compared to influenza. METHODS: This retrospective study consisted of 8216 hospitalized, 2998 non-hospitalized COVID-19 patients, and 2988 hospitalized influenza patients without history of pre-diabetes or diabetes in the Montefiore Health System in Bronx, New York. The primary outcomes were incidences of new-onset in-hospital type-2 diabetes mellitus (I-DM) and persistent diabetes mellitus (P-DM) at 3 months (average) follow-up. Predictive models used 80%/20% of data for training/testing with five-fold cross-validation. FINDINGS: I-DM was diagnosed in 22.6% of patients with COVID-19 compared to only 3.3% of patients with influenza (95% CI of difference [0.18, 0.20]). COVID-19 patients with I-DM compared to those without I-DM were older, more likely male, more likely to be treated with steroids and had more comorbidities. P-DM was diagnosed in 16.7% of hospitalized COVID-19 patients versus 12% of hospitalized influenza patients (95% CI of difference [0.03,0.065]) but only 7.3% of non-hospitalized COVID-19 patients (95% CI of difference [0.078,0.11]). The rates of P-DM significantly decreased from 23.9% to 4.0% over the studied period. Logistic regression identified similar risk factors predictive of P-DM for COVID-19 and influenza. The adjusted odds ratio (0.90 [95% CI 0.64,1.28]) for developing P-DM was not significantly different between the two viruses. INTERPRETATION: The incidence of new-onset type-2 diabetes was higher in patients with COVID-19 than influenza. Increased risk of diabetes associated with COVID-19 is mediated through disease severity, which plays a dominant role in the development of this post-acute infection sequela. FUNDING: None.

Long-term outcomes of COVID-19 survivors with hospital AKI: association with time to recovery from AKI.

BACKGROUND: Although COVID-19 patients who developed in-hospital AKI have worse short-term outcomes, their long-term outcomes have not been fully characterized. We investigated 90-day and one-year outcomes after hospital AKI grouped by time to recovery from AKI. METHODS: This study consisted of 3,296 COVID-19 patients with hospital AKI stratified by early recovery (<48 hours), delayed recovery (2-7 days), and prolonged recovery (>7-90 days). Demographics, comorbidities, laboratory values were obtained at admission and up to one-year follow-up. Incidence of major adverse cardiovascular event (MACE) and major adverse kidney event (MAKE), rehospitalization, recurrent AKI, and new-onset chronic kidney disease (CKD) were obtained 90-days post COVID-19 discharge. RESULTS: The incidence of hospital AKI was 28.6%. Of COVID-19 patients with AKI, 58.0% experienced early recovery, 14.8% delayed recovery and 27.1% prolonged recovery. Patients with longer AKI recovery time had higher prevalence of CKD (p<0.05) and were more likely to need invasive mechanical ventilation (p<0.001) and to die (p<0.001). Many COVID-19 patients developed MAKE, recurrent AKI, and new-onset CKD within 90 days, and these incidences were higher in the prolonged recovery group (p<0.05). Incidence of MACE peaked 20-40 days post-discharge, whereas MAKE peaked 80-90 days post-discharge. Logistic regression models predicted 90-day MACE and MAKE with 82.4±1.6% and 79.6.9±2.3% accuracy, respectively. CONCLUSION: COVID-19 survivors who developed hospital AKI are at high risk for adverse cardiovascular and kidney outcomes, especially those with longer AKI recovery time and those with history of CKD. These patients may require long-term follow-up for cardiac and kidney complications.

Clinical predictors of recovery of COVID-19 associated-abnormal liver function test 2 months after hospital discharge.

This study investigated whether acute liver injury (ALI) persisted and identified predictors of ALI recovery [as indicated by alanine aminotransferase (ALT) level] at hospital discharge and 2 months post-discharge for 7595 hospitalized COVID-19 patients from the Montefiore Health System (03/11/2020-06/03/2021). Mild liver injury (mLI) was defined as ALT = 1.5-5 ULN, and severe livery injury (sLI) was ALT ≥ 5 ULN. Logistic regression was used to identify predictors of ALI onset and recovery. There were 4571 (60.2%), 2306 (30.4%), 718 (9.5%) patients with no liver injury (nLI), mLI and sLI, respectively. Males showed higher incidence of sLI and mLI (p < 0.05). Mortality odds ratio was 4.15 [95% CI 3.41, 5.05, p < 0.001] for sLI and 1.69 [95% CI 1.47, 1.96, p < 0.001] for mLI compared to nLI. The top predictors (ALT, lactate dehydrogenase, ferritin, lymphocytes) accurately predicted sLI onset up to three days prior. Only 33.5% of mLI and 17.1% of sLI patients (survivors) recovered completely at hospital discharge. Most ALI patients (76.7-82.4%) recovered completely ~ 2 months post-discharge. The top predictors accurately predicted recovery post discharge with 83.2 ± 2.2% accuracy. In conclusion, most COVID-19 patients with ALI recovered completely ~ 2 months post discharge. Early identification of patients at-risk of persistent ALI could help to prevent long-term liver complications.

