Predictors of Mortality Among Post-COVID-19 Discharged Patients in Northern India: A Case-Control Study.

Introduction The post-discharge all-cause mortality of COVID-19 disease is known, but predictors for the same have not been studied as much. The objective of this study was to develop an understanding of predictors of mortality to guide in prioritizing patient care and preventive approaches. Methods This current research is a single-center unmatched case-control study conducted at a tertiary care center in northern India, between April and September 2022. The data were extracted retrospectively from the hospital's electronic medical records of patients with the assistance of trained physicians using a standardized data extraction sheet. Results A total of 184 patients were enrolled and were segregated into two groups, cases and control, with 92 in each. The mean age of patients was 49.3 ± 17.53 years. The mortality group had a higher mean age (53.24 ± 18.53 yrs) as compared to the control group (45.37 ± 15.58 yrs, p=0.002). Bivariate analysis revealed a significant difference in the two groups with respect to O2 saturation at the time of admission (case - 91.12 ± 12.49 %, control - 95.46 ± 5.01 %, p=0.003); maximum O2 flow rate (L/min) (case - 11.01 ± 22.2, control - 6.41 ± 13.31, p=0.04); ICU need (p=0.005), cancer (p=0.001), O2 requirement at discharge (p=0.001) and acute kidney injury (AKI; p=0.007). On multiple regression analysis, cancer (adjusted odds ratio (aOR) - 2.469; 95% CI 1.183-5.150, p=0.016), ICU admission (aOR - 2.446; 95% CI 1.212-4.938, p=0.013), oxygen at discharge (aOR - 2.340; 95% CI 0.971-5.640, p=0.0586) and AKI (aOR - 5.6; 95% CI 2.351- 13.370, p=0.00) only found to be significant. Conclusion Among the patients released from the hospital post-COVID-19 treatment, the following aspects oxygen requirement (2.3 times), malignancy (2.4 times), ICU admission (2.4 times), and AKI (5.6 times) are risk factors of mortality. The presence of these variables would warrant a close follow-up for these patients in order to decrease post-COVID mortality.

Predictors of Mortality Among Post-COVID-19 Discharged Patients in Northern India: A Case-Control Study

Introduction The post-discharge all-cause mortality of COVID-19 disease is known, but predictors for the same have not been studied as much. The objective of this study was to develop an understanding of predictors of mortality to guide in prioritizing patient care and preventive approaches. Methods This current research is a single-center unmatched case-control study conducted at a tertiary care center in northern India, between April and September 2022. The data were extracted retrospectively from the hospital's electronic medical records of patients with the assistance of trained physicians using a standardized data extraction sheet. Results A total of 184 patients were enrolled and were segregated into two groups, cases and control, with 92 in each. The mean age of patients was 49.3 ± 17.53 years. The mortality group had a higher mean age (53.24 ± 18.53 yrs) as compared to the control group (45.37 ± 15.58 yrs, p=0.002). Bivariate analysis revealed a significant difference in the two groups with respect to O2 saturation at the time of admission (case - 91.12 ± 12.49 %, control - 95.46 ± 5.01 %, p=0.003);maximum O2 flow rate (L/min) (case - 11.01 ± 22.2, control - 6.41 ± 13.31, p=0.04);ICU need (p=0.005), cancer (p=0.001), O2 requirement at discharge (p=0.001) and acute kidney injury (AKI;p=0.007). On multiple regression analysis, cancer (adjusted odds ratio (aOR) - 2.469;95% CI 1.183-5.150, p=0.016), ICU admission (aOR - 2.446;95% CI 1.212-4.938, p=0.013), oxygen at discharge (aOR - 2.340;95% CI 0.971-5.640, p=0.0586) and AKI (aOR - 5.6;95% CI 2.351- 13.370, p=0.00) only found to be significant. Conclusion Among the patients released from the hospital post-COVID-19 treatment, the following aspects oxygen requirement (2.3 times), malignancy (2.4 times), ICU admission (2.4 times), and AKI (5.6 times) are risk factors of mortality. The presence of these variables would warrant a close follow-up for these patients in order to decrease post-COVID mortality.

