Mortality and prognostic factors among inpatients with systemic lupus erythematosus in China: A 20-year retrospective study.

OBJECTIVE: To summarize the causes of death and clinical characteristics of systemic lupus erythematosus (SLE) hospitalized patients in the last 20 years to improve SLE survival rates by detecting critical SLE early. METHODS: In this case-control study, 218 SLE death cases were retrospectively analyzed from January 2002 to December 2022, with 110 SLE inpatients chosen at random as controls. The clinical symptoms, causes of death, and risk factors in patients with SLE were investigated. RESULTS: There were 218 deaths among 9538 patients with SLE, including 188 women and 30 men. The death rate fell steadily from 4.14% in 2002 to 1.96% in 2013 and remained at 1.84% from 2014 to 2022. The standardized mortality ratio (SMR) was 4.98 [95% CI (4.06-5.89)] from 2002 to 2012 and 3.39 [95% CI (2.74-4.04)] from 2013 to 2022. Infection, lupus-induced multiple organ failure syndrome (MODS), and neuropsychiatric lupus (NPLE) were the leading causes of death, accounting for 31.19%, 15.14%, and 11.47% of overall deaths. Age had a significant association with the major causes of death. Logistic regression analysis showed NPLE[OR = 10.772,95% CI (3.350,34.633), p < 0.001], lupus pulmonary involvement (LP)[OR = 3.844,95%CI (1.547,9.552), p = 0.004], pneumonia[OR = 3.439,95%CI(1.552,7.621), p = 0.002], thrombocytopenia[OR = 14.941,95%CI (4.088,54.604), p < 0.001], creatinine>177 µmol/L[OR = 8.644,95%CI (2.831,26.388), p < 0.001], glutamic transaminase(AST) > 60U/L[OR = 5.762,95%CI (2.200,15.088), p < 0.001], total bilirubin > 34 µmol/L[OR = 16.701,95%CI (3.349,83.294), p = 0.001], higher SLE Disease Activity Index (SLEDAI)[OR = 1.089,95%CI (1.032,1.149), p = 0.002] and SLE Damage Index (SDI)[OR = 3.690,95%CI (2.487,5.474), p < 0.001] correlated positively with death. CONCLUSION: From 2002 to 2013, the mortality rate among patients with SLE fell steadily but remained unchanged from 2014 to 2022. Patients with SLE had significantly higher SMR than the general population. Childhood-onset SLE had a poorer prognosis than adult-onset SLE. Infection, MODS, and NPLE were the three leading causes of death. Major organ involvement and high disease activity were risk factors for mortality.

Inflammation and prediction of death in type 2 diabetes. Evidence of an intertwined link with tryptophan metabolism.

OBJECTIVE: To study whether inflammation is associated with and helps predict mortality risk in patients with type 2 diabetes. To explore the intertwined link between inflammation and tryptophan metabolism on death risk. DESIGN: Two prospective cohorts: the aggregate Gargano Mortality Study (1,731 individuals; 872 all-cause deaths) as discovery sample, the Foggia Mortality Study (490 individuals; 256 deaths) as validation sample. Twenty-seven inflammatory markers were measured. Causal mediation analysis and in vitro studies were carried out to explore the link between inflammatory markers and the kynurenine-to-tryptophan ratio (KTR) in shaping mortality risk. RESULTS: Using multivariable stepwise Cox regression analysis, IL-4, IL-6, IL-8, IL-13, RANTES and IP-10, were independently associated with death. An inflammation score (I-score) comprising these six molecules is strongly associated with death in both the discovery and the validation cohorts HR (95%CI) = 2.13 (1.91-2.37) and 2.20 (1.79-2.72), respectively. The I-score improved discrimination and reclassification measures (all P<0.01) of two mortality prediction models based on clinical variables. The causal mediation analysis showed that 28% of the KTR effect on mortality was mediated by IP-10. Studies in cultured endothelial cells showed that 5-Methoxy-tryptophan, an anti-inflammatory metabolite derived from tryptophan, reduces the expression of IP-10, thus providing a functional basis for the observed causal mediation. CONCLUSIONS: Adding the I-score to clinical prediction models may help identify individuals who are at greater risk of death. Deeply addressing the intertwined relationship between low-grade inflammation and imbalanced tryptophan metabolism in shaping mortality risk may help discover new therapies targeting patients characterized by these abnormalities.