Profiles of Burnout and Response to the COVID-19 Pandemic Among General Surgery Residents at a Large Academic Training Program.

BACKGROUND: COVID-19 has placed demands on General Surgery residents, who are already at high risk of burnout. This study examined the pandemic's impact on burnout and wellness among General Surgery residents at a large training program. METHODS: General Surgery residents at our institution completed a survey focused on self-reported burnout, mental health, perceptions of wellness resources, and changes in activities during the pandemic. Burnout was measured using the Maslach Burnout Inventory (MBI). Unsupervised machine learning (k-means clustering) was used to identify profiles of burnout and comparisons between profiles were made. RESULTS: Of 82 eligible residents, 51 completed the survey (62% response rate). During COVID-19, 63% of residents had self-described burnout, 43% had depression, 18% acknowledged binge drinking/drug use, and 8% had anxiety. There were no significant differences from pre-pandemic levels (p all >.05). Few residents perceived available wellness resources as effective (6%). Based on MBI scores, the clustering analysis identified three clusters, characterized as "overextended", "engaged", and "ineffective". Engaged residents had the least concerning MBI scores and were significantly more likely to exercise, retain social contact during the pandemic, and had less self-reported anxiety or depression. Research residents were overrepresented in the ineffective cluster (46%), which had high rates of self-reported burnout (77%) and was characterized by the lowest personal accomplishment scores. Rates of self-reported burnout for overextended and engaged residents were 73% and 48%, respectively. CONCLUSION: Surgical residents have high rates of self-reported burnout and depression during the COVID-19 pandemic. Clusters of burnout may offer targets for individualized intervention.

Long-short-term memory machine learning of longitudinal clinical data accurately predicts acute kidney injury onset in COVID-19: a two-center study.

OBJECTIVES: This study used the long-short-term memory (LSTM) artificial intelligence method to model multiple time points of clinical laboratory data, along with demographics and comorbidities, to predict hospital-acquired acute kidney injury (AKI) onset in patients with COVID-19. METHODS: Montefiore Health System data consisted of 1982 AKI and 2857 non-AKI (NAKI) hospitalized patients with COVID-19, and Stony Brook Hospital validation data consisted of 308 AKI and 721 NAKI hospitalized patients with COVID-19. Demographic, comorbidities, and longitudinal (3 days before AKI onset) laboratory tests were analyzed. LSTM was used to predict AKI with fivefold cross-validation (80%/20% for training/validation). RESULTS: The top predictors of AKI onset were glomerular filtration rate, lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, and C-reactive protein. Longitudinal data yielded marked improvement in prediction accuracy over individual time points. The inclusion of comorbidities and demographics further improves prediction accuracy. The best model yielded an area under the curve, accuracy, sensitivity, and specificity to be 0.965 ± 0.003, 89.57 ± 1.64%, 0.95 ± 0.03, and 0.84 ± 0.05, respectively, for the Montefiore validation dataset, and 0.86 ± 0.01, 83.66 ± 2.53%, 0.66 ± 0.10, 0.89 ± 0.03, respectively, for the Stony Brook Hospital validation dataset. CONCLUSION: LSTM model of longitudinal clinical data accurately predicted AKI onset in patients with COVID-19. This approach could help heighten awareness of AKI complications and identify patients for early interventions to prevent long-term renal complications.

Outcomes of Hospitalized Patients With COVID-19 With Acute Kidney Injury and Acute Cardiac Injury.

