Patients with type 1 diabetes are at elevated risk of developing new hypertension, chronic kidney disease and diabetic ketoacidosis after COVID-19: Up to 40 months' follow-up.

AIM: The aim was to investigate whether COVID-19 increases new incidence of hypertension (HTN), chronic kidney disease (CKD) and diabetic ketoacidosis (DKA) in patients with type 1 diabetes (T1D) up to 40 months post-infection. MATERIALS AND METHODS: Three groups of patients from the Montefiore Health System in the Bronx (1 March 2020 to 1 July 2023) were studied: T1D patients hospitalized for COVID-19 (H-COVID-19, n = 511), T1D patients with COVID-19 but not hospitalized for COVID-19 (NH-COVID-19, n = 306) and T1D patients without a positive COVID-19 test on record (non-COVID-19, n = 1547). COVID-19 patients were those with a positive polymerase-chain-reaction test on record, and non-COVID-19 patients were either tested negative or not tested on record. Cumulative incidences and adjusted hazard ratios (aHR) with 95% confidence intervals (CI) were computed with adjustment for competing risks. RESULTS: Compared to non-COVID-19 patients, both H-COVID-19 (unadjusted 19.72% vs. 3.14%, p < 0.001; aHR = 7.55 [3.33, 17.06], p < 0.001) and NH-COVID-19 (10.26% vs. 3.14%, p = 0.004; aHR = 5.08 [2.19, 11.78], p < 0.001) patients were more likely to develop new HTN. Compared to non-COVID-19 patients, both H-COVID-19 (11.41% vs. 1.14%, p < 0.001; aHR = 9.76 [4.248, 22.25], p < 0.001) and NH-COVID-19 (7.69% vs. 1.14%, p < 0.001; aHR = 6.54 [2.91, 14.67], p < 0.001) patients were more likely to develop new CKD. Compared to non-COVID-19 patients, both H-COVID-19 (4.09% vs. 1.06%, p < 0.001; aHR = 12.24 [4.09, 36.59], p < 0.001) and NH-COVID-19 (3.06% vs. 1.06%, p = 0.035; aHR = 12.94 [4.09, 40.89], p < 0.001) patients were more likely to develop new DKA at follow-up. CONCLUSION: T1D patients with COVID-19 are at higher risk of developing new HTN, CKD and DKA compared to T1D patients without COVID-19.

Analysis of schizophrenia-associated genetic markers in the HLA region as risk factors for tardive dyskinesia.

OBJECTIVES: The pathology of Tardive Dyskinesia (TD) has yet to be fully understood, but there have been proposed hypotheses for the cause of this condition. Our team previously reported a possible association of TD with the Complement Component C4 gene in the HLA region. In this study, we explored the HLA region further by examining two previously identified schizophrenia-associated HLA-region single-nucleotide polymorphisms (SNPs), namely rs13194504 and rs210133. METHODS: The SNPs rs13194504 and rs210133 were tested for association with the occurrence and severity of TD in a sample of 172 schizophrenia patients who were recruited for four studies from three different clinical sites in Canada and USA. RESULTS: The rs13194504 AA genotype was associated with decreased severity for TD as measured by Abnormal Involuntary Movement Scale (AIMS) scores (p = 0.047) but not for TD occurrence. SNP rs210133 was not significantly associated with either TD occurrence or AIMS scores. CONCLUSION: Our findings suggest that the rs13194504 AA genotype may play a role in TD severity, while SNP rs210133 may not have a major role in the risk or severity of TD.

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

BACKGROUND: Although coronavirus disease 2019 (COVID-19) patients who develop in-hospital acute kidney injury (AKI) have worse short-term outcomes, their long-term outcomes have not been fully characterized. We investigated 90-day and 1-year outcomes after hospital AKI grouped by time to recovery from AKI. METHODS: This study consisted of 3296 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 and laboratory values were obtained at admission and up to the 1-year follow-up. The incidence of major adverse cardiovascular events (MACE) and major adverse kidney events (MAKE), rehospitalization, recurrent AKI and new-onset chronic kidney disease (CKD) were obtained 90-days after COVID-19 discharge. RESULTS: The incidence of hospital AKI was 28.6%. Of the COVID-19 patients with AKI, 58.0% experienced early recovery, 14.8% delayed recovery and 27.1% prolonged recovery. Patients with a longer AKI recovery time had a higher prevalence of CKD (P < .05) and were more likely to need invasive mechanical ventilation (P < .001) and to die (P < .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 < .05). The incidence of MACE peaked 20-40 days postdischarge, whereas MAKE peaked 80-90 days postdischarge. Logistic regression models predicted 90-day MACE and MAKE with 82.4 ± 1.6% and 79.6 ± 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 times and those with a history of CKD. These patients may require long-term follow-up for cardiac and kidney complications.