Disrupting autorepression circuitry generates "open-loop lethality" to yield escape-resistant antiviral agents.

Across biological scales, gene-regulatory networks employ autorepression (negative feedback) to maintain homeostasis and minimize failure from aberrant expression. Here, we present a proof of concept that disrupting transcriptional negative feedback dysregulates viral gene expression to therapeutically inhibit replication and confers a high evolutionary barrier to resistance. We find that nucleic-acid decoys mimicking cis-regulatory sites act as "feedback disruptors," break homeostasis, and increase viral transcription factors to cytotoxic levels (termed "open-loop lethality"). Feedback disruptors against herpesviruses reduced viral replication >2-logs without activating innate immunity, showed sub-nM IC50, synergized with standard-of-care antivirals, and inhibited virus replication in mice. In contrast to approved antivirals where resistance rapidly emerged, no feedback-disruptor escape mutants evolved in long-term cultures. For SARS-CoV-2, disruption of a putative feedback circuit also generated open-loop lethality, reducing viral titers by >1-log. These results demonstrate that generating open-loop lethality, via negative-feedback disruption, may yield a class of antimicrobials with a high genetic barrier to resistance.

Clinical profile, risk factors, and therapeutic outcome of cavitating fungal pneumonia coinfection in COVID-19 patients: A retrospective analysis.

Background An end to the novel coronavirus disease 2019 (COVID-19) pandemic appears to be a distant dream. To make matters worse, there has been an alarming upsurge in the incidence of cavitating invasive fungal pneumonia associated with COVID-19, reported from various parts of the world including India. Therefore, it remains important to identify the clinical profile, risk factors, and outcome of this group of patients.

Methods Out of 50 moderate to severe COVID-19 inpatients with thoracic computed tomographic (CT) evidence of lung cavitation, we retrospectively collected demographic and clinical data of those diagnosed as fungal pneumonia for further investigation. We observed these patients for a total of 60 days from identification of fungal pneumonia and determined the association between risk factors related to 30-day and 60-day mortality.

Results Of the 50 COVID-19 patients with cavitating lung lesions, 22 (44 %) were identified to have fungal pneumonia. Most of these patients (n=16, 72.7 %) were male, with a median (range) age of 56 (38-64) years. On chest CT imaging, the most frequent findings were multiple cavities (n=13, 59.1 %) and consolidation (n=14, 63.6 %). Mucormycosis (n=10, 45.5 %) followed by Aspergillus fumigatus (n=9, 40.9 %) were the common fungi identified. 30-day and 60-day mortality was seen in 12 (54.5 %) and 16 (72.7 %) patients, respectively. On subgroup analysis, high cumulative prednisolone dose was an independent risk factor associated with 30-day mortality (p=0.024).

Conclusion High cumulative prednisolone dose, baseline neutropenia, hypoalbuminemia, multiple cavities on CT chest, leukopenia, lymphopenia and raised inflammatory markers were associated with poor prognosis in severe COVID-19 patients with cavitating fungal pneumonia.

The clinical course, biochemical markers, and clinical outcomes of COVID-19 positive patients from the third wave in Pakistan: A retrospective cohort study.

Background: Third wave of COVID-19 has affected several countries. Case fatality rates from first and second waves are expected to be surpassed by the current wave due to various variant transmissions. This study was aimed to compare and contrast the significant clinical markers between survivors and non-survivors during the third wave of COVID-19 to assess severity and prognosis. Methods: It includes all the patients who were diagnosed with COVID-19 polymerase chain reaction (PCR) during the third wave, and were monitored for their disease course and outcomes. A total of 209 patients were included in the analysis via non-probability consecutive sampling method. Results: The median age was higher in non-surviving patients (p = 0.010). Majority of deaths occurred in intensive care patients (p < 0.001) and those with diabetes (p = 0.032) and hypertension (p = 0.003). Fever was the most predominant symptom in all patients (78.9%), dyspnea was common among expired individuals (p = 0.043) while recovered patients were more likely to be asymptomatic (p = 0.044). Gastrointestinal symptoms were not found marked during this wave. Being on ventilator has higher mortality (p < 0.001). Predominant radiological findings were interstitial patches or infiltrate (43.7%). Multivariable analysis showed hypertension (p = 0.042), BiPAP/CPAP (p < 0.001), being on ventilator (p = 0.004), and ARDS (p < 0.001) was associated with poor survival while patchy interstitial infiltrates on X-ray had good survival probability (p = 0.032). On Kaplan-Meier survival analysis, hypertension (p = 0.003), BiPAP/CPAP (p = 0.008), ventilator (p = 0.025), ICU stay (p = 0.001), high-grade fever (p = 0.001), and ARDS (p < 0.001) had reduced cumulative survival. Conclusion: Certain biochemical markers were more predictive of disease severity in the third-wave than the preceding waves.

