Numerous studies have been published regarding outcomes of cancer patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causing the coronavirus disease 2019 ...(COVID-19) infection. However, most of these are single-center studies with a limited number of patients. To better assess the outcomes of this new infection in this subgroup of susceptible patients, we performed a systematic review and meta-analysis to evaluate the impact of COVID-19 infection on cancer patients. We performed a literature search using PubMed, Web of Science, and Scopus for studies that reported the risk of infection and complications of COVID-19 in cancer patients and retrieved 22 studies (1018 cancer patients). The analysis showed that the frequency of cancer among patients with confirmed COVID-19 was 2.1% (95% confidence interval CI: 1.3–3) in the overall cohort. These patients had a mortality of 21.1% (95% CI: 14.7–27.6), severe/critical disease rate of 45.4% (95% CI: 37.4–53.3), intensive care unit (ICU) admission rate of 14.5% (95% CI: 8.5–20.4), and mechanical ventilation rate of 11.7% (95% CI: 5.5–18). The double-arm analysis showed that cancer patients had a higher risk of mortality (odds ratio OR = 3.23, 95% CI: 1.71–6.13), severe/critical disease (OR = 3.91, 95% CI: 2.70–5.67), ICU admission (OR = 3.10, 95% CI: 1.85–5.17), and mechanical ventilation (OR = 4.86, 95% CI: 1.27–18.65) than non-cancer patients. Furthermore, cancer patients had significantly lower platelet levels and higher D-dimer levels, C-reactive protein levels, and prothrombin time. In conclusion, these results indicate that cancer patients are at a higher risk of COVID-19 infection-related complications. Therefore, cancer patients need diligent preventive care measures and aggressive surveillance for earlier detection of COVID-19 infection.
There is substantial evidence that patients with COVID-19 were treated with sustained deep sedation during the pandemic. However, it is unknown whether such guideline-discordant care had spillover ...effects to patients without COVID-19.
Did patterns of early deep sedation change during the pandemic for patients on mechanical ventilation without COVID-19?
We used electronic health record data from 4,237 patients who were intubated without COVID-19. We compared sedation practices in the first 48 h after intubation across prepandemic (February 1, 2018, to January 31, 2020), pandemic (April 1, 2020, to March 31, 2021), and late pandemic (April 1, 2021, to March 31, 2022) periods.
In the prepandemic period, patients spent an average of 13.0 h deeply sedated in the first 48 h after intubation. This increased 1.9 h (95% CI, 1.0-2.8) during the pandemic period and 2.9 h (95% CI, 2.0-3.8) in the late pandemic period. The proportion of patients that spent over one-half of the first 48 h deeply sedated was 18.9% in the prepandemic period, 22.3% during the pandemic period, and 25.9% during the late pandemic period. Ventilator-free days decreased during the pandemic, with a subdistribution hazard ratio of being alive without mechanical ventilation at 28 days of 0.87 (95% CI, 0.79-0.95) compared with the prepandemic period. Tracheostomy placement increased during the pandemic period compared with the prepandemic period (OR, 1.41; 95% CI, 1.08-1.82). In the medical ICU, early deep sedation increased 2.5 h (95% CI, 0.6-4.4) during the pandemic period and 4.9 h (95% CI, 3.0-6.9) during the late pandemic period, compared with the prepandemic period.
Among patients on mechanical ventilation without COVID-19, sedation use increased during the pandemic. In the subsequent year, these practices did not return to prepandemic standards.
There is substantial evidence that patients with COVID-19 were treated with sustained deep sedation during the pandemic. However, it is unknown whether such guideline-discordant care had spillover ...effects to patients without COVID-19.
Did patterns of early deep sedation change during the pandemic for patients on mechanical ventilation without COVID-19?
We used electronic health record data from 4,237 patients who were intubated without COVID-19. We compared sedation practices in the first 48 h after intubation across prepandemic (February 1, 2018, to January 31, 2020), pandemic (April 1, 2020, to March 31, 2021), and late pandemic (April 1, 2021, to March 31, 2022) periods.