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.

Schizophrenia-associated gene dysbindin-1 and tardive dyskinesia.

Tardive dyskinesia (TD) is a potentially irreversible movement disorder observed following long-term antipsychotic exposure. Its cause is unknown; however, a genetic component has been supported by studies of affected families. Dysbindin-1, encoded by the dystrobrevin-binding protein 1 DTNBP1 gene, has been associated with schizophrenia and is potentially involved in dopamine neurotransmission through its regulation of dopamine release and dopamine D2 receptor recycling, making it a candidate for investigation in TD. We investigated common variants across the DTNBP1 gene in our schizophrenia/patients with schizoaffective disorder of European ancestry. We found a number of DTNBP1 three-marker haplotypes to be associated with TD occurrence and TD severity (p < 0.05). These preliminary findings, if replicated in larger independent samples, would suggest that drugs targeting dysbindin-1 may be an option in the prevention and treatment of TD.

Incidence, characteristics, and risk factors of new liver disorders 3.5 years post COVID-19 pandemic in the Montefiore Health System in Bronx.

PURPOSE: To determine the incidence of newly diagnosed liver disorders (LD) up to 3.5-year post-acute COVID-19, and risk factors associated with new LD. METHODS: We analyzed 54,699 COVID-19 patients and 1,409,547 non-COVID-19 controls from March-11-2020 to Jan-03-2023. New liver disorders included abnormal liver function tests, advanced liver failure, alcohol and non-alcohol related liver disorders, and cirrhosis. Comparisons were made with ambulatory non-COVID-19 patients and patients hospitalized for other lower respiratory tract infections (LRTI). Demographics, comorbidities, laboratory data, incomes, insurance status, and unmet social needs were tabulated. The primary outcome was new LD at least two weeks following COVID-19 positive test. RESULTS: Incidence of new LD was not significantly different between COVID-19 and non-COVID-19 cohorts (incidence:1.99% vs 1.90% p>0.05, OR = 1.04[95%CI: 0.92,1.17], p = 0.53). COVID-19 patients with new LD were older, more likely to be Hispanic and had higher prevalence of diabetes, hypertension, chronic kidney disease, and obesity compared to patients without new LD. Hospitalized COVID-19 patients had no elevated risk of LD compared to hospitalized LRTI patients (2.90% vs 2.07%, p>0.05, OR = 1.29[0.98,1.69], p = 0.06). Among COVID-19 patients, those who developed LD had fewer patients with higher incomes (14.18% vs 18.35%, p<0.05) and more with lower incomes (21.72% vs 17.23%, p<0.01), more Medicare and less Medicaid insurance, and more patients with >3 unmet social needs (6.49% vs 2.98%, p<0.001) and fewer with no unmet social needs (76.19% vs 80.42%, p<0.001). CONCLUSIONS: Older age, Hispanic ethnicity, and obesity, but not COVID-19 status, posed increased risk for developing new LD. Lower socioeconomic status was associated with higher incidence of new LD.

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.

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.

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.

Effect of routine jejunostomy tube insertion in esophagectomy: A systematic review and meta-analysis.

BACKGROUND: Routine feeding jejunostomy tube post esophagectomy is being revaluated because of its associated postoperative complications. We performed a systematic review and meta-analysis to evaluate the effect of routine feeding jejunostomy tube insertion on mortality and postesophagectomy outcomes. METHODS: Electronic databases (MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials) were queried through December 2020. Included studies compared esophagectomy with and without postoperative feeding jejunostomy. The primary outcome was 30-day mortality. Secondary outcomes included readmission rate, length of stay, postoperative complications (sepsis, pneumonia, chyle leakage, and anastomotic leakage), and duration of surgery. Random effects pairwise meta-analysis was used to compare groups, and the risk of bias was assessed using the Newcastle-Ottawa Scale and Cochrane Risk of Bias Tool. RESULTS: The meta-analyses of 12 studies (2 randomized controlled trials, 10 observational) that enrolled 36,284 participants showed lower 30-day all-cause mortality in the jejunostomy tube group (risk ratio [RR] = 1.53 [95% CI, 1.37-1.70], P < .01; I2 = 0%, P = .80). Duration of surgery favored the no jejunostomy group (mean difference = -37.18; 95% CI, -59.48 to -14.87; P < .01). However, the 2 groups were not different in incidence of anastomotic leakage (RR = 0.88; 95% CI, 0.61-1.28; P = .50), length of stay (mean difference = -0.22; 95% CI, -1.34-0.89; P = .69), readmission (RR = 0.97; 95% CI, 0.92-1.02; P = .20), chyle leakage (RR = 1.05; 95% CI, 0.34-3.27; P = .94), sepsis (RR = 1.20; 95% CI, 0.96-1.50; P = .11), pneumonia (RR = 0.88; 95% CI, 0.75-1.03; P = .11). CONCLUSIONS: Feeding jejunostomy tube after esophagectomy might lead to lower 30-day all-cause mortality with no difference in common postesophagectomy complications. A routine insertion of a jejunostomy tube should be considered at the time of surgery for esophageal cancer resection.