Identification of a therapeutic interfering particle-A single-dose SARS-CoV-2 antiviral intervention with a high barrier to resistance.

Viral-deletion mutants that conditionally replicate and inhibit the wild-type virus (i.e., defective interfering particles, DIPs) have long been proposed as single-administration interventions with high genetic barriers to resistance. However, theories predict that robust, therapeutic DIPs (i.e., therapeutic interfering particles, TIPs) must conditionally spread between cells with R0 >1. Here, we report engineering of TIPs that conditionally replicate with SARS-CoV-2, exhibit R0 >1, and inhibit viral replication 10- to 100-fold. Inhibition occurs via competition for viral replication machinery, and a single administration of TIP RNA inhibits SARS-CoV-2 sustainably in continuous cultures. Strikingly, TIPs maintain efficacy against neutralization-resistant variants (e.g., B.1.351). In hamsters, both prophylactic and therapeutic intranasal administration of lipid-nanoparticle TIPs durably suppressed SARS-CoV-2 by 100-fold in the lungs, reduced pro-inflammatory cytokine expression, and prevented severe pulmonary edema. These data provide proof of concept for a class of single-administration antivirals that may circumvent current requirements to continually update medical countermeasures against new variants.

Post-COVID-19 Panic Disorder in Older Adults: Two Case Reports

Introduction Patients who recover from infection with SARS-CoV-2 (COVID-19) are at risk for a range of neuropsychiatric conditions, among which anxiety spectrum disorders have been frequently observed. Methods In this report we present two cases of older adults with no past psychiatric history who developed panic disorder after recovering from COVID-19. Results Patient A is a 51-year-old Haitian American woman who was admitted to inpatient psychiatry with symptoms of anxiety, insomnia, disorganized behavior, and suicidal ideation, as well as intermittent hypertensive episodes. After discharge, the hypertensive episodes persisted and were associated with feelings of impending doom, palpitations, and shortness of breath. While undergoing blood pressure management from her cardiologist, she was admitted to outpatient psychiatry, diagnosed with panic disorder, and tried on multiple medications (Mirtazapine, Trazodone, Hydroxyzine, Escitalopram, Sertraline). None of these medications relieved her symptoms, which gradually evolved from panic/anxiety/depression to derealization/depersonalization. Eventually, all her symptoms abated without medication. Patient B is a 61-year-old African American woman who was admitted to outpatient psychiatry with episodes of chest tightness, palpitations, and trembling, as well as insomnia and depressed mood;she too was diagnosed with panic disorder. She had previously been treated by her primary care doctor and in the emergency room with various benzodiazepines (Diazepam, Alprazolam, Lorazepam), but she was eventually stabilized on a regimen of Sertraline, Trazodone, and Gabapentin. Conclusions Here we examine the rationale and effectiveness of various medication trials for COVID-19-induced panic disorder, as well as how psychosocial risk factors may predict the course of illness. We also discuss some hypothesized mechanisms by which SARS-CoV-2 could produce neuropsychiatric sequelae (e.g. direct viral injury, cytokine storm, molecular mimicry). These mechanisms could affect both peripheral and central nervous systems, resulting in the combination of autonomic instability and mood disturbance classically associated with panic disorder. Funding New York State Department of Health, Center of Excellence Grant