PURPOSE: This study investigated the incidence, disease course, risk factors, and mortality in COVID-19 patients who developed both acute kidney injury (AKI) and acute cardiac injury (ACI), and compared to those with AKI only, ACI only, and no injury (NI). METHODS: This retrospective study consisted of hospitalized COVID-19 patients at Montefiore Health System in Bronx, New York between March 11, 2020 and January 29, 2021. Demographics, comorbidities, vitals, and laboratory tests were collected during hospitalization. Predictive models were used to predict AKI, ACI, and AKI-ACI onset. Longitudinal laboratory tests were analyzed with time-lock to discharge alive or death. RESULTS: Of the 5,896 hospitalized COVID-19 patients, 44, 19, 9, and 28% had NI, AKI, ACI, and AKI-ACI, respectively. Most ACI presented very early (within a day or two) during hospitalization in contrast to AKI (p < 0.05). Patients with combined AKI-ACI were significantly older, more often men and had more comorbidities, and higher levels of cardiac, kidney, liver, inflammatory, and immunological markers compared to those of the AKI, ACI, and NI groups. The adjusted hospital-mortality odds ratios were 17.1 [95% CI = 13.6-21.7, p < 0.001], 7.2 [95% CI = 5.4-9.6, p < 0.001], and 4.7 [95% CI = 3.7-6.1, p < 0.001] for AKI-ACI, ACI, and AKI, respectively, relative to NI. A predictive model of AKI-ACI onset using top predictors yielded 97% accuracy. Longitudinal laboratory data predicted mortality of AKI-ACI patients up to 5 days prior to outcome, with an area-under-the-curve, ranging from 0.68 to 0.89. CONCLUSIONS: COVID-19 patients with AKI-ACI had markedly worse outcomes compared to those only AKI, ACI and NI. Common laboratory variables accurately predicted AKI-ACI. The ability to identify patients at risk for AKI-ACI could lead to earlier intervention and improvement in clinical outcomes.

Clinical predictors of acute cardiac injury and normalization of troponin after hospital discharge from COVID-19.

BACKGROUND: Although acute cardiac injury (ACI) is a known COVID-19 complication, whether ACI acquired during COVID-19 recovers is unknown. This study investigated the incidence of persistent ACI and identified clinical predictors of ACI recovery in hospitalized patients with COVID-19 2.5 months post-discharge. METHODS: This retrospective study consisted of 10,696 hospitalized COVID-19 patients from March 11, 2020 to June 3, 2021. Demographics, comorbidities, and laboratory tests were collected at ACI onset, hospital discharge, and 2.5 months post-discharge. ACI was defined as serum troponin-T (TNT) level >99th-percentile upper reference limit (0.014ng/mL) during hospitalization, and recovery was defined as TNT below this threshold 2.5 months post-discharge. Four models were used to predict ACI recovery status. RESULTS: There were 4,248 (39.7%) COVID-19 patients with ACI, with most (93%) developed ACI on or within a day after admission. In-hospital mortality odds ratio of ACI patients was 4.45 [95%CI: 3.92, 5.05, p<0.001] compared to non-ACI patients. Of the 2,880 ACI survivors, 1,114 (38.7%) returned to our hospitals 2.5 months on average post-discharge, of which only 302 (44.9%) out of 673 patients recovered from ACI. There were no significant differences in demographics, race, ethnicity, major commodities, and length of hospital stay between groups. Prediction of ACI recovery post-discharge using the top predictors (troponin, creatinine, lymphocyte, sodium, lactate dehydrogenase, lymphocytes and hematocrit) at discharge yielded 63.73%-75.73% accuracy. INTERPRETATION: Persistent cardiac injury is common among COVID-19 survivors. Readily available patient data accurately predict ACI recovery post-discharge. Early identification of at-risk patients could help prevent long-term cardiovascular complications. FUNDING: None.

Longitudinal progression of clinical variables associated with graded liver injury in COVID-19 patients.

BACKGROUND: Hospital-acquired liver injury is associated with worse outcomes in COVID-19. This study investigated the temporal progression of clinical variables of in-hospital liver injury in COVID-19 patients. METHODS: COVID-19 patients (n = 1361) were divided into no, mild and severe liver injury (nLI, mLI and sLI) groups. Time courses of laboratory variables were time-locked to liver-injury onset defined by alanine aminotransferase level. Predictors of liver injury were identified using logistic regression. RESULTS: The prevalence of mLI was 39.4% and sLI was 9.2%. Patients with escalated care had higher prevalence of sLI (23.2% vs. 5.0%, p < 0.05). sLI developed 9.4 days after hospitalization. sLI group used more invasive ventilation, anticoagulants, steroids, and dialysis (p < 0.05). sLI, but not mLI, had higher adjusted mortality odds ratio (= 1.37 [95% CI 1.10, 1.70], p = 0.005). Time courses of the clinical variables of the sLI group differed from those of the nLI and mLI group. In the sLI group, alanine aminotransferase, procalcitonin, ferritin, and lactate dehydrogenase showed similar temporal profiles, whereas white-blood-cell count, D-dimer, C-reactive protein, respiration and heart rate were elevated early on, and lymphocyte and SpO2 were lower early on. The top predictors of sLI were alanine aminotransferase, lactate dehydrogenase, respiration rate, ferritin, and lymphocyte, yielding an AUC of 0.98, 0.92, 0.88 and 0.84 at 0, - 1, - 2 and - 3 days prior to onset, respectively. CONCLUSIONS: This study identified key clinical variables predictive of liver injury in COVID-19, which may prove useful for management of liver injury. Late onset of sLI and more aggressive care are suggestive of treatment-related hepatotoxicity.