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.

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 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.

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.

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.

Sex Differences in Dopamine Receptor Signaling in Fmr1 Knockout Mice: A Pilot Study.

Fragile X syndrome (FXS) is an X-chromosome-linked dominant genetic disorder that causes a variable degree of cognitive dysfunction and developmental disability. Current treatment is symptomatic and no existing medications target the specific cause of FXS. As with other X-linked disorders, FXS manifests differently in males and females, including abnormalities in the dopamine system that are also seen in Fmr1-knockout (KO) mice. We investigated sex differences in dopamine signaling in Fmr1-KO mice in response to L-stepholidine, a dopamine D1 receptor agonist and D2 receptor antagonist. We found significant sex differences in basal levels of phosphorylated protein kinase A (p-PKA) and glycogen synthase kinase (GSK)-3ß in wild type mice that were absent in Fmr1-KO mice. In wild-type mice, L-stepholidine increased p-PKA in males but not female mice, decreased p-GSK-3 in female mice and increased p-GSK-3 in male mice. Conversely, in Fmr1-KO mice, L-stepholidine increased p-PKA and p-GSK-3ß in females, and decreased p-PKA and p-GSK-3ß in males.

Liver enzyme CYP2D6 gene and tardive dyskinesia.

Background: Tardive dyskinesia (TD) is an iatrogenic involuntary movement disorder occurring after extended antipsychotic use with unclear pathogenesis. CYP2D6 is a liver enzyme involved in antipsychotic metabolism and a well-studied gene candidate for TD. Materials & methods: We tested predicted CYP2D6 metabolizer phenotype with TD occurrence and severity in our two samples of European chronic schizophrenia patients (total n = 198, of which 82 had TD). Results: TD occurrence were associated with extreme metabolizer phenotype, controlling for age and sex (p = 0.012). In other words, individuals with either increased and no CYP2D6 activity were at higher risk of having TD. Conclusion: Unlike most previous findings, TD occurrence may be associated with both extremes of CYP2D6 metabolic activity rather than solely for poor metabolizers.

Association study of Disrupted-In-Schizophrenia-1 gene variants and tardive dyskinesia.

Tardive dyskinesia (TD) is an involuntary movement disorder that occurs in ∼20% of patients after extended antipsychotic use. Its pathophysiology is unclear; however, familial patterns and gene association studies indicate an inherited component to risk. The disrupted in schizophrenia 1 (DISC1) gene was selected for analysis because it interacts with and regulates two important proteins involved in antipsychotic medication action: the dopamine D2 receptor and the cAMP phosphodiesterase type IVB (PDE4B). The D2 receptor is the obligate target of all existing antipsychotic medications, and PDE4B hydrolyzes cAMP, a core signaling molecule activated by agonist binding to the D2 receptor. Notably, PDE4B inhibitors such as rolipram have been shown to reduce TD-like behaviours in animal models. Nine single-nucleotide polymorphisms (SNPs) in the DISC1 gene were investigated in a sample of 193 chronic schizophrenia patients for association with the presence and severity of TD, with age and sex as additional variables. TD severity was measured using the Abnormal Involuntary Movement Scale (AIMS). Two DISC1 SNPs were associated with TD severity (uncorrected p < 0.05), but these findings did not survive correction for multiple testing. This preliminary investigation suggests that DISC1 gene variants do not affect risk for TD or severity.

Investigation of the HSPG2 Gene in Tardive Dyskinesia - New Data and Meta-Analysis.

Tardive dyskinesia (TD) is a movement disorder that may occur after extended use of antipsychotic medications. The etiopathophysiology is unclear; however, genetic factors play an important role. The Perlecan (HSPG2) gene was found to be significantly associated with TD in Japanese schizophrenia patients, and this association was subsequently replicated by an independent research group. To add to the evidence for this gene in TD, we conducted a meta-analysis specific to the relationship of HSPG2 rs2445142 with TD occurrence, while also adding our unpublished genotype data. Overall, we found a significant association of the G allele with TD occurrence (p = 0.0001); however, much of the effect appeared to originate from the discovery dataset. Nonetheless, most study samples exhibit the same trend of association with TD for the G allele. Our findings encourage further genetic and molecular studies of HSPG2 in TD.