BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

Objective Studies on the relationship between iodine,vitamin A(VA),and vitamin D(VD)and thyroid function are limited.This study aimed to analyze iodine and thyroid-stimulating hormone(TSH)status and their possible relationships with VA,VD,and other factors in postpartum women. Methods A total of 1,311 mothers(896 lactating and 415 non-lactating)from Hebei,Zhejiang,and Guangxi provinces were included in this study.The urinary iodine concentration(UIC),TSH,VA,and VD were measured. Results The median UIC of total and lactating participants were 142.00 μg/L and 139.95 μg/L,respectively.The median TSH,VA,and VD levels in all the participants were 1.89 mIU/L,0.44 μg/mL,and 24.04 ng/mL,respectively.No differences in the UIC were found between lactating and non-lactating mothers.UIC and TSH levels were significantly different among the three provinces.The rural UIC was higher than the urban UIC.Obese mothers had a higher UIC and a higher prevalence of excessive TSH.Higher UICs and TSHs levels were observed in both the VD deficiency and insufficiency groups than in the VD-sufficient group.After adjustment,no linear correlation was observed between UIC and VA/VD.No interaction was found between vitamins A/D and UIC on TSH levels. Conclusion The mothers in the present study had no iodine deficiency.Region,area type,BMI,and VD may be related to the iodine status or TSH levels.

Objective As primary Sj?gren's syndrome(pSS)primarily affects the salivary glands,saliva can serve as an indicator of the glands'pathophysiology and the disease's status.This study aims to illustrate the salivary proteomic profiles of pSS patients and identify potential candidate biomarkers for diagnosis. Methods The discovery set contained 49 samples(24 from pSS and 25 from age-and gender-matched healthy controls[HCs])and the validation set included 25 samples(12 from pSS and 13 from HCs).Totally 36 pSS patients and 38 HCs were centrally randomized into the discovery set or to the validation set at a 2:1 ratio.Unstimulated whole saliva samples from pSS patients and HCs were analyzed using a data-independent acquisition(DIA)strategy on a 2D LC-HRMS/MS platform to reveal differential proteins.The crucial proteins were verified using DIA analysis and annotated using gene ontology(GO)and International Pharmaceutical Abstracts(IPA)analysis.A prediction model for SS was established using random forests. Results A total of 1,963 proteins were discovered,and 136 proteins exhibited differential representation in pSS patients.The bioinformatic research indicated that these proteins were primarily linked to immunological functions,metabolism,and inflammation.A panel of 19 protein biomarkers was identified by ranking order based on P-value and random forest algorichm,and was validated as the predictive biomarkers exhibiting good performance with area under the curve(AUC)of 0.817 for discovery set and 0.882 for validation set. Conclusions The candidate protein panel discovered may aid in pSS diagnosis.Salivary proteomic analysis is a promising non-invasive method for prognostic evaluation and early and precise treatments for pSS patients.DIA offers the best time efficiency and data dependability and may be a suitable option for future research on the salivary proteome.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.

The paper is to establish an UPLC-MS/MS method for the simultaneous determination of 19 components in Microctis Folium from different production areas. The 50% methanol was used as extraction solvent. The Agilent ZORBAX SB C18 (150 mm × 2.1 mm, 1.8 μm) column was used; mobile phase was acetonitrile - 0.1% acetic acid with gradient elution, flow rate was 0.3 mL·min^-1, colume temperature was 30 ℃, and the injection volume was 2 μL; electrospray ionizaton source was used and detected in negative ion mode. The results showed that the established UPLC-MS/MS method could well separate the 19 components, and the methodological investigation results of 19 components were good. By means of orthogonal partial least squares discriminant analysis (OPLS-DA), 28 batches of Microctis Folium samples from different production areas can be divided into three categories, Guangdong, Guangxi and Hainan are each classified into one category, and 10 signature compounds which affecting the quality differences of different production areas were screened out. The established method is accurate, reliable, sensitive and reproducible. It can provide a basis for the establishment of the quality standard of Microctis Folium, as well as for safety and quality research.