The inverted U-shaped association between blood fibrinogen and rehospitalization risk in patients with heart failure.

Fibrinogen, a biomarker of thrombosis and inflammation, is related to a high risk for cardiovascular diseases. However, studies on the prognostic value of blood fibrinogen concentrations for heart failure (HF) patients are few and controversial. We performed a retrospective analysis among acute or deteriorating chronic HF patients admitted to a hospital in Sichuan, China, between 2016 and 2019, integrating electronic health care records and external outcome data (N = 1532). During 6 months of follow-up, 579 HF patients were readmitted within 6 months, and 46 of them died. Surprisingly, we found an inverted U-shaped association of blood fibrinogen levels with risk of readmission within 6 months but not with risk of death within 6 months. It was found that HF patients had the highest risk for readmission within 6 months after reaching the turning point for blood fibrinogen (2.4 g/L). In HF patients with low fibrinogen levels < 2.4 g/L, elevated fibrinogen concentrations were still significantly associated with a higher risk for readmission within 6 months [OR = 2.3, 95% CI (1.2, 4.6); P = 0.014] after controlling for relevant covariates. There was no significant association between blood fibrinogen and readmission within 6 months [(OR = 1.0, 95% CI (0.9, 1.1); P = 0.675] in HF patients with high fibrinogen (> 2.4 g/L). The effect difference for the two subgroups was significant (P = 0.014). However, we did not observe any association between blood fibrinogen and death within 6 months stratified by the turning point, and the effect difference for the stratification was not significant (P = 0.380). We observed an inverted U-shaped association between blood fibrinogen and rehospitalization risk in HF patients for the first time. Additionally, our results did not support that elevated blood fibrinogen was related to increased death risk after discharge.

IoT-based emergency cardiac death risk rescue alert system.

The use of technology in healthcare is one of the most critical application areas today. With the development of medical applications, people's quality of life has improved. However, it is impractical and unnecessary for medium-risk people to receive specialized daily hospital monitoring. Due to their health status, they will be exposed to a high risk of severe health damage or even life-threatening conditions without monitoring. Therefore, remote, real-time, low-cost, wearable, and effective monitoring is ideal for this problem. Many researchers mentioned that their studies could use electrocardiogram (ECG) detection to discover emergencies. However, how to respond to discovered emergencies in household life is still a research gap in this field.•This paper proposes a real-time monitoring of ECG signals and sending them to the cloud for Sudden Cardiac Death (SCD) prediction.•Unlike previous studies, the proposed system has an additional emergency response mechanism to alert nearby community healthcare workers when SCD is predicted to occur.

Understanding COVID-19 Impacts on the Health Workforce: AI-Assisted Open-Source Media Content Analysis.

