Our aim was to clarify the incidence and risk of acute symptomatic seizures in people with coronavirus disease 2019 (COVID‐19). This multicenter retrospective study enrolled people with COVID‐19 from January 18 to February 18, 2020 at 42 government‐designated hospitals in Hubei province, the epicenter of the epidemic in China; Sichuan province; and Chongqing municipality. Data were collected from medical records by 11 neurologists using a standard case report form. A total of 304 people were enrolled, of whom 108 had a severe condition. None in this cohort had a known history of epilepsy. Neither acute symptomatic seizures nor status epilepticus was observed. Two people had seizurelike symptoms during hospitalization due to acute stress reaction and hypocalcemia, and 84 (27%) had brain insults or metabolic imbalances during the disease course known to increase the risk of seizures. There was no evidence suggesting an additional risk of acute symptomatic seizures in people with COVID‐19. Neither the virus nor potential risk factors for seizures seem to be significant risks for the occurrence of acute symptomatic seizures in COVID‐19.

Objective To investigate new-onset neurologic impairments associated with coronavirus disease 2019 (COVID-19). Methods A retrospective multicenter cohort study was conducted between January 18 and March 20, 2020, including people with confirmed COVID-19 from 56 hospitals officially designated in 3 Chinese regions; data were extracted from medical records. New-onset neurologic events as assessed by neurology consultants based on manifestations, clinical examination, and investigations were noted, in which critical events included disorders of consciousness, stroke, CNS infection, seizures, and status epilepticus. Results We enrolled 917 people with average age 48.7 years and 55% were male. The frequency of new-onset critical neurologic events was 3.5% (32/917) overall and 9.4% (30/319) among those with severe or critical COVID-19. These were impaired consciousness (n = 25) or stroke (n = 10). The risk of critical neurologic events was highly associated with age above 60 years and previous history of neurologic conditions. Noncritical events were seen in fewer than 1% (7/917), including muscle cramp, unexplained headache, occipital neuralgia, tic, and tremor. Brain CT in 28 people led to new findings in 9. Findings from lumbar puncture in 3 with suspected CNS infection, unexplained headache, or severe occipital neuralgia were unremarkable. Conclusions People with COVID-19 aged over 60 and with neurologic comorbidities were at higher risk of developing critical neurologic impairment, mainly impaired consciousness and cerebrovascular accidents. Brain CT should be considered when new-onset brain injury is suspected, especially in people under sedation or showing an unexplained decline in consciousness. Evidence of direct acute insult of severe acute respiratory syndrome coronavirus 2 to the CNS is lacking.

Background: To investigate clinicopathological variables influencing overall survival, overall recurrence, and post-recurrence survival (PRS) in patients who experienced curative-intent surgical resection of stage I non-small-cell lung cancer (NSCLC). Methods: We investigated a series of 1387 patients with stage I NSCLC who underwent surgical resection from 2008 to 2015. The effect clinicopathological factors on death, recurrence, and PRS were evaluated by Kaplan-Meier estimates and cox regression analysis. Results: Among the 1387 stage I patients, 301 (21.7%) experienced recurrence. The 5-year cumulative incidence of recurrence (CIR) for all patients was 20.2% and median PRS was 25.5 months. The older age (P = 0.036), p-stage IB (P = 0.001), sublobar resection(P<0.001), histology subtype (P<0.001), and lymphovascular invasion (LVI) (P = 0.042) were significantly associated with worse overall survival. Among 301 recurrent patients, univariable analysis indicated that p-stage IB (versus IA) (P<0.001), LVI (P<0.001) and visceral pleural invasion (VPI) (P<0.001) were remarkably correlated with the higher incidence of recurrence. Taking the effect of clinicopathological variables on PRS into consideration, smoking history (P = 0.043), non-adenocarcinoma (P = 0.013), high architectural grade of LUAD (P = 0.019), EGFR wild status (P = 0.002), bone metastasis (P =0.040) and brain metastasis (P = 0.042) were substantially related with poorer PRS. Multivariate analysis demonstrated that high architectural grade of LUAD (P = 0.008), brain metastasis (P = 0.010) and bone metastasis (P = 0.043) were independently associated with PRS. Conclusion: In patients with resected stage I NSCLC, the older age, p-stage IB (versus IA), sublobar resection, histology subtype, and LVI were significantly associated with worse overall survival. P-stage IB (versus IA), LVI, and VPI were significantly correlated with the higher incidence of recurrence. High architectural grade of LUAD, brain metastasis and bone metastasis were independent risk factors with PRS.