Objective:To investigate the clinical features of patients with maintenance hemodialysis (MHD) infected with SARS-CoV-2 and analyze the risk factors of death after SARS-CoV-2 infection, and to provide clinical data for early detection of critically ill patients and timely intervention.Methods:It was a cross-sectional investigation study. MHD patients in the hemodialysis centers of four tertiary hospitals with geographical representation in Shanxi province from December 1, 2022 to January 31, 2023 were enrolled, and the demographic data, dialysis-related indicators, laboratory test results and clinical features of SARS-CoV-2 infection were collected by distributing the questionnaires on SARS-CoV-2 infection, and consulting the hospital medical record system and the outpatient hemodialysis information system. SARS-CoV-2-infected patients were divided into survival group and death group according to whether all-cause death occurred and the differences of baseline data between the two groups were compared. Multivariate logistic regression analysis method was used to analyze the risk factors of mortality in MHD patients infected with SARS-CoV-2.Results:A total of 519 MHD patients were included in this study, with 508 patients (97.88%) infected with SARS-CoV-2, 474 patients in the survival group and 34 patients in the death group. The clinical symptoms of MHD patients infected with SARS-CoV-2 were diverse, and the most common initial symptom was fever (314/508, 61.81%). Other initial symptoms included cough and phlegm in 66 patients (12.99%), fatigue in 66 patients (12.99%), poor appetite in 20 patients (3.94%), dyspnea in 20 patients (3.94%), muscle pain in 14 patients (2.76%) and diarrhea in 8 patients (1.57%). Compared with the survival group, the death group had older age ( t=5.229, P<0.001), high proportions of males ( χ2=12.319, P<0.001) and diabetic nephropathy ( χ2=49.423, P<0.001), and lower levels of red blood cells ( t=-5.060, P<0.001), lymphocyte ( t=-2.614, P=0.011), neutrophil ( t=-5.117, P<0.001), serum albumin ( t=-2.940, P=0.012), serum prealbumin ( t=-3.519, P=0.001), blood phosphorus ( t=-3.309, P=0.002), serum creatinine ( Z=-3.607, P<0.001), total triglyceride ( Z=-2.486, P=0.013), total cholesterol ( Z=-3.291, P=0.001) and low-density lipoprotein cholesterol ( Z=-3.292, P=0.001). Among 508 SARS-CoV-2-infected patients, 194 patients (38.19%) were treated with nonsteroidal anti-inflammatory agents, 154 patients (30.31%) were treated with antibiotics, and 98 patients (19.29%) were treated with antiviral drugs. There were 225 (43.29%) vaccinated patients against SARS-CoV-2. Multivariate logistic regression analysis showed that low red blood cells ( OR=0.256, 95% CI 0.014-0.429), low lymphocytes ( OR=0.487, 95% CI 0.193-0.826), low serum albumin ( OR=0.613, 95% CI 0.329-0.917), older age ( OR=1.227, 95% CI 1.066-1.412) and diabetes mellitus ( OR=1.126, 95% CI 1.025-1.235) were the independent influencing factors of all-cause mortality in MHD patients infected with SARS-CoV-2. Conclusions:The clinical manifestations of SARS-CoV-2 infection in MHD patients are varied. Low red blood cells, low lymphocytes, low serum albumin, elder age and diabetes mellitus are the independent risk factors of death after SARS-CoV-2 infection in MHD patients. Strengthening management of MHD patients especially in the elderly, and improving and correcting anemia and malnutrition in time, may reduce the death risk of SARS-CoV-2 infection in MHD patients.