BACKGROUND: To investigate the impacts of the COVID-19 pandemic on the health workforce, we aimed to develop a framework that synergizes natural language processing (NLP) techniques and human-generated analysis to reduce, organize, classify, and analyze a vast volume of publicly available news articles to complement scientific literature and support strategic policy dialogue, advocacy, and decision-making. OBJECTIVE: This study aimed to explore the possibility of systematically scanning intelligence from media that are usually not captured or best gathered through structured academic channels and inform on the impacts of the COVID-19 pandemic on the health workforce, contributing factors to the pervasiveness of the impacts, and policy responses, as depicted in publicly available news articles. Our focus was to investigate the impacts of the COVID-19 pandemic and, concurrently, assess the feasibility of gathering health workforce insights from open sources rapidly. METHODS: We conducted an NLP-assisted media content analysis of open-source news coverage on the COVID-19 pandemic published between January 2020 and June 2022. A data set of 3,299,158 English news articles on the COVID-19 pandemic was extracted from the World Health Organization Epidemic Intelligence through Open Sources (EIOS) system. The data preparation phase included developing rules-based classification, fine-tuning an NLP summarization model, and further data processing. Following relevancy evaluation, a deductive-inductive approach was used for the analysis of the summarizations. This included data extraction, inductive coding, and theme grouping. RESULTS: After processing and classifying the initial data set comprising 3,299,158 news articles and reports, a data set of 5131 articles with 3,007,693 words was devised. The NLP summarization model allowed for a reduction in the length of each article resulting in 496,209 words that facilitated agile analysis performed by humans. Media content analysis yielded results in 3 sections: areas of COVID-19 impacts and their pervasiveness, contributing factors to COVID-19-related impacts, and responses to the impacts. The results suggest that insufficient remuneration and compensation packages have been key disruptors for the health workforce during the COVID-19 pandemic, leading to industrial actions and mental health burdens. Shortages of personal protective equipment and occupational risks have increased infection and death risks, particularly at the pandemic's onset. Workload and staff shortages became a growing disruption as the pandemic progressed. CONCLUSIONS: This study demonstrates the capacity of artificial intelligence-assisted media content analysis applied to open-source news articles and reports concerning the health workforce. Adequate remuneration packages and personal protective equipment supplies should be prioritized as preventive measures to reduce the initial impact of future pandemics on the health workforce. Interventions aimed at lessening the emotional toll and workload need to be formulated as a part of reactive measures, enhancing the efficiency and maintainability of health delivery during a pandemic.

[Constructing an early-warning model for mortality risk in heat stroke patients based on Fisher discriminant analysis].

Objective: To establish an early warning model to assess the mortality risk of patients with heat stroke disease. Methods: The case data of patients diagnosed with heat stroke disease admitted to the comprehensive ICU of Shanshan County from January 2016 to December 2020 were selected. According to the short-term outcome (28 days) of patients, they were divided into death group (20 cases) and survival group (53 cases) . The relevant indicators with statistically significant differences between groups within 24 hours after admission were selected. By drawing the subject work curve (ROC) and calculating the area under the curve, the relevant indicators with the area under the curve greater than 0.7 were selected, Fisher discriminant analysis was used to establish an assessment model for the death risk of heat stroke disease. The data of heat stroke patients from January 1, 2021 to December 2022 in the comprehensive ICU of Shanshan County were collected for external verification. Results There were significant differences in age, cystatin C, procalcitonin, platelet count, CKMB, CK, CREA, PT, TT, APTT, heart rate, respiratory rate and GLS score among the groups. Cystatin C, CKMB, CREA, PT, TT, heart rate AUC area at admission was greater than 0.7. Fisher analysis method is used to build a functional model. Results: The diagnostic sensitivity, specificity and AUC area of the functional model were 95%, 83% and 0.937 respectively. The external validation results showed that the accuracy of predicting survival group was 85.71%, the accuracy of predicting death group was 88.89%. Conclusion: The early warning model of heat stroke death constructed by ROC curve analysis and Fisher discriminant analysis can provide objective reference for early intervention of heat stroke.

Up digital and personal: How heart digital twins can transform heart patient care.

Precision medicine is the vision of health care where therapy is tailored to each patient. As part of this vision, digital twinning technology promises to deliver a digital representation of organs or even patients by using tools capable of simulating personal health conditions and predicting patient or disease trajectories on the basis of relationships learned both from data and from biophysics knowledge. Such virtual replicas would update themselves with data from monitoring devices and medical tests and assessments, reflecting dynamically the changes in our health conditions and the responses to treatment. In precision cardiology, the concepts and initial applications of heart digital twins have slowly been gaining popularity and the trust of the clinical community. In this article, we review the advancement in heart digital twinning and its initial translation to the management of heart rhythm disorders.

Higher intakes of fiber, total vegetables, and fruits may attenuate the risk of all-cause and cause-specific mortality: findings from a large prospective cohort study.

