Dentists prescribe 10% of all outpatient antibiotics in the United States and are the top specialty prescriber. Data on current antibiotic prescribing trends are scarce. Therefore, we evaluated trends in antibiotic prescribing rates by dentists, and we further assessed whether these trends differed by agent, specialty, and by patient characteristics.Retrospective study of dental antibiotic prescribing included data from the IQVIA Longitudinal Prescription Data set from January 1, 2012 to December 31, 2019.The change in the dentist prescribing rate and mean days’ supply were evaluated using linear regression models.P = .5915). However, the dental prescribing rate  increased in the Northeast , among oral and maxillofacial surgeons , prosthodontists , endodontists , periodontists , and for amoxicillin . The mean days’ supply significantly decreased over the study period by 0.023 days per 1,000 dentists per year (P < .001).Dentists wrote >216 million antibiotic prescriptions between 2012 and 2019. The annual dental antibiotic prescribing rate remained steady over time (From 2012 to 2019, dental prescribing rates for antibiotics remained unchanged, despite decreases in antibiotic prescribing nationally and changes in guidelines during the study period. However, mean days’ supply decreased over time. Dental specialties, such as oral and maxillofacial surgeons, had the highest prescribing rate with increases over time. Antibiotic stewardship efforts to improve unnecessary prescribing by dentists and targeting dental specialists may decrease overall antibiotic prescribing rates by dentists. Studies on dental antibiotic prescribing have found that penicillins are the most commonly prescribed antibiotic by dentists; they account for ∼70% of all dental antibiotic prescriptions. Dentists also prescribe other classes of antibiotics not commonly prescribed by other providers, such as clindamycin. Infection prophylaxis is the most common reason for antibiotics prescribed by dentists, 77.6% of which are discordant with guidelines in the United States. Dentists also prescribe antibiotics for the treatment of acute oral infections, among which, 12%–28% of prescriptions are unnecessary.In the United States, 10% of outpatient antibiotic prescriptions are written by dentists. and the 2013 American Academy of Orthopedic Surgeons guidelines on infection prophylaxis for patients with specific cardiac diagnoses and prosthetic joints, respectively, as well as the 2019 guidelines for management of pulpal- and periapical-related dental pain and intraoral swelling. Targeted antibiotic stewardship in dental settings have also been implemented to assist with improving guideline-concordant antibiotic use.Guidelines provide recommendations for antibiotic use in dental practice to minimize unnecessary antibiotic prescribing. Antibiotic-specific guidelines include the 2021 American Heart Association (AHA) guidelines However, data from 2015–2017 from the Department of Veterans’ Affairs suggest that dental antibiotic prescribing is decreasing. The primary objective of this study was to evaluate trends in antibiotic prescribing rates by dentists between 2012 and 2019. A secondary objective was to assess whether these trends differed by antibiotic agent and dentist specialty.A recent study of US outpatient antibiotic prescribing between 2011 and 2016 suggests increasing trends in dental antibiotic prescribing, whereas prescribing by medical clinicians has decreased.In this cross-sectional retrospective study of dental antibiotic prescribing, we evaluated data from the IQVIA Longitudinal Prescription Data set (LRx) from January 1, 2012, to December 31, 2019. LRx includes 92% of all dispensed outpatient prescriptions in the United States. LRx contains prescriptions dispensed without insurance reimbursement and those reimbursed by public and private payers. This analysis was performed at the prescription level and included all dispensed prescriptions prescribed by all dentists as well as hygienists and technologists. This data set included prescription data , prescriber data , and patient data (age and sex). Antibiotics were limited to oral forms  or liquid systemic forms (liquid dosage forms). If a prescription was missing information regarding any prescription, patient, or prescriber information, the prescription was excluded. This research was reviewed and approved by the university’s institutional review board. Mean days’ supply was calculated for each year for the number of prescriptions that were prescribed.Dental antibiotic prescribing trends were evaluated using total number of antibiotics prescribed, mean days’ supply, and an annual provider-based prescribing rate. The annual provider-based prescribing rate was calculated by dividing the number of antibiotics prescribed each year by the number of actively prescribing dentists per year (reported as the “provider-based prescribing rate” herein). This number was reported as the prescribing rate per 1,000 dentists per year and the percentage change per year. Actively prescribing dentists were defined as those who prescribed ≥20 of any prescription in a calendar year within the data set.Additional variables to describe the cohort included patient age , patient sex , and US Census Bureau Region . Antibiotics were classified as amoxicillin, clindamycin, cephalexin, azithromycin, penicillin, doxycycline, fluoroquinolones, and other . Amoxicillin-clavulanic acid was combined with the amoxicillin category. Dentists were categorized as general dentists, anesthesiologists, endodontists, orthodontists, periodontists, prosthodontists, oral and maxillofacial surgeons, pediatric dentists, and hygienists or technologists according to dental specialty data within the LRx data set.P < .05. Because large data sets may identify small differences to be statistically significant, we defined clinically important results as differences ≥5%. All analyses were conducted using SAS version 9.4 software .The frequency distribution of prescription data was examined according to patient, provider, and prescription variables. Means with standard deviations were calculated for the provider-based prescribing rate and days’ supply. Linear regression models were used to analyze the annual change in the provider-based prescribing rate, total antibiotics prescribed, and mean days’ supply. We used linear regression models to assess trends across all antibiotics, by adult (≥18) and children’s (<18) prescriptions, by antibiotic agent, geography, and dental specialties. Statistical significance was defined as After removing prescriptions for missing information , >216 million antibiotics were prescribed by 241,106 dentists from January 2012 to December 2019. Most prescriptions were for male patients (55.0%) and for those aged 40–64 years (42.0%). Most prescribing dentists were located in the Southern region (38.7%) and were categorized as general dentists (86.7%) or oral and maxillofacial surgeons (12.2%) (Table P = .5915) (Table P < .001) or 2% per year over the 7-year period. Furthermore, the annual number of prescriptions increased by 10.4% from 2012 to 2017 (Supplementary Table S2 online). However, between 2017 and 2019, the number of prescriptions decreased by 3.2% (Supplementary Table S2).The average provider-based prescribing rate between 2012 and 2019 was 142,155 prescriptions per 1,000 dentists per year . Similar to overall trends, the most commonly prescribed antibiotics for adults and children were amoxicillin , clindamycin (14.6% and 7.7%), and penicillin (1.2% and 12.0%) (Supplementary Table S3).During the study period, ∼202 million (93.6%) of the antibiotics prescribed by dentists were prescribed for adults and 13 million (6.4%) were prescribed for children (Table P = .3433) (Table P ≤ .001) for adult prescriptions between 2012 and 2019  per 1,000 dentists per year at a rate of 0.4% per year and did not significantly increase over the 7-year period (P = .0665) over the study period (Supplementary Table S1 online). The number of antibiotics prescribed significantly decreased at a yearly rate of 17,706 antibiotics per 1,000 dentists per year among children (P = .0084), which was equivalent to a −0.4% change (decrease) in prescribing rate per year. The mean days’ supply for antibiotics prescribed to children  decreased significantly by 0.0077 days per 1,000 dentists per year  between 2012 and 2019.Among children, the mean provider-based prescribing rate for all years was 13,708  per 1,000 dentists per year, and with a nonsignificant decrease . Although penicillin was the second most prescribed antibiotic in 2012, from 2013 through 2019 clindamycin was the second most prescribed antibiotic (Supplementary Table S2). The annual provider-based prescribing rate of amoxicillin increased by 2,562.7 prescriptions per 1,000 dentists per year (P ≤ .001), whereas it decreased for cephalexin, penicillin, doxycycline, fluoroquinolones, and other antibiotics at rates of −328, −894.5, −305.4, −91.4, and −150.50 prescriptions per 1,000 dentists annually, respectively . This finding also suggests dentist concordance with recent guidelines recommending shorter durations.Over the study period, the antibiotic prescribing rate per 1,000 dentists remained steady, whereas the mean days’ supply for all antibiotics decreased. This finding suggests that although the prescribing rate was unchanged over the study period, the days’ supply decreased and, thus, fewer doses of antibiotics prescribed by dentists circulated in the community. Considering that the majority of antibiotics prescribed by dentists are for preventative reasons, However, a more recent national analysis by King et al found that dental prescribing increased while medical clinician prescribing decreased between 2011 and 