Purpose::To identify the risk factors for training-related lower extremity muscle injuries in young males by a non-invasive method of body composition analysis.Methods::A total of 282 healthy young male volunteers aged 18 -20 years participated in this cohort study. Injury location, degree, and injury rate were adjusted by a questionnaire based on the overuse injury assessment methods used in epidemiological studies of sports injuries. The occurrence of training injuries is monitored and diagnosed by physicians and treated accordingly. The body composition was measured using the BodyStat QuadScan 4000 multifrequency Bio-impedance system at 5, 50, 100 and 200 kHz to obtain 4 impedance values. The Shapiro-Wilk test was used to check whether the data conformed to a normal distribution. Data of normal distribution were shown as mean ± SD and analyzed by t-test, while those of non-normal distribution were shown as median (Q 1, Q 3) and analyzed by Wilcoxon rank sum test. The receiver operator characteristic curve and logistic regression analysis were performed to investigate risk factors for developing training-related lower extremity injuries and accuracy. Results::Among the 282 subjects, 78 (27.7%) developed training injuries. Lower extremity training injuries revealed the highest incidence, accounting for 23.4% (66 cases). These patients showed higher percentages of lean body mass ( p = 0.001), total body water (TBW, p=0.006), extracellular water ( p=0.020) and intracellular water ( p=0.010) as well as a larger ratio of basal metabolic rate/total weight ( p=0.006), compared with those without lower extremity muscle injuries. On the contrary, the percentage of body fat ( p=0.001) and body fat mass index ( p=0.002) were lower. Logistic regression analysis showed that TBW percentage > 65.35% ( p=0.050, odds ratio =3.114) and 3rd space water > 0.95% ( p=0.045, odds ratio =2.342) were independent risk factors for lower extremity muscle injuries. Conclusion::TBW percentage and 3rd space water measured with bio-impedance method are potential risk factors for predicting the incidence of lower extremity muscle injuries in young males following training.

Objective:To explore potential predictors of refractory Mycoplasma pneumoniae pneumonia (RMPP) in early stage. Methods:The prospective multicenter study was conducted in Zhejiang, China from May 1 st, 2019 to January 31 st, 2020. A total of 1 428 patients with fever >48 hours to <120 hours were studied. Their clinical data and oral pharyngeal swab samples were collected; Mycoplasma pneumoniae DNA in pharyngeal swab specimens was detected. Patients with positive Mycoplasma pneumoniae DNA results underwent a series of tests, including chest X-ray, complete blood count, C-reactive protein, lactate dehydrogenase (LDH), and procalcitonin. According to the occurrence of RMPP, the patients were divided into two groups, RMPP group and general Mycoplasma pneumoniae pneumonia (GMPP) group. Measurement data between the 2 groups were compared using Mann-Whitney U test. Logistic regression analyses were used to examine the associations between clinical data and RMPP. Receiver operating characteristic (ROC) curves were used to analyse the power of the markers for predicting RMPP. Results:A total of 1 428 patients finished the study, with 801 boys and 627 girls, aged 4.3 (2.7, 6.3) years. Mycoplasma pneumoniae DNA was positive in 534 cases (37.4%), of whom 446 cases (83.5%) were diagnosed with Mycoplasma pneumoniae pneumonia, including 251 boys and 195 girls, aged 5.2 (3.3, 6.9) years. Macrolides-resistant variation was positive in 410 cases (91.9%). Fifty-five cases were with RMPP, 391 cases with GMPP. The peak body temperature before the first visit and LDH levels in RMPP patients were higher than that in GMPP patients (39.6 (39.1, 40.0) vs. 39.2 (38.9, 39.7) ℃, 333 (279, 392) vs. 311 (259, 359) U/L, both P<0.05). Logistic regression showed the prediction probability π=exp (-29.7+0.667×Peak body temperature (℃)+0.004×LDH (U/L))/(1+exp (-29.7+0.667×Peak body temperature (℃)+0.004 × LDH (U/L))), the cut-off value to predict RMPP was 0.12, with a consensus of probability forecast of 0.89, sensitivity of 0.89, and specificity of 0.67; and the area under ROC curve was 0.682 (95% CI 0.593-0.771, P<0.01). Conclusion:In MPP patients with fever over 48 to <120 hours, a prediction probability π of RMPP can be calculated based on the peak body temperature and LDH level before the first visit, which can facilitate early identification of RMPP.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.