In the prepandemic period, patients spent an average of 13.0 h deeply sedated in the first 48 h after intubation. This increased 1.9 h (95% CI, 1.0-2.8) during the pandemic period and 2.9 h (95% CI, 2.0-3.8) in the late pandemic period. The proportion of patients that spent over one-half of the first 48 h deeply sedated was 18.9% in the prepandemic period, 22.3% during the pandemic period, and 25.9% during the late pandemic period. Ventilator-free days decreased during the pandemic, with a subdistribution hazard ratio of being alive without mechanical ventilation at 28 days of 0.87 (95% CI, 0.79-0.95) compared with the prepandemic period. Tracheostomy placement increased during the pandemic period compared with the prepandemic period (OR, 1.41; 95% CI, 1.08-1.82). In the medical ICU, early deep sedation increased 2.5 h (95% CI, 0.6-4.4) during the pandemic period and 4.9 h (95% CI, 3.0-6.9) during the late pandemic period, compared with the prepandemic period.
We found that among patients on mechanical ventilation without COVID-19, sedation use increased during the pandemic. In the subsequent year, these practices did not return to prepandemic standards.
Background: Mechanical ventilation is the technique through which gas is moved toward and from the lungs through an external device connected directly to the patient. Information about the mortality ...if patients requiring mechanical ventilation is important because it allows for better counseling of patients and their families. Objectives: To study the outcome in patients receiving mechanical ventilation for specific indications. Methodology: Patients on mechanical ventilation in Government Wenlock Hospital. It is a retrospective record-based study—a semi-structured questionnaire including all complete information from pre-recorded case sheets prepared after an extensive review of the literature. Data was analyzed using SPSS version 29. Results: The mean age was 45 years. Other details of patients suffering from Chronic kidney disease, Acute Kidney Injury, Multiple organ dysfunction syndrome, Head injuries, shock, pulmonary edema, and Pneumothorax mainly. The majority of the patients who received mechanical ventilation were below 40 years of age (37.7%). A major reason for the initiation of mechanical ventilation was pneumonia (22.3%), Sepsis (25.4%), and ARDS (16.9%). AKI (N= 12), CKD (N=9), Shock (N=7), and MODS (N=6) were the major under ‘others. The type of ventilation used in the majority of the cases was invasive (87.7%) The type of ventilation used in most cases was of invasive type (87.7%). Conclusion: Even after providing mechanical ventilation, high number of patients succumbed to the complications.
Aim
To assess the relationship between body mass index (BMI) classes and early COVID‐19 prognosis in inpatients with type 2 diabetes (T2D).
Methods
From the CORONAvirus‐SARS‐CoV‐2 and Diabetes ...Outcomes (CORONADO) study, we conducted an analysis in patients with T2D categorized by four BMI subgroups according to the World Health Organization classification. Clinical characteristics and COVID‐19–related outcomes (i.e. intubation for mechanical ventilation IMV, death and discharge by day 7 D7) were analysed according to BMI status.
Results
Among 1965 patients with T2D, 434 (22.1%) normal weight (18.5‐24.9 kg/m2, reference group), 726 (36.9%) overweight (25‐29.9 kg/m2) and 805 (41.0%) obese subjects were analysed, including 491 (25.0%) with class I obesity (30‐34.9 kg/m2) and 314 (16.0%) with class II/III obesity (≥35 kg/m2). In a multivariable‐adjusted model, the primary outcome (i.e. IMV and/or death by D7) was significantly associated with overweight (OR 1.65 1.05‐2.59), class I (OR 1.93 1.19‐3.14) and class II/III obesity (OR 1.98 1.11‐3.52). After multivariable adjustment, primary outcome by D7 was significantly associated with obesity in patients aged younger than 75 years, while such an association was no longer found in those aged older than 75 years.
Conclusions
Overweight and obesity are associated with poor early prognosis in patients with T2D hospitalized for COVID‐19. Importantly, the deleterious impact of obesity on COVID‐19 prognosis was no longer observed in the elderly, highlighting the need for specific management in this population.
