Lower blood pH as a strong prognostic factor for fatal outcomes in critically ill COVID-19 patients at an intensive care unit: A multivariable analysis

Integrated Electrochemical Aptamer Biosensing and Colorimetric pH Monitoring via Hydrogel Microneedle Assays for Assessing Antibiotic Treatment

Current methods for therapeutic drug monitoring (TDM) have a long turnaround time as they involve collecting patients' blood samples followed by transferring the samples to medical laboratories where sample processing and analysis are performed. To enable real-time and minimally invasive TDM, a microneedle (MN) biosensor to monitor the levels of two important antibiotics, vancomycin (VAN) and gentamicin (GEN) is developed. The MN biosensor is composed of a hydrogel MN (HMN), and an aptamer-functionalized flexible (Flex) electrode, named HMN-Flex. The HMN extracts dermal interstitial fluid (ISF) and transfers it to the Flex electrode where sensing of the target antibiotics happens. The HMN-Flex performance is validated ex vivo using skin models as well as in vivo in live rat animal models. Data is leveraged from the HMN-Flex system to construct pharmacokinetic profiles for VAN and GEN and compare these profiles with conventional blood-based measurements. Additionally, to track pH and monitor patient's response during antibiotic treatment, an HMN is developed that employs a colorimetric method to detect changes in the pH, named HMN-pH assay, whose performance has been validated both in vitro and in vivo. Further, multiplexed antibiotic and pH detection is achieved by simultaneously employing the HMN-pH and HMN-Flex on live animals.

Insights into the baseline blood pH homeostasis at admission and the risk of in-hospital mortality in COVID-19 patients

Aim: A laboratory finding in critically ill COVID-19 patients is blood academia (pH <7.35). We investigated its cause in connection with the admission baseline blood pH homeostasis.Patients & methods: We retrospectively monitored the baseline blood pH homeostasis of 1215 COVID-19 patients who were admitted with pneumonia using data-driven knowledge. Two categories of patients were identified: non-survivors (107) and survivors (1108).Results: Non-survivors showed greater levels of lactate and lower blood pH, saturation, and partial pressure of oxygen than survivors. A bivariate Spearman's correlation matrix showed that the [HCO3-]/pCO2 and pCO2 of non-survivors exhibited an unmatched connection, but not in the survivor group. When comparing non-survivors to survivors, the dendrograms derived from the bivariate comparison matrix showed differences in gasometry parameters like blood pH, [HCO3-]/pCO2 ratio, anion gap and pO2.Conclusion: The little variations in the gasometry readings between survivors and non-survivors upon admission suggested abnormal changes in the complementary renal and respiratory systems that bring blood pH back to normal. In advanced COVID-19, modest blood acid-base imbalances could become blood acidemia if these compensatory strategies were overused. Data-driven monitoring of acid-base parameters may help predict abnormal blood pH and the advancement of metabolic acidemia before it is too late.

Severe COVID-19 infection: An institutional review and literature overview

BACKGROUND

Our study aimed to describe the group of severe COVID-19 patients at an institutional level, and determine factors associated with different outcomes.

METHODS

A retrospective chart review of patients admitted with severe acute hypoxic respiratory failure due to COVID-19 infection. Based on outcomes, we categorized 3 groups of severe COVID-19: (1) Favorable outcome: progressive care unit admission and discharge (2) Intermediate outcome: ICU care (3) Poor outcome: in-hospital mortality.

RESULTS

Eighty-nine patients met our inclusion criteria; 42.7% were female. The average age was 59.7 (standard deviation (SD):13.7). Most of the population were Caucasian (95.5%) and non-Hispanic (91.0%). Age, sex, race, and ethnicity were similar between outcome groups. Medicare and Medicaid patients accounted for 62.9%. The average BMI was 33.5 (SD:8.2). Moderate comorbidity was observed, with an average Charlson Comorbidity index (CCI) of 3.8 (SD:2.6). There were no differences in the average CCI between groups(p = 0.291). Many patients (67.4%) had hypertension, diabetes (42.7%) and chronic lung disease (32.6%). A statistical difference was found when chronic lung disease was evaluated; p = 0.002. The prevalence of chronic lung disease was 19.6%, 27.8%, and 40% in the favorable, intermediate, and poor outcome groups, respectively. Smoking history was associated with poor outcomes (p = 0.04). Only 7.9% were fully vaccinated. Almost half (46.1%) were intubated and mechanically ventilated. Patients spent an average of 12.1 days ventilated (SD:8.5), with an average of 6.0 days from admission to ventilation (SD:5.1). The intermediate group had a shorter average interval from admission to ventilator (77.2 hours, SD:67.6), than the poor group (212.8 hours, SD:126.8); (p = 0.001). The presence of bacterial pneumonia was greatest in the intermediate group (72.2%), compared to the favorable group (17.4%), and the poor group (56%); this was significant (p<0.0001). In-hospital mortality was seen in 28.1%.