BACKGROUND: Although studies have reported an inverse association between fruits, vegetables, and fiber consumption and all-cause and cause-specific mortality, the issue remains incompletely defined in the Middle Eastern population. AIMS: The current study aimed to investigate the association between dietary fiber, fruit, and vegetable intake and all-cause and cause-specific mortality. METHODS: A total of 48632 participants (mean age = 52years), 57.5% (n = 27974) women and 42.5% (n = 20658) men, were recruited from an ongoing large-scale prospective cohort study (the Golestan Cohort Study (GCS)), in the north of Iran. Using a validated semi-quantitative 116-item food questionnaire, dietary intakes were collected. Hazard ratios (HRs) and 95% confidence intervals (95%CIs) of all-cause and cause-specific mortality were reported. RESULTS: After approximately 14 years of follow-up, 10,774 deaths were recorded. In the fully adjusted model, compared to those in the lowest quintile of intake, those in the second and third quintiles of dietary fiber intake had a 7%-10% reduction in risk of all-cause mortality, and a 15%-17% reduction in the risk of mortality from other causes. Increasing consumption of fruits was also associated with a decreased risk of mortality for all-cause mortality by 9%-11%, and all cancer by 15-20%. Further, those in the third and fourth quintiles of vegetables intake had 11%-12% lower risk for CVD mortality. DISCUSSION: The results from the GCS further support the current recommendations on following a healthy diet containing proper amounts of fiber, vegetables, and fruits, as health-protective dietary items. CONCLUSIONS: Higher intake of dietary fiber, fruits, and vegetables has the potential to reduce both overall and cause-specific mortality rates. However, additional cohort studies with larger sample size and long-term follow-up durations are required to establish these findings.

Reduction of lymphocyte count at early stage elevates severity and death risk of COVID-19 patients: a hospital-based case-cohort study.

Introduction: Several reports have noted that severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced lymphopenia in coronavirus disease 2019 (COVID-19) patients. However, the clinical significance of lymphopenia remains unclear. The objective of this study was to analyze the association between lymphopenia at an early stage and the prognosis of COVID-19 patients. Material and methods: All 192 hospitalized patients with COVID-19 were enrolled. Demographic data and clinical characteristics were collected and patient's prognosis was followed up. Results: On admission, 84 (43.8%) patients suffered from lymphopenia among COVID-19 patients. The count and percentage of lymphocytes on admission were lower among patients over 70 years old than those of younger patients. Multivariate logistic regression revealed that older age was a risk factor of lymphopenia. Of interest, chest CT score, a key marker of lung injury, was increased among COVID-19 patients with lymphopenia. By contrast, PaCO2, SpO2 and oxygenation index, several respiratory function markers, were decreased in COVID-19 patients with lymphopenia. Moreover, total bilirubin (TBIL) and direct bilirubin (DBIL), two markers of hepatic injury, creatinine and urea nitrogen, two indices of renal function, and creatine kinase, AST and LDH, three myocardial enzymes, were elevated in COVID-19 patients with lymphopenia. Among 84 COVID-19 patients with lymphopenia, 32.1% died. The fatality rate was obviously higher in COVID-19 patients with lymphopenia. Conclusions: Older COVID-19 patients are more susceptible to lymphopenia. Multiple organ injuries were more serious in COVID-19 patients with lymphopenia. Lymphopenia at an early stage aggravates the severity and elevates the death risk of COVID-19 patients.

Asymptomatic Wolff-Parkinson-White Syndrome: An Ounce of Prevention Is Worth the Risk of Cure.

PURPOSE OF REVIEW: With increased electrocardiogram screening, asymptomatic preexcitation has become more prevalent. Historically, the asymptomatic-symptomatic dichotomy has directed management. This approach warrants scrutiny, as asymptomatic Wolff-Parkinson-White (WPW) syndrome is not without risk. Children may be unreliable symptom reporters, have atypical arrhythmia symptoms, yet have years to become symptomatic. RECENT FINDINGS: In a large WPW study, symptomatic patients were more likely to undergo ablation than asymptomatic patients, yet, except for symptoms, there were no differences in clinical or electrophysiology study (EPS) characteristics. Present data confirm real risk in asymptomatic WPW-sudden death can be the first symptom. Although malignant arrhythmias correlate better with EPS risk stratification than with symptoms, EPS data are imperfect predictors. Unlike adults with WPW, children have yet to prove survivorship. Asymptomatic children must be treated differently than adults. Sudden death risk is low but front-loaded in the young. An aggressive approach to asymptomatic WPW is warranted in this era of highly successful, low-risk catheter ablations.

