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Large language models(LLM) are leading to a new revolution in artificial intelligence technology. As LLM have the characteristics of platform, mass data dependence, frequent user interaction, and easy to be attacked, the risk of privacy disclosure is more worrying. The source and internal mechanism of privacy leakage caused by LLM were focused. After reviewing the domestic and foreign experience in the governance of LLM privacy risks, a five-dimensional governance framework that included policies, standards, data, technology, and ecology were proposed. Finally, this paper also looks forward to the new privacy disclosure risks that LLM may face under the development trend of multimodal, agent, embodied intelligence, edge intelligence, etc.

AIM: To compare the changes in axial length of myopic patients of different ages after wearing orthokeratology lenses with increased compression factor(ICF)or conventional compression factor(CCF)for 2 a.METHODS: Retrospective study. A total of 141 myopia patients(141 right eyes)aged 8 to 15 years who fitted with orthokeratology lenses in the General Hospital of Foshan Aier Eye Hospital from July 2020 to July 2021 were continuously included. They were divided into the CCF group(70 cases, 70 eyes)and the ICF group(71 cases, 71 eyes). The patients in the CCF group were fitted with orthokeratology lens of 0.75 DS CCF, while patients in the ICF group were fitted with orthokeratology lens of 1.25 D ICF. Taking 12 years old as a boundary, these two groups were divided into 8-11 years old and 12-15 years old group. The uncorrected visual acuity(UCVA), horizontal corneal curvature(K1)and corneal staining were recorded for all subjects after wearing lenses for 1 d, 1 wk, 1, 6 mo, 1 and 2 a. The axial length(AL)was recorded after wearing lenses for 6 mo, 1 and 2 a, and the complication and corneal epithelial staining were observed during lens wearing.RESULTS:The improvement of UCVA in the ICF group was faster than that in the CCF group, which were statistical significant after wearing lenses for 1 d, 1 wk and 1 mo, respectively(all P0.05); K1 of the ICF group decreased faster than that of the CCF group, and there were statistical significance at 1 d, 1 wk, and 1 mo after wearing lenses(all P0.05). The axial length growth of patients aged 8-11 years old in the ICF group and CCF group was 0.35±0.17 and 0.48±0.26 mm, respectively(P=0.010), after wearing lenses for 2 a, and the axial length growth of patients aged 12-15 years old in the ICF group and CCF group was 0.16±0.15 and 0.31±0.29 mm, respectively(P=0.011). During the follow-up period, corneal spotting occurred in 6 eyes(8.5%)in the ICF group, and 7 eyes(10%)in the CCF group(P>0.05), all of which were grade 1 spotting.CONCLUSION:Wearing ICF orthokeratology lens is more effective than wearing CCF lenses in controlling the growth of axial length, with faster shaping and more obvious improvement in UCVA, especially for the prevention of high myopia in children under 12 years. Therefore, young children can give priority to wearing lenses that increase the compression factor, and for children over 12 years old, the compression factor of the lens can be selectively increased according to the wearer's eye habits, health status of ocular surface and visual function.

With the advent of the era of big data and cloud computing, big data is more and more widely used in various industries, and the research and practice of using big data technology to realize blaze new trails and start an undertaking cultivate mode in computer special field of study will become an important focus of the blaze new trails and start an undertaking cultivate system nowadays. In this paper, we construct the blaze new trails and start an undertaking cultivate model based on BP ANN, construct the blaze new trails and start an undertaking cultivate evaluation index system through Delphi method, and finally design the model of blaze new trails and start an undertaking cultivate evaluation in order to analyze the results of blaze new trails and start an undertaking cultivate. The scoring results correspond to the data of 21 evaluation indexes of a student, and the various scores can map to the level of individual students’ blaze new trails and start an undertaking ability, and provide effective countermeasures for computer special field of study students’ blaze new trails and start an undertaking cultivate. This paper effectively evaluates the blaze new trails and start an undertaking ability of students, broadens the application value and research field of BP ANN, and actively explores the blaze new trails and start an undertaking cultivate of computer special field of study students, which helps the operation mode of blaze new trails and start an undertaking cultivate of computer special field of study special field of study, provides step foreward ideas, and is of great significance to promote the step forward of blaze new trails and start an undertaking cultivate mode.