CONCLUSION

Most patients were male, obese, had moderate-level comorbidity, a history of tobacco abuse, and government-funded insurance. Nearly 50% required mechanical ventilation, and about 28% died during hospitalization. Bacterial pneumonia was most prevalent in intubated groups. Patients who were intubated with a good outcome were intubated earlier during their hospital course, with an average difference of 135.6 hours. A history of cigarette smoking and chronic lung disease were associated with poor outcomes.

Failure of First Transition to Pressure Support Ventilation After Spontaneous Awakening Trials in Hypoxemic Respiratory Failure: Influence of COVID-19

OBJECTIVES

To describe the rate of failure of the first transition to pressure support ventilation (PSV) after systematic spontaneous awakening trials (SATs) in patients with acute hypoxemic respiratory failure (AHRF) and to assess whether the failure is higher in COVID-19 compared with AHRF of other etiologies. To determine predictors and potential association of failure with outcomes.

DESIGN

Retrospective cohort study.

SETTING

Twenty-eight-bedded medical-surgical ICU in a private hospital (Argentina).

PATIENTS

Subjects with arterial pressure of oxygen (AHRF to Fio2 [Pao2/Fio2] < 300 mm Hg) of different etiologies under controlled mechanical ventilation (MV).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We collected data during controlled ventilation within 24 hours before SAT followed by the first PSV transition. Failure was defined as the need to return to fully controlled MV within 3 calendar days of PSV start. A total of 274 patients with AHRF (189 COVID-19 and 85 non-COVID-19) were included. The failure occurred in 120 of 274 subjects (43.7%) and was higher in COVID-19 versus non-COVID-19 (49.7% and 30.5%; p = 0.003). COVID-19 diagnosis (odds ratio [OR]: 2.22; 95% CI [1.15-4.43]; p = 0.020), previous neuromuscular blockers (OR: 2.16; 95% CI [1.15-4.11]; p = 0.017) and higher fentanyl dose (OR: 1.29; 95% CI [1.05-1.60]; p = 0.018) increased the failure chances. Higher BMI (OR: 0.95; 95% CI [0.91-0.99]; p = 0.029), Pao2/Fio2 (OR: 0.87; 95% CI [0.78-0.97]; p = 0.017), and pH (OR: 0.61; 95% CI [0.38-0.96]; p = 0.035) were protective. Failure groups had higher 60-day ventilator dependence (p < 0.001), MV duration (p < 0.0001), and ICU stay (p = 0.001). Patients who failed had higher mortality in COVID-19 group (p < 0.001) but not in the non-COVID-19 (p = 0.083).

CONCLUSIONS

In patients with AHRF of different etiologies, the failure of the first PSV attempt was 43.7%, and at a higher rate in COVID-19. Independent risk factors included COVID-19 diagnosis, fentanyl dose, previous neuromuscular blockers, acidosis and hypoxemia preceding SAT, whereas higher BMI was protective. Failure was associated with worse outcomes.

Prognostic factors for favorable outcomes after veno-venous extracorporeal membrane oxygenation in critical care patients with COVID-19

BACKGROUND

Patients with COVID-19 and severe acute respiratory failure may require veno-venous extracorporeal membrane oxygenation (VV ECMO). Yet, this procedure is resource-intensive and high mortality rates have been reported. Thus, predictors for identifying patients who will benefit from VV ECMO would be helpful.

METHODS

This retrospective study included 129 patients with COVID-19 and severe acute respiratory failure, who had received VV ECMO at the University Medical Center Regensburg, Germany, between 1 March 2020 and 31 December 2021. Patient-specific factors and relevant intensive-care parameters at the time of the decision to start VV ECMO were investigated regarding their value as predictors of patient survival. In addition, the intensive-care course of the first 10 days of VV ECMO was compared between survivors and patients who had died in the intensive care unit.

RESULTS

The most important parameters for predicting outcome were patient age and platelet count, which differed significantly between survivors and non-survivors (age: 52.6±8.1 vs. 57.4±10.1 years, p<0.001; platelet count before VV ECMO: 321.3±132.2 vs. 262.0±121.0 /nL, p = 0.006; average on day 10: 199.2±88.0 vs. 147.1±57.9 /nL, p = 0.002). A linear regression model derived from parameters collected before the start of VV ECMO only included age and platelet count. Patients were divided into two groups by using receiver operating characteristics (ROC) analysis: group 1: 78% of patients, mortality 26%; group 2: 22% of patients, mortality 75%. A second linear regression model included average blood pH, minimum paO2, and average pump flow on day 10 of VV ECMO in addition to age and platelet count. The ROC curve resulted in two cut-off values and thus in three groups: group 1: 25% of patients, mortality 93%; group 2: 45% of patients, mortality 31%; group 3: 30% of patients, mortality 0%.

Arterial lactate as a risk factor for death in respiratory failure related to coronavirus disease 2019: an observational study

BACKGROUND

Arterial lactate is a recognized biomarker associated with death in critically ill patients. The prognostic role of arterial lactate in acute respiratory failure due to the novel coronavirus disease 2019 (COVID-19) is unclear.

