ABSTRACT
Background: Recently, internet hospitals have been emerging in China, saving patients time and money during the COVID-19 pandemic. In addition, pharmacy services that link doctors and patients are becoming essential in improving patient satisfaction. However, the existing internet hospital pharmacy service mode relies primarily on manual operations, making it cumbersome, inefficient, and high-risk. Objective: To establish an internet hospital pharmacy service mode based on artificial intelligence (AI) and provide new insights into pharmacy services in internet hospitals during the COVID-19 pandemic. Methods: An AI-based internet hospital pharmacy service mode was established. Initially, prescription rules were formulated and embedded into the internet hospital system to review the prescriptions using AI. Then, the "medicine pick-up code," which is a Quick Response (QR) code that represents a specific offline self-pick-up order, was created. Patients or volunteers could pick up medications at an offline hospital or drugstore by scanning the QR code through the window and wait for the dispensing machine or pharmacist to dispense the drugs. Moreover, the medication consultation function was also operational. Results: The established internet pharmacy service mode had four major functional segments: online drug catalog search, prescription preview by AI, drug dispensing and distribution, and AI-based medication consultation response. The qualified rate of AI preview was 83.65%. Among the 16.35% inappropriate prescriptions, 49% were accepted and modified by physicians proactively and 51.00% were passed after pharmacists intervened. The "offline self-pick-up" mode was preferred by 86% of the patients for collecting their medication in the internet hospital, which made the QR code to be fully applied. A total of 426 medication consultants were served, and 48.83% of them consulted outside working hours. The most frequently asked questions during consultations were about the internet hospital dispensing process, followed by disease diagnosis, and patient education. Therefore, an AI-based medication consultation was proposed to respond immediately when pharmacists were unavailable. Conclusion: The established AI-based internet hospital pharmacy service mode could provide references for pharmacy departments during the COVID-19 pandemic. The significance of this study lies in ensuring safe/rational use of medicines and raising pharmacists' working efficiency.
ABSTRACT
Background: Recently, internet hospitals have been emerging in China, saving patients time and money during the COVID-19 pandemic. In addition, pharmacy services that link doctors and patients are becoming essential in improving patient satisfaction. However, the existing internet hospital pharmacy service mode relies primarily on manual operations, making it cumbersome, inefficient, and high-risk. Objective: To establish an internet hospital pharmacy service mode based on artificial intelligence (AI) and provide new insights into pharmacy services in internet hospitals during the COVID-19 pandemic. Methods: An AI-based internet hospital pharmacy service mode was established. Initially, prescription rules were formulated and embedded into the internet hospital system to review the prescriptions using AI. Then, the “medicine pick-up code,” which is a Quick Response (QR) code that represents a specific offline self-pick-up order, was created. Patients or volunteers could pick up medications at an offline hospital or drugstore by scanning the QR code through the window and wait for the dispensing machine or pharmacist to dispense the drugs. Moreover, the medication consultation function was also operational. Results: The established internet pharmacy service mode had four major functional segments: online drug catalog search, prescription preview by AI, drug dispensing and distribution, and AI-based medication consultation response. The qualified rate of AI preview was 83.65%. Among the 16.35% inappropriate prescriptions, 49% were accepted and modified by physicians proactively and 51.00% were passed after pharmacists intervened. The “offline self-pick-up” mode was preferred by 86% of the patients for collecting their medication in the internet hospital, which made the QR code to be fully applied. A total of 426 medication consultants were served, and 48.83% of them consulted outside working hours. The most frequently asked questions during consultations were about the internet hospital dispensing process, followed by disease diagnosis, and patient education. Therefore, an AI-based medication consultation was proposed to respond immediately when pharmacists were unavailable. Conclusion: The established AI-based internet hospital pharmacy service mode could provide references for pharmacy departments during the COVID-19 pandemic. The significance of this study lies in ensuring safe/rational use of medicines and raising pharmacists’ working efficiency.
ABSTRACT
Background: To date, the COVID-19 pandemic does not appear to be overcome with new variants continuously emerging. The vaccination against COVID-19 has been the trend, but there are multiple systematic reviews on COVID-19 vaccines in patients with cancer, resulting in redundant and sub-optimal systematic reviews. There are still some doubts about efficacy and safety of the COVID-19 vaccine in cancer patients. Purpose: To identify, summarize and synthesize the available evidence of systematic reviews on response and COVID-19 vaccine safety in patients with cancer. Methods: Multiple databases were searched from their inception to May 1, 2022 to fetch the relevant articles. Study quality was assessed by AMSTAR2. The protocol of this study was registered on PROSPERO (CRD42022327931). Results: A total of 18 articles were finally included. The seroconversion rates after first dose were ranged from 37.30-54.20% in all cancers, 49.60-62.00% in solid cancers and 33.30-56.00% in hematological malignancies. The seroconversion rates after second dose were ranged from 65.30-87.70% in all cancers, 91.60-96.00% in solid cancers and 58.00-72.60% in hematological malignancies. Cancer types and types of therapy could influence vaccine response. COVID-19 vaccines were safe and well-tolerated. Conclusions: This study suggests COVID-19 vaccine response is significantly lower in cancer patients. Number of received doses, cancer types and treatment strategies could influence response of COVID-19 vaccine in cancer patients. COVID-19 vaccines are safe and well-tolerated. Considering the emergence of several new variants of SARS-CoV-2 with potential influence on ongoing vaccination programs, there is a need for booster doses to increase the effectiveness of COVID-19 vaccines. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022327931, identifier CRD42022327931.