2016. In our study with a longer timeframe of data through 2019, trends in the dental antibiotic prescribing rate remained steady and were discordant with national decreases observed for medical clinicians.Previous research has described trends in antibiotic prescribing by all provider types, including dentists. We previously identified a decrease in dental antibiotic prescribing between 2005 and 2010, from 10.7% of all antibiotics prescribed in the community in 2005 to 10% in 2010. identified the highest proportion of prescriptions among general dentists followed by oral and maxillofacial surgeons in a commercially insured cohort. Importantly, oral and maxillofacial surgeons had the highest prescribing rate in our study. Although oral and maxillofacial surgeons prescribed 12% of all antibiotics over the study period, these dental specialists only account for 4% of all dentists in the United States. With the exception of orthodontists, large increases in the prescribing rate were observed for dental specialists, especially oral and maxillofacial surgeons, endodontists, periodontists, and prosthodontists. We also identified a temporary increase in antibiotic prescribing by dental anesthesiologists in 2016. The reason for the increases in prescribing rate by dental specialists is unclear, and a lack of visit-level data made it difficult to decipher the cause. Potential explanations for increased prescribing by dental specialists include the increased use of dental implants and worsening oral health in an aging population. To our knowledge, this is the first description of antibiotic prescribing trends by dental specialists.Similar to results in our population-level cohort, Durkin et alThis study had several limitations. The IQVIA LRx data set did not include characteristics of dental visits or patient comorbidities. Thus, we could not evaluate the appropriateness of the antibiotic prescribed. Furthermore, we included all prescriptions dispensed, but we could not determine whether patients actually took the antibiotic. Finally, the data included in this study may not include all patients receiving dental care because the LRx database only contains information on dispensed prescriptions. Population-level prescription data sets, such as IQVIA LRx, can be used to monitor the need for and effectiveness of antibiotic stewardship strategies. The CDC Core Elements of Outpatient Antibiotic Stewardship recommend the use of prescribing data to inform stewardship efforts. Although dentists are included as a targeted group to implement the Core Elements, there are few examples of the implementation of antibiotic stewardship in dental practices. These antibiotic stewardship strategies should be tailored to the practice of dental specialists, especially oral and maxillofacial surgeons. Future monitoring should assess overall antibiotic prescribing rates, trends by dental specialists, and the impact of removing clindamycin from the 2021 update to the AHA infective endocarditis prophylaxis guidelines. Before-and-after analyses specific to guideline changes and/or stewardship efforts that are implemented as a result of these data can also be monitored with the use of IQVIA LRx to determine whether these strategies have made a significant impact. Using these data in this manner can be an effective monitoring strategy in future dental stewardship efforts. Antibiotics are commonly used as premedication to prevent complications from tooth extractions and dental implants. Although data are mixed on the effectiveness of this practice, guidelines recommending antibiotic prophylaxis for extractions and implants are not available. The United Kingdom does not recommend antibiotics to prevent postoperative infection or dry socket associated with tooth extraction and only recommends antibiotics to prevent dental implant complications when bone augmentation is part of the procedure. Finally, the impact of the 2015 ADA guidelines removing antibiotic prophylaxis recommendations in patients with prosthetic joints appears to have minimal, if any, impact on overall antibiotic prescribing rates by dentists.Regardless, our results are relevant to public health efforts to preserve the effectiveness of antibiotics. Obtaining data identifying the indication for a dental antibiotic is challenging.In conclusion, between 2012 and 2019, provider-based prescribing rates for all antibiotics prescribed by dentists remained steady, which is discordant with medical clinician prescribing trends. However, mean days’ supply for antibiotics prescribed by dentists did decrease over time. Oral and maxillofacial surgeons had the highest prescribing rate, with increases over time. Antibiotic stewardship efforts to improve unnecessary prescribing by dentists and targeting dental specialists and prescribing of clindamycin may decrease overall antibiotic prescribing rates by dentists.