OBJECTIVES

We aimed to investigate the prognostic role of arterial lactate levels at admission in patients with COVID-19-related acute respiratory failure.

DESIGN AND METHODS

Cohorts of consecutive patients admitted to nonintensive care units (ICU) at study centers for COVID-19-related respiratory failure were merged into a collaborative database. The prognostic role of lactate levels at admission was assessed for continuous values and values ⩾2.0 mmol/l, and lactate clearance at 24 h through delta-lactate (ΔLac). The study outcome was 30-day in-hospital death. Cox proportional regression model was used to assess independent predictors of the study outcome.

RESULTS

At admission, 14.6% of patients had lactate levels ⩾2 mmol/l. In-hospital death at 30 days occurred in 57 out of 206 patients; 22.3% and 56.7% with normal or ⩾ 2 mmol/l lactate at admission, respectively. The median lactate level was 1.0 [interquartile range (IQR) 0.8-1.3] mmol/l and 1.3 (IQR 1.0-2.1) mmol/l in survivors and nonsurvivors, respectively (p-value < 0.001). After adjusting for age, relevant comorbidities, acidemia, and the severity of respiratory failure, lactate ⩾2.0 mmol/l was associated with in-hospital death (HR 2.53, 95% CI 1.29-4.95, p-value 0.0066), while Δ Lac ⩾0 was not (HR 1.37, 95% CI 0.42-4.49). These results were confirmed in patients with a pO2/FiO2-ratio (P/F ratio) ⩽300 mmHg.

CONCLUSIONS

In our study, increased arterial lactate at admission was independently associated with in-hospital death at 30 days in non-ICU patients with acute respiratory failure related to COVID-19.

Biomarkers Predicting Poor Prognosis in Covid-19 Patients: A Survival Analysis

Introduction With the spread of the Covid-19 pandemic and its overwhelming impact on health systems in several countries, the importance of identifying predictors of severity is of paramount importance. The objective of this study is to determine the relationship between death and the biological parameters of patients with Covid-19. Materials and methods This is an analytical retrospective cohort study conducted on 326 patients admitted to the Mohammed VI University Hospital in Oujda, Morocco. The statistical analysis concerned the biological parameters carried out on the admission of the patients, in addition to age and sex. The comparison between the two surviving and non-surviving groups was made by a simple analysis than a multivariate analysis by logistic regression. Next, a survival analysis was performed by the Kaplan-Meier method and then by Cox regression. Results A total of 326 patients were included in the study, including 108 fatal cases. The mean age was 64.66 ± 15.51 and the sex ratio was 1.08:1 (M:F). Age, procalcitonin, liver enzymes, and coagulation factors were significantly higher in patients who died of Covid-19 and are therefore considered to be the main prognostic factors identified in this study. Conclusion Knowledge and monitoring of predictive biomarkers of poor prognosis in patients with Covid-19 could be of great help in the identification of patients at risk and in the implementation of an effective diagnostic and therapeutic strategy to predict severe disease forms.

Evaluation of models for prognosing mortality in critical care patients with COVID-19: First- and second-wave data from a German university hospital

Background

In a previous study, we had investigated the intensive care course of patients with coronavirus disease 2019 (COVID-19) in the first wave in Germany by calculating models for prognosticating in-hospital death with univariable and multivariable regression analysis. This study analyzed if these models were also applicable to patients with COVID-19 in the second wave.

Methods

This retrospective cohort study included 98 critical care patients with COVID-19, who had been treated at the University Medical Center Regensburg, Germany, between October 2020 and February 2021. Data collected for each patient included vital signs, dosage of catecholamines, analgosedation, anticoagulation, and antithrombotic medication, diagnostic blood tests, treatment with extracorporeal membrane oxygenation (ECMO), intensive care scores, ventilator therapy, and pulmonary gas exchange. Using these data, expected mortality was calculated by means of the originally developed mathematical models, thereby testing the models for their applicability to patients in the second wave.

Results

Mortality in the second-wave cohort did not significantly differ from that in the first-wave cohort (41.8% vs. 32.2%, p = 0.151). As in our previous study, individual parameters such as pH of blood or mean arterial pressure (MAP) differed significantly between survivors and non-survivors. In contrast to our previous study, however, survivors and non-survivors in this study showed significant or even highly significant differences in pulmonary gas exchange and ventilator therapy (e.g. mean and minimum values for oxygen saturation and partial pressure of oxygen, mean values for the fraction of inspired oxygen, positive expiratory pressure, tidal volume, and oxygenation ratio). ECMO therapy was more frequently administered than in the first-wave cohort. Calculations of expected mortality by means of the originally developed univariable and multivariable models showed that the use of simple cut-off values for pH, MAP, troponin, or combinations of these parameters resulted in correctly estimated outcome in approximately 75% of patients without ECMO therapy.