BackgroundTo develop a sensitive risk score predicting the risk of mortality in patients with coronavirus disease 2019 (COVID-19) using complete blood count (CBC).MethodsWe performed a retrospective cohort study from a total of 13,138 inpatients with COVID-19 in Hubei, China, and Milan, Italy. Among them, 9,810 patients with ≥2 CBC records from Hubei were assigned to the training cohort. CBC parameters were analyzed as potential predictors for all-cause mortality and were selected by the generalized linear mixed model (GLMM).FindingsFive risk factors were derived to construct a composite score (PAWNN score) using the Cox regression model, including platelet counts, age, white blood cell counts, neutrophil counts, and neutrophil:lymphocyte ratio. The PAWNN score showed good accuracy for predicting mortality in 10-fold cross-validation (AUROCs 0.92-0.93) and subsets with different quartile intervals of follow-up and preexisting diseases. The performance of the score was further validated in 2,949 patients with only 1 CBC record from the Hubei cohort (AUROC 0.97) and 227 patients from the Italian cohort (AUROC 0.80). The latent Markov model (LMM) demonstrated that the PAWNN score has good prediction power for transition probabilities between different latent conditions.ConclusionsThe PAWNN score is a simple and accurate risk assessment tool that can predict the mortality for COVID-19 patients during their entire hospitalization. This tool can assist clinicians in prioritizing medical treatment of COVID-19 patients.FundingThis work was supported by National Key R&D Program of China (2016YFF0101504, 2016YFF0101505, 2020YFC2004702, 2020YFC0845500), the Key R&D Program of Guangdong Province (2020B1111330003), and the medical flight plan of Wuhan University (TFJH2018006).

Corticosteroid therapy is now recommended as a treatment in patients with severe COVID-19. But one key question is how to objectively identify severely ill patients who may benefit from such therapy. Here, we assigned 12,862 COVID-19 cases from 21 hospitals in Hubei Province equally to a training and a validation cohort. We found that a neutrophil-to-lymphocyte ratio (NLR) > 6.11 at admission discriminated a higher risk for mortality. Importantly, however, corticosteroid treatment in such individuals was associated with a lower risk of 60-day all-cause mortality. Conversely, in individuals with an NLR ≤ 6.11 or with type 2 diabetes, corticosteroid treatment was not associated with reduced mortality, but rather increased risks of hyperglycemia and infections. These results show that in the studied cohort corticosteroid treatment is associated with beneficial outcomes in a subset of COVID-19 patients who are non-diabetic and with severe symptoms as defined by NLR.

BackgroundThe coronavirus disease 2019 (COVID-19) is a recently emerged respiratory infectious disease with kidney injury as a part of the clinical complications. However, the dynamic change of kidney function and its association with COVID-19 prognosis are largely unknown.MethodsIn this multicenter retrospective cohort study, we analyzed clinical characteristics, medical history, laboratory tests, and treatment data of 12,413 COVID-19 patients. The patient cohort was stratified according to the severity of the outcome into three groups: non-severe, severe, and death.FindingsThe prevalence of elevated blood urea nitrogen (BUN), elevated serum creatinine (Scr), and decreased blood uric acid (BUA) at admission was 6.29%, 5.22%, and 11.66%, respectively. The trajectories showed the elevation in BUN and Scr levels, as well as a reduction in BUA level for 28 days after admission in death cases. Increased all-cause mortality risk was associated with elevated baseline levels of BUN and Scr and decreased levels of BUA.ConclusionsThe dynamic changes of the three kidney function markers were associated with different severity and poor prognosis of COVID-19 patients. BUN showed a close association with and high potential for predicting adverse outcomes in COVID-19 patients for severity stratification and triage.FundingThis study was supported by grants from the National Key R&D Program of China (2016YFF0101504), the National Science Foundation of China (81630011, 81970364, 81970070, 81970011, 81870171, and 81700356), the Major Research Plan of the National Natural Science Foundation of China (91639304), the Hubei Science and Technology Support Project (2019BFC582, 2018BEC473, and 2017BEC001), and the Medical Flight Plan of Wuhan University.