This review aimed to evaluate the impact of obesity on the onset, exacerbation, and mortality of coronavirus disease 2019 (COVID‐19); and compare the effects of different degrees of obesity. PubMed, ...EMBASE, and Web of Science were searched to find articles published between December 1, 2019, and July 27, 2020. Only observational studies with specific obesity definition were included. Literature screening and data extraction were conducted simultaneously by two researchers. A random‐effects model was used to merge the effect quantity. Sensitivity analysis, subgroup analysis, and meta‐regression analysis were used to deal with the heterogeneity among studies. Forty‐one studies with 219,543 subjects and 115,635 COVID‐19 patients were included. Subjects with obesity were more likely to have positive SARS‐CoV‐2 test results (OR = 1.50; 95% CI: 1.37–1.63, I2 = 69.2%); COVID‐19 patients with obesity had a higher incidence of hospitalization (OR = 1.54, 95% CI: 1.33–1.78, I2 = 60.9%); hospitalized COVID‐19 patients with obesity had a higher incidence of intensive care unit admission (OR = 1.48, 95% CI: 1.24–1.77, I2 = 67.5%), invasive mechanical ventilation (OR = 1.47, 95% CI: 1.31–1.65, I2 = 18.8%), and in‐hospital mortality (OR = 1.14, 95% CI: 1.04–1.26, I2 = 74.4%). A higher degree of obesity also indicated a higher risk of almost all of the above events. The region may be one of the causes of heterogeneity. Obesity could promote the occurrence of the whole course of COVID‐19. A higher degree of obesity may predict a higher risk. Further basic and clinical therapeutic research needs to be strengthened.
OBJECTIVETo describe the clinical and respiratory characteristics of a cohort of 43 patients with COVID-19 after an evolutive period of 28 days. DESIGNA prospective, single-center observational study ...was carried out. SETTINGIntensive care. PATIENTSPatients admitted due to COVID-19 and respiratory failure. INTERVENTIONSNone. VARIABLESAutomatic recording was made of demographic variables, severity parameters, laboratory data, assisted ventilation (HFO: high-flow oxygen therapy and IMV: invasive mechanical ventilation), oxygenation (PaO2, PaO2/FiO2) and complications. The patients were divided into three groups: survivors (G1), deceased (G2) and patients remaining under admission (G3). The chi-squared test or Fisher exact test (categorical variables) was used, along with the Mann-Whitney U-test or Wilcoxon test for analyzing the differences between medians. Statistical significance was considered for p<0.05. RESULTSA total of 43 patients were included (G1=28 65.1%; G2=10 23.3% and G3=5 11.6%), with a mean age of 65 years (range: 52-72), 62% males, APACHE II 18 (15-24), SOFA 6 (4-7). Arterial hypertension (30.2%) and obesity (25.6%) were the most frequent comorbidities. High-flow oxygen therapy was used in 62.7% of the patients, with failure in 85%. In turn, 95% of the patients required IMV and 85% received ventilation in prone decubitus. In the general population, initial PaO2/FiO2 improved after 7 days (165 125-210 vs.194 153-285; p=0.02), in the same way as in G1 (164 125-197 vs. 207 160-294; p=0.07), but not in G2 (163 95-197 vs. 135 85-177). No bacterial coinfection was observed. The incidence of IMV-associated pneumonia was high (13 episodes/1000 days of IMV). CONCLUSIONSPatients with COVID-19 require early IMV, a high frequency of ventilation in prone decubitus, and have a high incidence of failed HFO. The lack of improvement of PaO2/FiO2 at 7 days could be a prognostic marker. .
Background
Carbon dioxide concentration trending is used in chronic management of children with invasive home mechanical ventilation (HMV) in clinical settings, but options for end‐tidal carbon ...dioxide (EtCO2) monitoring at home are limited. We hypothesized that a palm‐sized, portable endotracheal capnograph (PEC) that measures EtCO2 could be adapted for in‐home use in children with HMV.
Methods
We evaluated the internal consistency of the PEC by calculating an intraclass correlation coefficient of three back‐to‐back breaths by children (0–17 years) at baseline health in the clinic. Pearson's correlation was calculated for PEC EtCO2 values with concurrent mean values of in‐clinic EtCO2 and transcutaneous CO2 (TCM) capnometers. The Bland–Altman test determined their level of agreement. Qualitative interviews and surveys assessed usability and acceptability by family‐caregivers at home.