Association of sleep duration and sleeping pill use with mortality and life expectancy: A cohort study of 484,916 adults.

OBJECTIVES: To compare mortality risk and life expectancy among individuals with different sleep durations and sleeping pill use. METHODS: A cohort of 484,916 community-dwelling adults in Taiwan was recruited into a health screening program from 1994 to 2011. Subjects were categorized by daily sleep duration into 4 groups: extremely short (<4 hours), short (4-6 hours), medium (6-8 hours), and long (>8 hours). Cox proportional hazards models were used to investigate the associations of mortality risk with sleep duration and sleeping pill use. Models were adjusted for sociodemographic characteristics, lifestyle, and comorbidities. Life expectancy tables were calculated among sleeping pill users and nonusers with different sleep durations. RESULTS: With 6- 8 hours of daily sleep, sleeping pill nonusers had the lowest mortality risk. Sleeping pill users, even with this optimal amount of sleep, had a 55% (p < .001, 95% CI, 1.38-1.73) higher mortality risk than nonusers. The life expectancy of 30-year-old male sleeping pill users with extremely short or long sleep durations was 12-13 years shorter than sleeping pill nonusers who had 6-8 hours of sleep. On average, life expectancy in individuals using sleeping pills (vs. nonusers) was shorter by 5.3 (95% CI, 4.10-6.32) years in men and 5.7 (95% CI, 5.28-7.98) years in women. CONCLUSIONS: This study suggests that the use of sleeping pills is associated with an increased risk of mortality and shortened life expectancy, especially in extreme sleepers. Regular users should be aware of potential harms from sleeping pills.

Research of mortality risk prediction based on hospital admission data for COVID-19 patients.

As COVID-19 continues to spread across the world and causes hundreds of millions of infections and millions of deaths, medical institutions around the world keep facing a crisis of medical runs and shortages of medical resources. In order to study how to effectively predict whether there are risks of death in patients, a variety of machine learning models have been used to learn and predict the clinical demographics and physiological indicators of COVID-19 patients in the United States of America. The results show that the random forest model has the best performance in predicting the risk of death in hospitalized patients with COVID-19, as the COVID-19 patients' mean arterial pressures, ages, C-reactive protein tests' values, values of blood urea nitrogen and their clinical troponin values are the most important implications for their risk of death. Healthcare organizations can use the random forest model to predict the risks of death based on data from patients admitted to a hospital due to COVID-19, or to stratify patients admitted to a hospital due to COVID-19 based on the five key factors this can optimize the diagnosis and treatment process by appropriately arranging ventilators, the intensive care unit and doctors, thus promoting the efficient use of limited medical resources during the COVID-19 pandemic. Healthcare organizations can also establish databases of patient physiological indicators and use similar strategies to deal with other pandemics that may occur in the future, as well as save more lives threatened by infectious diseases. Governments and people also need to take action to prevent possible future pandemics.

Cardiac Multimodality Imaging in Hypertrophic Cardiomyopathy: What to Look for and When to Image.

Hypertrophic cardiomyopathy (HCM), now recognized as a common cardiomyopathy of complex genomics and pathophysiology, is defined by the presence of left ventricular hypertrophy of various morphologies and severity, significant hemodynamic consequences, and diverse phenotypic, both structural and clinical, profiles. Advancements in cardiac multimodality imaging, including echocardiography, cardiac magnetic resonance imaging, and cardiac computed tomography, with and without angiography have greatly improved the diagnosis of HCM, and enable precise measurements of cardiac mass, volume, wall thickness, function, and physiology. Multimodality imaging provides comprehensive and complementary information and hasemerged as the bedrock for the diagnosis, clinical assessment, serial monitoring, and sudden cardiac death risk stratification of patients with HCM. This review highlights the role of cardiac multimodality imaging in the modern diagnosis and management of HCM.