Background: Lung cancer is the leading cause of cancer‐related deaths worldwide and the prognosis remains poor. The recent introduction of the immune checkpoint inhibitor (ICI), or plus chemotherapy, both resulted in the survival benefit for patients with advanced non‐small‐cell lung cancer (NSCLC), but it remains unanswered which is superior. The current study aimed to estimate the comparative efficacy and safety of ICI‐chemotherapy versus ICI‐monotherapy in advanced NSCLC.Methods: Studies were identified by searching PubMed, Embase, and Cochrane library. The randomized controlled trials (RCTs) that ICI monotherapy or ICI plus chemotherapy compared with chemotherapy in NSCLC were included with available primary endpoints of progression‐free survival (PFS), overall survival (OS), objective response rate, or treatment‐related adverse events. A fixed‐effect or random‐effects model was adopted depending on between‐study heterogeneity.Results: A total of 20 RCTs involving 12,025 patients with NSCLC were included. Both ICI‐monotherapy and ICI‐chemotherapy resulted in significantly prolonged survival compared to chemotherapy and the former led to significantly longer PFS. The magnitude of survival benefits appeared to be greatest among those treated with pembrolizumab plus platinum‐based chemotherapy (OS, 0.56; PFS, 0.54). Additionally, OS and PFS advantages of ICI therapies were observed in patients with NSCLC with low or high programmed cell death 1 ligand 1 (PD‐L1) expression level, but not in intermediate PD‐L1 TPS.Conclusions: Pembrolizumab plus platinum‐based chemotherapy was recommended as the optimal first‐line therapy for advanced patients with NSCLC. Additionally, PD‐L1 alone is not recommended as an adequate molecular biomarker to identify eligible patients for routine clinical practice in immunotherapy.

The subtype classification of lung adenocarcinoma is important for treatment decision. This study aimed to investigate the deep learning and radiomics networks for predicting histologic subtype classification and survival of lung adenocarcinoma diagnosed through computed tomography (CT) images. A dataset of 1222 patients with lung adenocarcinoma were retrospectively enrolled from three medical institutions. The anonymised preoperative CT images and pathological labels of atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, invasive adenocarcinoma (IAC) with five predominant components were obtained. These pathological labels were divided into 2-category classification (IAC; non-IAC), 3-category and 8-category. We modeled the classification task of histological subtypes based on modified ResNet-34 deep learning network, radiomics strategies and deep radiomics combined algorithm. Then we established the prognostic models in lung adenocarcinoma patients with survival outcomes. The accuracy (ACC), area under ROC curves (AUCs) and C-index were primarily performed to evaluate the algorithms. This study included a training set (n = 802) and two validation cohorts (internal, n = 196; external, n = 224). The ACC of deep radiomics algorithm in internal validation achieved 0.8776, 0.8061 in the 2-category, 3-category classification, respectively. Even in 8 classifications, the AUC ranged from 0.739 to 0.940 in internal set. Further, we constructed a prognosis model that C-index was 0.892(95% CI: 0.846-0.937) in internal validation set. The automated deep radiomics based triage system has achieved the great performance in the subtype classification and survival predictability in patients with CT-detected lung adenocarcinoma nodules, providing the clinical guide for treatment strategies.