Results
CO2 values were collected in awake children in varied activity levels and positions (N = 30). The intraclass correlation coefficient for the PEC was 0.95 (p < 0.05). The correlation between the PEC and in‐clinic EtCO2 device was 0.85 with a mean difference of −3.8 mmHg and precision of ±1.1 mmHg. The correlation between the PEC and the clinic TCM device was 0.92 with a mean difference of 0.2 mmHg and precision of ±1.0. Family‐caregivers (N = 10) trialed the PEC at home; all were able to obtain measurements at home while children were awake and sometimes asleep.
Conclusions
A portable, noninvasive device for measuring EtCO2 was feasible and acceptable, with values that trend similarly to currently in‐practice, outpatient models. These devices may facilitate monitoring of EtCO2 at home in children with invasive HMV.
Current evidence on obstetric patients requiring advanced ventilatory support and impact of delivery on ventilatory parameters is retrospective, scarce, and controversial.
What are the ventilatory ...parameters for obstetric patients with COVID-19 and how does delivery impact them? What are the risk factors for invasive mechanical ventilation (IMV) and for maternal, fetal, and neonatal mortality?
Prospective, multicenter, cohort study including pregnant and postpartum patients with COVID-19 requiring advanced ventilatory support in the ICU.
Ninety-one patients were admitted to 21 ICUs at 29.2 ± 4.9 weeks; 63 patients (69%) delivered in ICU. Maximal ventilatory support was as follows: IMV, 69 patients (76%); high-flow nasal cannula, 20 patients (22%); and noninvasive mechanical ventilation, 2 patients (2%). Sequential Organ Failure Assessment during the first 24 h (SOFA24) score was the only risk factor for IMV (OR, 1.97; 95% CI, 1.29-2.99; P = .001). Respiratory parameters at IMV onset for pregnant patients were: mean ± SD plateau pressure (PP), 24.3 ± 4.5 cm H2O; mean ± SD driving pressure (DP), 12.5 ± 3.3 cm H2O; median static compliance (SC), 31 mL/cm H2O (interquartile range IQR, 26-40 mL/cm H2O); and median Pao2 to Fio2 ratio, 142 (IQR, 110-176). Respiratory parameters before (< 2 h) and after (≤ 2 h and 24 h) delivery were, respectively: mean ± SD PP, 25.6 ± 6.6 cm H2O, 24 ± 6.7 cm H2O, and 24.6 ± 5.2 cm H2O (P = .59); mean ± SD DP, 13.6 ± 4.2 cm H2O, 12.9 ± 3.9 cm H2O, and 13 ± 4.4 cm H2O (P = .69); median SC, 28 mL/cm H2O (IQR, 22.5-39 mL/cm H2O), 30 mL/cm H2O (IQR, 24.5-44 mL/cm H2O), and 30 mL/cm H2O (IQR, 24.5-44 mL/cm H2O; P = .058); and Pao2 to Fio2 ratio, 134 (IQR, 100-230), 168 (IQR, 136-185), and 192 (IQR, 132-232.5; P = .022). Reasons for induced delivery were as follows: maternal, 43 of 71 patients (60.5%); maternal and fetal, 21 of 71 patients (29.5%); and fetal, 7 of 71 patients (9.9%). Fourteen patients (22.2%) continued pregnancy after ICU discharge. Risk factors for maternal mortality were BMI (OR, 1.10; 95% CI, 1.006-1.204; P = .037) and comorbidities (OR, 4.15; 95% CI, 1.212-14.20; P = .023). Risk factors for fetal or neonatal mortality were gestational age at delivery (OR, 0.67; 95% CI, 0.52-0.86; P = .002) and SOFA24 score (OR, 1.53; 95% CI, 1.13-2.08; P = .006).
Contrary to expectations, pregnant patient lung mechanics were similar to those of the general population with COVID-19 in the ICU. Delivery was induced mainly for maternal reasons, but did not change ventilatory parameters other than Pao2 to Fio2 ratio. SOFA24 score was the only risk factor for IMV. Maternal mortality was associated independently with BMI and comorbidities. Risk factors for fetal and neonatal mortality were SOFA24 score and gestational age at delivery.
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