Comparison of assessment tools in acute upper gastrointestinal bleeding: Which one at which time point?

BACKGROUND: Decisions on managing bleeders remain a critical issue due to the high death risk. The Glasgow-Blatchford score (GBS) correctly identifies low-risk patients but none of the existing scores precisely assess the high risk patients. AIMS: To evaluate bleeding scores' prognostic performances in predicting mortality risk. SECONDARY OUTCOMES: To compare the scores in low and high-risk patients and identify the "best performing cut-off" (if different from the standard one) in discriminating survivors from deceased. METHODS: prospective multicenter cohort study including consecutive UGIB patients admitted to 50 Italian hospitals. We collected information to calculate Rockall, PNED, AIMS65, GB, and ABC scores, together with demographic and clinical data, and outcomes. RESULTS: for low-risk patients, the GB and the ABC are the best performing scores; for high-risk patients, all scores showed weak results, with the PNED score having the higher PPV. Searching for the "best performing cut-off", we found different points that determined a relevant numerical gain in terms of patients correctly assessed. CONCLUSIONS: we suggest using the GBS and the ABC score at admission, while the PNED appears to be more useful for high-risk. We also suggest using a new decisional cut-offs that, if validated, may increase the accuracy of current scores.

Electrolyte imbalances as poor prognostic markers in COVID-19: a systemic review and meta-analysis.

PURPOSE: Serum electrolyte imbalances are highly prevalent in COVID-19 patients. However, their associations with COVID-19 outcomes are inconsistent, and of unknown prognostic value. We aim to systematically clarify the associations and prognostic accuracy of electrolyte imbalances (sodium, calcium, potassium, magnesium, chloride and phosphate) in predicting poor COVID-19 clinical outcome. METHODS: PubMed, Embase and Cochrane Library were searched. Odds of poor clinical outcome (a composite of mortality, intensive-care unit (ICU) admission, need for respiratory support and acute respiratory distress syndrome) were pooled using mixed-effects models. The associated prognostic sensitivity, positive and negative likelihood ratios (LR + , LR-) and predictive values (PPV, NPV; assuming 25% pre-test probability), and area under the curve (AUC) were computed. RESULTS: We included 28 observational studies from 953 records with low to moderate risk-of-bias. Hyponatremia (OR = 2.08, 95% CI = 1.48-2.94, I2 = 93%, N = 8), hypernatremia (OR = 4.32, 95% CI = 3.17-5.88, I2 = 45%, N = 7) and hypocalcemia (OR = 3.31, 95% CI = 2.24-4.88, I2 = 25%, N = 6) were associated with poor COVID-19 outcome. These associations remained significant on adjustment for covariates such as demographics and comorbidities. Hypernatremia was 97% specific in predicting poor outcome (LR + 4.0, PPV = 55%, AUC = 0.80) despite no differences in CRP and IL-6 levels between hypernatremic and normonatremic patients. Hypocalcemia was 76% sensitive in predicting poor outcome (LR- 0.44, NPV = 87%, AUC = 0.71). Overall quality of evidence ranged from very low to moderate. CONCLUSION: Hyponatremia, hypernatremia and hypocalcemia are associated with poor COVID-19 clinical outcome. Hypernatremia is 97% specific for a poor outcome, and the association is independent of inflammatory marker levels. Further studies should evaluate if correcting these imbalances help improve clinical outcome.

JAK2V617F variant allele frequency, non-driver mutations, single-nucleotide variants and polycythemia vera outcome.

