Defining severe pneumonia

Effects of nursing team communication and collaboration on treatment outcomes in intensive care unit patients with severe pneumonia

BACKGROUND

Severe pneumonia is a common severe respiratory infection worldwide, and its treatment is challenging, especially for patients in the intensive care unit (ICU).

AIM

To explore the effect of communication and collaboration between nursing teams on the treatment outcomes of patients with severe pneumonia in ICU.

METHODS

We retrospectively analyzed 60 patients with severe pneumonia who were treated at the ICU of the hospital between January 1, 2021 and December 31, 2023. We compared and analyzed the respiratory mechanical indexes [airway resistance (Raw), mean airway pressure (mPaw), peak pressure (PIP)], blood gas analysis indexes (arterial oxygen saturation, arterial oxygen partial pressure, and oxygenation index), and serum inflammatory factor levels [C-reactive protein (CRP), procalcitonin (PCT), cortisol (COR), and high mobility group protein B1 (HMGB1)] of all patients before and after treatment.

RESULTS

Before treatment, there was no significant difference in respiratory mechanics index and blood gas analysis index between 2 groups (P > 0.05). However, after treatment, the respiratory mechanical indexes of patients in both groups were significantly improved, and the improvement of Raw, mPaw, plateau pressure, PIP and other indexes in the combined group after communication and collaboration with the nursing team was significantly better than that in the single care group (P < 0.05). The serum CRP and PCT levels of patients were significantly decreased, and the difference was statistically significant compared with that of nursing group alone (P < 0.05). The levels of serum COR and HMGB1 before and after treatment were also significantly decreased between the two groups.

CONCLUSION

The communication and collaboration of the nursing team have a significant positive impact on respiratory mechanics indicators, blood gas analysis indicators and serum inflammatory factor levels in the treatment of severe pneumonia patients in ICU.

Stroke among highly active antiretroviral therapy-naive people living with the human immunodeficiency virus in China: a retrospective study of the characteristics, risk factors, and prognosis

BACKGROUND

We aimed to clarify the characteristics, risk factors, and prognosis of stroke among HAART-naive people living with HIV (PLWH) in China.

METHODS

We selected HAART-naive PLWH admitted to Beijing Ditan Hospital, Capital Medical University, from 1 January 2009 to 31 December 2019. Demographic and clinical data were obtained by searching an anonymous electronic case system. Descriptive analysis and logistic regression and Cox proportional hazard models were used to determine the characteristics and predictors of stroke among all HAART-naive PLWH and evaluate the risk factors of mortality in HAART-naive PLWH with stroke.

RESULTS

Stroke was diagnosed in 105 cases (3.7%) of 2867 HAART-naive PLWH. Multivariate logistic regression indicated that age of 30-55 years (OR 1.903, 95% CI 1.005-3.603, p = 0.048), age of ≥ 55 years (OR 4.104, 95% CI 1.928-8.737, p < 0.001), and CD4 count of < 200 cells/µL (OR 2.005, 95% CI 1.008-3.985, p = 0.047) were associated with increased odds of stroke. Diabetes (OR 3.268, 95% CI 1.744-6.125, p < 0.001), hypertension (OR 2.301, 95% CI 1.425-3.717, p = 0.001), syphilis (OR 2.003, 95% CI 1.300-3.089, p = 0.002), and complicated AIDS-defining CNS diseases (OR 7.719, 95% CI 4.348-13.703, p < 0.001) were risk factors for stroke. Of the 105 stroke patients, 12 (11.4%) died during hospitalisation, and the risk factors for mortality among patients with stroke were age of > 65 years (AHR: 8.783, 95% CI 1.522-50.668, p = 0.015), complicated severe pneumonia (AHR: 3.940, 95% CI 1.106-14.029, p = 0.034), and AIDS-defining CNS diseases (AHR: 19.766, 95% CI 3.586-108.961, p = 0.001).

CONCLUSIONS

For HAART-naive people living with HIV (PLWH), stroke occurred in various age groups, and early screening for stroke, timely intervention for risk factors among patients in various age groups, and controlling the CD4 count are extremely important in reducing the burden of stroke.

The Association between Presence of Comorbidities and COVID-19 Severity: A Systematic Review and Meta-Analysis

AIM

Several studies reported the accompaniment of severe COVID-19 with comorbidities. However, there is not a systematic evaluation of all aspects of this association. Therefore, this meta-analysis aimed to assess the association between all underlying comorbidities in COVID-19 infection severity.

METHODS

Electronic literature search was performed via scientific search engines. After the removal of duplicates and selection of articles of interest, 28 studies were included. A fixed-effects model was used; however, if heterogeneity was high (I2 > 50%) a random-effects model was applied to combine the data.

RESULTS

A total of 6,270 individuals were assessed (1,615 severe and 4,655 non-severe patients). The median age was 63 (95% confidence interval [CI]: 49-74) and 47 (95% CI: 19-63) years in the severe and non-severe groups, respectively. Moreover, about 41% of patients had comorbidities. Severity was higher in patients with a history of cerebrovascular disease: OR 4.85 (95% CI: 3.11-7.57). The odds of being in a severe group increase by 4.81 (95% CI: 3.43-6.74) for a history of cardiovascular disease (CVD). This was 4.19 (95% CI: 2.84-6.19) for chronic lung disease and 3.18, 95% CI: 2.09-4.82 for cancer. The odds ratios of diabetes and hypertension were 2.61 (95% CI: 2.02-3.3) and 2.37 (95% CI: 1.80-3.13), respectively.

CONCLUSIONS

The presence of comorbidities is associated with severity of COVID-19 infection. The strongest association was observed for cerebrovascular disease, followed by CVD, chronic lung disease, cancer, diabetes, and hypertension.