The prognostic power of circulating cardiac biomarkers, their utility, and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multicentered retrospective study, we enrolled 3219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effects Cox model, after adjusting for age, sex, and comorbidities, the adjusted hazard ratio of 28-day mortality for hs-cTnI (high-sensitivity cardiac troponin I) was 7.12 ([95% CI, 4.60-11.03] P

The safety and efficacy of anti-diabetic drugs are critical for maximizing the beneficial impacts of well-controlled blood glucose on the prognosis of individuals with COVID-19 and pre-existing type 2 diabetes (T2D). Metformin is the most commonly prescribed first-line medication for T2D, but its impact on the outcomes of individuals with COVID-19 and T2D remains to be clarified. Our current retrospective study in a cohort of 1,213 hospitalized individuals with COVID-19 and pre-existing T2D indicated that metformin use was significantly associated with a higher incidence of acidosis, particularly in cases with severe COVID-19, but not with 28-day COVID-19-related mortality. Furthermore, metformin use was significantly associated with reduced heart failure and inflammation. Our findings provide clinical evidence in support of continuing metformin treatment in individuals with COVID-19 and pre-existing T2D, but acidosis and kidney function should be carefully monitored in individuals with severe COVID-19.

Statins are lipid-lowering therapeutics with favorable anti-inflammatory profiles and have been proposed as an adjunct therapy for COVID-19. However, statins may increase the risk of SARS-CoV-2 viral entry by inducing ACE2 expression. Here, we performed a retrospective study on 13,981 patients with COVID-19 in Hubei Province, China, among which 1,219 received statins. Based on a mixed-effect Cox model after propensity score-matching, we found that the risk for 28-day all-cause mortality was 5.2% and 9.4% in the matched statin and non-statin groups, respectively, with an adjusted hazard ratio of 0.58. The statin use-associated lower risk of mortality was also observed in the Cox time-varying model and marginal structural model analysis. These results give support for the completion of ongoing prospective studies and randomized controlled trials involving statin treatment for COVID-19, which are needed to further validate the utility of this class of drugs to combat the mortality of this pandemic.

RationaleUse of ACEIs (angiotensin-converting enzyme inhibitors) and ARBs (angiotensin II receptor blockers) is a major concern for clinicians treating coronavirus disease 2019 (COVID-19) in patients with hypertension.ObjectiveTo determine the association between in-hospital use of ACEI/ARB and all-cause mortality in patients with hypertension and hospitalized due to COVID-19.Methods and resultsThis retrospective, multi-center study included 1128 adult patients with hypertension diagnosed with COVID-19, including 188 taking ACEI/ARB (ACEI/ARB group; median age 64 [interquartile range, 55-68] years; 53.2% men) and 940 without using ACEI/ARB (non-ACEI/ARB group; median age 64 [interquartile range 57-69]; 53.5% men), who were admitted to 9 hospitals in Hubei Province, China from December 31, 2019 to February 20, 2020. In mixed-effect Cox model treating site as a random effect, after adjusting for age, gender, comorbidities, and in-hospital medications, the detected risk for all-cause mortality was lower in the ACEI/ARB group versus the non-ACEI/ARB group (adjusted hazard ratio, 0.42 [95% CI, 0.19-0.92]; P=0.03). In a propensity score-matched analysis followed by adjusting imbalanced variables in mixed-effect Cox model, the results consistently demonstrated lower risk of COVID-19 mortality in patients who received ACEI/ARB versus those who did not receive ACEI/ARB (adjusted hazard ratio, 0.37 [95% CI, 0.15-0.89]; P=0.03). Further subgroup propensity score-matched analysis indicated that, compared with use of other antihypertensive drugs, ACEI/ARB was also associated with decreased mortality (adjusted hazard ratio, 0.30 [95% CI, 0.12-0.70]; P=0.01) in patients with COVID-19 and coexisting hypertension.ConclusionsAmong hospitalized patients with COVID-19 and coexisting hypertension, inpatient use of ACEI/ARB was associated with lower risk of all-cause mortality compared with ACEI/ARB nonusers. While study interpretation needs to consider the potential for residual confounders, it is unlikely that in-hospital use of ACEI/ARB was associated with an increased mortality risk.