INTRODUCTION: Despite comparatively favourable prognosis in polycythemia vera (PV) patients (pts), the overall survival is shorter compared to the age-matched general population. The aim of the study was to evaluate the impact of chosen laboratory and genetic factors on the individual disease outcome, i.e. risk of thrombosis, myelofibrosis/blastic transformation and death. MATERIALS AND METHODS: The study group consisted of 151 pts and 57 healthy donors (HD). RESULTS: JAK2V617F mutation was found in 96.7% (146/151) of the studied pts. JAK2 exon 12 mutations were identified in 2 individuals. The coexistence of JAK2V617F and JAK2 exon 12 mutation was confirmed in 2 other pts. In one case, neither JAK2V617F nor JAK2 exon 12 mutation was found. The presence of ten different non-driver mutations (ASXL1, SRSF2, U2AF1, IDH2) in eight of the analyzed pts (5.3%) was confirmed. The overall frequency of thrombotic events (TE) in the studied PV group was 23.8% (36/151). In patients with TE, median platelet count was lower than in pts without TE. Thrombotic risk did not depend on JAK2 rs12343867, TERT rs2736100, OBFC1 rs9420907 SNV, however, we found a novel strong tendency towards statistical significance between the CC genotype miR-146a rs2431697 and thrombosis. The disease progression to fibrotic phase was confirmed in 9% of the pts. Fibrotic transformation in PV pts was affected mainly by JAK2V617F variant allele frequency (VAF) and the presence of coexisting non-driver variants. The high JAK2V617F VAF and elevated white blood cell (WBC) count at the time of diagnosis were associated with an increased risk of death. CONCLUSION: Therefore, in our opinion, complex, laboratory and genetic PV pts evaluation at the time of diagnosis should be incorporated into a new prognostic scoring system to more precisely define the PV prognosis and to optimize the therapeutic decision-making process.

Development and validation of tools for predicting the risk of death and ICU admission of non-HIV-infected patients with Pneumocystis jirovecii pneumonia.

Introduction: The mortality rate of non-HIV-infected Pneumocystis jirovecii pneumonia (PCP) is high. This research aimed to develop and validate two clinical tools for predicting the risk of death and intensive care unit (ICU) admission in non-HIV-infected patients with PCP to reduce mortality. Methods: A retrospective study was conducted at Peking Union Medical College Hospital between 2012 and 2021. All proven and probable non-HIV-infected patients with PCP were included. The least absolute shrinkage and selection operator method and multivariable logistic regression analysis were used to select the high-risk prognostic parameters. In the validation, the receiver operating characteristic curve and concordance index were used to quantify the discrimination performance. Calibration curves were constructed to assess the predictive consistency compared with the actual observations. A likelihood ratio test was used to compare the tool and CURB-65 score. Results: In total, 508 patients were enrolled in the study. The tool for predicting death included eight factors: age, chronic lung disease, respiratory rate, blood urea nitrogen (BUN), lactate dehydrogenase (LDH), cytomegalovirus infection, shock, and invasive mechanical ventilation. The tool for predicting ICU admission composed of the following factors: respiratory rate, dyspnea, lung moist rales, LDH, BUN, C-reactive protein/albumin ratio, and pleural effusion. In external validation, the two clinical models performed well, showing good AUCs (0.915 and 0.880) and fit calibration plots. Compared with the CURB-65 score, our tool was more informative and had a higher predictive ability (AUC: 0.880 vs. 0.557) for predicting the risk of ICU admission. Conclusion: In conclusion, we developed and validated tools to predict death and ICU admission risks of non-HIV patients with PCP. Based on the information from the tools, clinicians can tailor appropriate therapy plans and use appropriate monitoring levels for high-risk patients, eventually reducing the mortality of those with PCP.

Surviving a 400 m Fall on Mount Everest.