Subject(s)
COVID-19 , Hematologic Neoplasms , Neoplasms , Humans , COVID-19 Vaccines , Pandemics , COVID-19/prevention & control , SARS-CoV-2 , Systematic Reviews as Topic , Neoplasms/therapyABSTRACT
Background: While some contacts of COVID-19 cases become symptomatic and radiographically abnormal, their SARS-CoV-2 RNA tests remain negative throughout the disease course. This prospective population-based cohort study aimed to explore their characteristics and significances. Methods: From January 22, 2020, when the first COVID-19 case was identified in Hefei, China, until July 3, a total of 14,839 people in Feidong, Hefei, with a population of ~1,081,000 underwent SARS-CoV-2 RNA testing, where 36 cases (0.2%) with confirmed COVID-19 infection (Group 1) and 27 close contacts (0.2%) testing negative for SARS-CoV-2 RNA but having both positive COVID-19 exposure histories and CT findings (Group 2) from eight clusters were prospectively identified. Another 62 non-COVID-19 pneumonia cases without any exposure history (Group 3) were enrolled, and characteristics of the three groups were described and compared. We further described a cluster with an unusual transmission pattern. Results: Fever was more common in Group 2 than Groups 1 and 3. Frequency of diarrhea in Group 1 was higher than in Groups 2 and 3. Median leucocyte, neutrophil, monocyte, and eosinophil counts were all lower in Groups 1 and 2 than in Group 3. Median D-dimer level was lower in Group 1 than in Groups 2 and 3. Total protein and albumin levels were higher in Groups 1 and 2 than in Group 3. C-reactive protein level was lower and erythrocyte sedimentation rate slower in Groups 1 and 2 than in Group 3. Combination antibacterial therapy and levofloxacin were more often used in Group 3 than in Groups 1 and 2. Lopinavir/ritonavir was more often administered in Groups 1 and 2 than in Group 3. Group 1 received more often corticosteroids than Groups 2 and 3. Group 2 received less often oxygen therapy than Groups 1 and 3. Median duration from illness onset to discharge was longer in Group 1 (27 d) than Groups 2 and 3 (both 17 d). Among contacts of a confirmed COVID-19 patient, only one had a positive virus RNA test but remained asymptomatic and had negative CT findings, and three had negative virus RNA tests but had symptoms and positive CT findings, one of whom transmitted COVID-19 to another asymptomatic laboratory-confirmed patient who had no other exposures. Conclusions: Among close contacts of confirmed COVID-19 cases, some present with positive symptoms and CT findings but test negative for SARS-CoV-2 RNA using common respiratory (throat swab and sputum) specimens; they have features more similar to confirmed COVID-19 cases than non-COVID-19 pneumonia cases and might have transmitted SARS-CoV-2 to others. Such cases might add to the complexity and difficulty of COVID-19 control. Our hypothesis-generating study might suggest that SARS-CoV-2 RNA testing by rRT-PCR assays of common respiratory (throat swab and sputum) specimens alone, the widely accepted "golden standard" for diagnosing COVID-19, might be sometimes insufficient, and that further studies with some further procedures (e.g., testing via bronchoalveolar lavage or specific antibodies) would be warranted for Group 2-like patients, namely, the SARS-CoV-2 RNA-negative (tested using common respiratory specimens), radiographically positive, symptomatic contacts of COVID-19 cases, to further reveal their nature.
ABSTRACT
BACKGROUND: The outbreak of coronavirus-disease-2019 (COVID-19) has rapidly spread to many places outside Wuhan. Previous studies on COVID-19 mostly included older hospitalized-adults. Little information on infectivity among and characteristics of youngsters with COVID-19 is available. METHODS: A cluster of 22 close-contacts of a 22-year-old male (Patient-Index) including youngsters with laboratory-confirmed COVID-19 and hospitalized close-contacts testing negative for severe-acute-respiratory-syndrome-coronavirus-2 (SARS-CoV-2) in Anhui Province, China was prospectively-traced. RESULTS: Since January 23, 2020, we enrolled a cluster of eight youngsters with COVID-19 (median age [range], 22 [16-23] years; six males) originating from Patient-Index returning from Wuhan to Hefei on January 19. Patient-Index visited his 16-year-old female cousin in the evening on his return, and met 15 previous classmates in a get-together on January 21. He reported being totally asymptomatic and were described by all his contacts as healthy on January 19-21. His very first symptoms were itchy eyes and fever developed at noon and in the afternoon on January 22, respectively. Seven youngsters (his cousin and six classmates) became infected with COVID-19 after a-few-hour-contact with Patient-Index. None of the patients and contacts had visited Wuhan (except Patient-Index), or had any exposure to wet-markets, wild-animals, or medical-institutes within three months. For affected youngsters, the median incubation-period was 2 days (range, 1-4). The median serial-interval was 1 day (range, 0-4). Half or more of the eight COVID-19-infected youngsters had fever, cough, sputum production, nasal congestion, and fatigue on admission. All patients had mild conditions. Six patients developed pneumonia (all mild; one bilateral) on admission. As of February 20, four patients were discharged. CONCLUSIONS: SARS-CoV-2-infection presented strong infectivity during the incubation-period with rapid transmission in this cluster of youngsters outside Wuhan. COVID-19 developed in these youngsters had fast onset and various nonspecific atypical manifestations, and were much milder than in older patients as previously reported.