Disease-specific dynamic biomarkers selected by integrating inflammatory mediators with clinical informatics in ARDS patients with severe pneumonia

Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome that occurs as a result of various risk factors, including either direct or indirect lung injury, and systemic inflammation triggered also by severe pneumonia (SP). SP-ARDS-associated morbidity and mortality remains high also due to the lack of disease-specific biomarkers. The present study aimed at identifying disease-specific biomarkers in SP or SP-ARDS by integrating proteomic profiles of inflammatory mediators with clinical informatics. Plasma was sampled from the healthy as controls or patients with SP infected with bacteria or infection-associated SP-ARDS on the day of admission, day 3, and day 7. About 15 or 52 cytokines showed significant difference between SP and SP-ARDS patients with controls or 13 between SP-ARDS with SP alone and controls, including bone morphogenetic protein-15 (BMP-15), chemokine (C-X-C motif) ligand 16 (CXCL16), chemokine (C-X-C motif) receptor 3 (CXCR3), interleukin-6 (IL-6), protein NOV homolog (NOV/CCN3), glypican 3, insulin-like growth factor binding protein 4 (IGFBP-4), IL-5, IL-5 R alpha, IL-22 BP, leptin, MIP-1d, and orexin B with a significant correlation with Digital Evaluation Score System (DESS) scores. ARDS patients with overexpressed IL-6, CXCL16, or IGFBP-4 had significantly longer hospital stay and higher incidence of secondary infection. We also found higher levels of those mediators were associated with poor survival rates in patients with lung cancer and involved in the process of the epithelial mesenchymal transition of alveolar epithelial cells. Our preliminary study suggested that integration of proteomic profiles with clinical informatics as part of clinical bioinformatics is important to validate and optimize disease-specific and disease-staged biomarkers.

In-hospital mortality risk factors in community acquired pneumonia: evaluation of immunocompetent adult patients without comorbidities

OBJECTIVE

several scores were developed in order to improve the determination of community acquired pneumonia (CAP) severity and its management, mainly CURB-65 and SACP score. However, none of them were evaluated for risk assessment of in-hospital mortality, particularly in individuals who were non-immunosuppressed and/or without any comorbidity. In this regard, the present study was carried out.

METHODS

we performed a cross-sectional study in 272 immunocompetent patients without comorbidities and with a diagnosis of CAP. Performance of CURB- 65 and SCAP scores in predicting in-hospital mortality was evaluated. Also, variables related to death were assessed. Furthermore, in order to design a model of in-hospital mortality prediction, sampled individuals were randomly divided in two groups. The association of the variables with mortality was weighed and, by multiple binary regression, a model was constructed in one of the subgroups. Then, it was validated in the other subgroup.

RESULTS

both scores yielded a fair strength of agreement, and CURB-65 showed a better performance in predicting in-hospital mortality. In our casuistry, age, white blood cell counts, serum urea and diastolic blood pressure were related to death. The model constructed with these variables showed a good performance in predicting in-hospital mortality; moreover, only one patient with fatal outcome was not correctly classified in the group where the model was constructed and in the group where it was validated.

CONCLUSION

our findings suggest that a simple model that uses only 4 variables, which are easily accessible and interpretable, can identify seriously ill patients with CAP.

Health promotion, risk stratification, and treatment options to decrease hospitalization rates for community-acquired pneumonia in adults

PURPOSE

Community-acquired pneumonia (CAP) is a serious illness and hospitalization for this illness is expensive. There is much the nurse practitioner (NP) can do to prevent and manage this illness.

DATA SOURCES

Review of current literature, medical/nursing references, and data from the healthcare utilization project (HCUP).

CONCLUSIONS

The use of health promotion, risk stratification, and current evidence-based treatment guidelines can help to decrease hospitalization rates for CAP for adults.

IMPLICATIONS FOR PRACTICE

NPs are experts at health promotion and evidence-based practice. Adhering to these practices and using risk stratification, NPs can help to further decrease hospitalization rates for CAP lowering healthcare costs related to this serious illness.

[Multidisciplinary guidelines for the management of community-acquired pneumonia]

Community-acquired pneumonia (CAP) is an infectious respiratory disease with an incidence that ranges from 3 to 8 cases per 1,000 inhabitants per year. This incidence increases with age and comorbidities. Forty per cent of CAP patients require hospitalization and around 10% of these patients are admitted in an Intensive Care Unit (ICU). Several studies have suggested that the implementation of clinical guidelines has a positive impact in the outcome of patients including mortality and length of stay. The more recent and used guidelines are those from Infectious Diseases Society of America/American Thoracic Society, published in 2007, the 2009 from the British Thoracic Society, and that from the European Respiratory Society/European Society of Clinical Microbiology and Infectious Diseases, published in 2010. In Spain, the most recently released guideline is the Sociedad Española de Neumología y Cirugía Torácica-2011 guideline. The present guidelines GNAC are designed to be used by the majority of health-care professionals that can participate in the care of CAP patients including diagnosis, decision of hospital and ICU admission, treatment and prevention. The Centro Cochrane Iberoamericano (CCIB) has participated in summarizing the previous guidelines and in the bibliography search. For each one of the following sections the panel of experts has developed a table with recommendations classified according to its evidence, strength and practical applicability using the Grading of Recommendations of Assessment Development and Evaluations (GRADE) system: 1. Epidemiology, microbiological etiology and antibiotic resistances.2. Clinical and microbiological diagnosis.3. Prognostic scales and decision of hospital admission.4. ICU admission criteria. 5. Empirical and definitive antibiotic treatment.6. Treatment failure. 7. Prevention.