Mountaineering is a dangerous recreational activity with falls causing severe injuries and deaths. Survival from falls longer than 100 m is uncommon. We present a case of a high-altitude porter on Mount Everest who fell 400 m and survived. He slipped from a ridge at 7000 m (22,900 ft). A rescue party found him above Camp 2 (6600 m, 21,600 ft) and arranged a helicopter rescue. The Everest ER medical team at Everest Base Camp (5400 m, 17,700 ft) received the climber. They identified a head injury without signs of other serious trauma. A doctor provided manual inline stabilization of the cervical spine, airway support, and ventilation for the patient during the helicopter and ground transport to a tertiary hospital in Kathmandu. The time from the fall to definitive hospital care was 2.5 h. The hospital emergency team diagnosed an epidural hematoma and subarachnoid hemorrhage without midline shift and right parietal, orbital, and maxillary fractures. The neurosurgical team evacuated the intracranial bleed. The patient spent 6 d in the hospital. He had a positive neurological outcome. He had mild cognitive impairment and vision loss in his left eye but could perform activities of daily living. He returned to physical work, but not to climbing. This case report provides evidence that survival is possible after falls from extreme heights and sheds light on the challenges of an evacuation from austere environments.

Association of Tumor Size With Prognosis in Patients With Resectable Endometrial Cancer: A SEER Database Analysis.

This study aimed to explore the relationship between tumor size (Ts) and prognosis in endometrial cancer (EC). A total of 52,208 patients with EC who underwent total hysterectomy were selected from the Surveillance, Epidemiology, and End Results Program database. Overall survival (OS) and endometrial cancer-specific survival (ESS) were chosen as survival outcomes. The Cox proportional hazards model was used to explore the effect of Ts on prognosis. The restricted cubic splines based on the Cox regression model were used to determine the nonlinear relationship between Ts and survival. When Ts was analyzed as a categorical variable, the risk of death increased with Ts, with the highest risk in patients with Ts > 9 cm with regard to all-cause death (ACD) (hazard ratio [HR] 1.317; 95% confidence interval [CI], 1.196-1.450; P < 0.001) and endometrial cancer-specific death (ESD) (HR, 1.378; 95% CI, 1.226-1.549; P < 0.001). As a continuous variable, Ts showed a nonlinear relationship with ACD (HR, 1.061; 95% CI, 1.053-1.069; P < 0.001) and ESD (HR, 1.062; 95% CI, 1.052-1.073; P < 0.001). The risk of mortality increased quickly with Ts when Ts was less than 7.5 cm and then leveled off when Ts was larger than 7.5 cm in all patients. Among patients with lymph node metastasis, the risk of poor prognosis decreased rapidly with Ts when Ts was less than 3.5 cm, and subsequently increased sharply with Ts when Ts ranged from 3.5 cm to 7.5 cm, and then increased slowly when Ts was larger than 7.5 cm (P < 0.001 for nonlinearity). There was a nonlinear relationship between Ts and prognosis in patients with EC. Clinicians should not ignore the impact of small tumors on prognosis in EC patients with lymph node metastasis.

Non-Linear Correlation Between Tumor Size and Survival Outcomes for Parathyroid Carcinoma: A SEER Population-Based Cohort Study.

Background: Parathyroid carcinoma (PC) is a rare malignancy without a commonly acknowledged prognostic assessment and treatment system. This study captures how independent prognostic factors and tumor size correlate with outcomes in patients with PC. Methods: The Surveillance, Epidemiology, and End Results database was used to perform a retrospective analysis on PC patients from 2000 to 2018. Univariate and multivariable survival analyses were performed to evaluate cancer-specific survival (CSS) and overall survival (OS), to identify independent prognostic factors in the PC patient population. A generalized additive model was applied to conduct smooth curve fitting and to examine the association between tumor size and relative risk of death. Results: A total of 590 patients were included. The 5- and 10-year OS were 80.8% and 67.1%, respectively. 5- and 10-year CSS was estimated to be 93.6% and 92.1%, respectively. The association between tumor size and relative risk of death can be generalized as a U-shaped curve. The mortality risk reaches its lowest point when tumor diameter approaches 2cm. At a tumor diameter cutoff of 3cm for CSS and 4cm for OS, there is an abrupt drop in survival rates. Multivariate Cox analysis revealed age, no surgery, and debulking surgery as consistent predictors of lower OS and CSS. Conclusions: A non-linear correlation between tumor size and death risk has been identified in patients with PC, along with an accurate size threshold at which survival rates sharply decrease. Further investigation is needed to determine if these trends are seen in other malignancies with promising prognoses.