Longitudinal prediction of hospital-acquired acute kidney injury in COVID-19: a two-center study.

BACKGROUND: To investigate the temporal characteristics of clinical variables of hospital-acquired acute kidney injury (AKI) in COVID-19 patients and to longitudinally predict AKI onset. METHODS: There were 308 hospital-acquired AKI and 721 non-AKI (NAKI) COVID-19 patients from Stony Brook Hospital (New York, USA) data, and 72 hospital-acquired AKI and 303 NAKI COVID-19 patients from Tongji Hospital (Wuhan, China). Demographic, comorbidities, and longitudinal (3 days before and 3 days after AKI onset) clinical variables were used to compute odds ratios for and longitudinally predict hospital-acquired AKI onset. RESULTS: COVID-19 patients with AKI were more likely to die than NAKI patients (31.5% vs 6.9%, adjusted p < 0.001, OR = 4.67 [95% CI 3.1, 7.0], Stony Brook data). AKI developed on average 3.3 days after hospitalization. Procalcitonin was elevated prior to AKI onset (p < 0.05), peaked, and remained elevated (p < 0.05). Alanine aminotransferase, aspartate transaminase, ferritin, and lactate dehydrogenase peaked the same time as creatinine, whereas D-dimer and brain natriuretic peptide peaked a day later. C-reactive protein, white blood cell and lymphocyte showed group differences - 2 days prior (p < 0.05). Top predictors were creatinine, procalcitonin, white blood cells, lactate dehydrogenase, and lymphocytes. They predicted AKI onset with areas under curves (AUCs) of 0.78, 0.66, and 0.56 at 0, - 1, and - 2 days prior, respectively. When tested on the Tongji Hospital data, the AUCs were 0.80, 0.79, and 0.77, respectively. CONCLUSIONS: Time-locked longitudinal data provide insight into AKI progression. Commonly clinical variables reasonably predict AKI onset a few days prior. This work may lead to earlier recognition of AKI and treatment to improve clinical outcomes.

Longitudinal Clinical Profiles of Hospital vs. Community-Acquired Acute Kidney Injury in COVID-19.

Acute kidney injury (AKI) is associated with high mortality in coronavirus disease 2019 (COVID-19). However, it is unclear whether patients with COVID-19 with hospital-acquired AKI (HA-AKI) and community-acquired AKI (CA-AKI) differ in disease course and outcomes. This study investigated the clinical profiles of HA-AKI, CA-AKI, and no AKI in patients with COVID-19 at a large tertiary care hospital in the New York City area. The incidence of HA-AKI was 23.26%, and CA-AKI was 22.28%. Patients who developed HA-AKI were older and had more comorbidities compared to those with CA-AKI and those with no AKI (p < 0.05). A higher prevalence of coronary artery disease, heart failure, and chronic kidney disease was observed in those with HA-AKI compared to those with CA-AKI (p < 0.05). Patients with CA-AKI received more invasive and non-invasive mechanical ventilation, anticoagulants, and steroids compared to those with HA-AKI (p < 0.05), but patients with HA-AKI had significantly higher mortality compared to those with CA-AKI after adjusting for demographics and clinical comorbidities (adjusted odds ratio = 1.61, 95% confidence interval = 1.1-2.35, p < 0.014). In addition, those with HA-AKI had higher markers of inflammation and more liver injury (p < 0.05) compared to those with CA-AKI. These results suggest that HA-AKI is likely part of systemic multiorgan damage and that kidney injury contributes to worse outcomes. These findings provide insights that could lead to better management of COVID-19 patients in time-sensitive and potentially resource-constrained environments.