Background: Antimicrobial stewardship programs (ASPs) often rely on International Classification of Diseases, Tenth Revision (ICD-10) codes to assess antibiotic appropriateness for provider feedback. Concordance between encounter ICD-10 codes and documented indication for antibiotics based on manual chart review varies greatly (74%–95%) in the inpatient setting. Data on concordance between documented indication and ICD-10 code in the outpatient setting are scarce. Methods: We conducted a retrospective cohort study of 650 randomly selected outpatient encounters with antibiotic prescriptions from walk-in and retail clinics between July 15 and September 15, 2021, at Vanderbilt University Medical Center. We performed chart review to compare documented antibiotic indication to the 3 most frequent encounter-associated ICD-10 codes. Also, 12 encounters were excluded due to insufficient available written documentation. The 95% CI for proportion of encounters with concordant antibiotic indications was calculated using Stata version 15.1 software. Results: Of the 638 antibiotic prescriptions with written documentation available for chart review, 204 (32%) were for amoxicillin, 102 (16%) were for amoxicillin-clavulanate, 61 (10%) were for cefdinir, and 56 (9%) were for azithromycin. Overall, 540  of 638 encounters had concordant antibiotic indication based on documentation in the note and associated ICD-10 for the encounter. Of the 540 encounters with concordant ICD-10 and documented indications, 348 (64%), 130 (24%), and 35 (6%) were listed as the first, second, and third ICD-10 codes, respectively. An additional 27 (5%) had a concordant ICD-10 code listed beyond the third position. In total, 125 (19.6%) of 638 encounters did not have the intended antibiotic indication as documented in the note in the 3 most frequent encounter-associated ICD-10 codes (whether a lower position or incongruent ICD-10 code with documentation). Of those 125 encounters, 42 (34%) had a documented diagnosis of strep pharyngitis, 16 (13%) had a documented diagnosis of skin or soft-tissue infection, 11 (9%) had a documented diagnosis of urinary tract infection, and 11 (9%) had a documented diagnosis of acute otitis media. Conclusions: Our data suggest that outpatient antimicrobial prescriptions correlate relatively well with encounter ICD-10 codes. However, most ASP prescribing goals aim to reduce inappropriate prescribing to 10% or fewer of prescriptions based on indication. Therefore, providers may not trust individual prescribing feedback that is based on data that is only correct 85% of the time. For ASPs to accurately assess prescribing and provide trusted, meaningful recommendations and specific feedback to individual prescribers, more reliable and valid data are needed. We intend to evaluate whether requiring outpatient antibiotic indications on prescriptions increases data reliability and validity.Disclosures: None


Immunoglobulin G4-related disease (IgG4-RD) is a fibroinflammatory condition characterized by tissue infiltration with lymphocytes and IgG4-secreting plasma cells. The presentation of IgG4-RD is heterogenous, making it difficult to diagnose. IgG4-RD presenting as a parapharyngeal mass is extremely rare. This report discusses the case of a 69-year-old African American female presenting with intermittent bilateral frontal headaches. Initial imaging revealed an ill-defined parapharyngeal mass encasing the left internal carotid artery and left internal jugular vein. Subsequent biopsy and immunohistochemistry showed a high concentration of IgG4-positive plasma cells with storiform fibrosis, despite normal serum IgG4 levels. The patient opted for conservative management. The localized parapharyngeal mass has remained stable over two years on annual imaging. This case report highlights that IgG4-RD can have varied and nonspecific presentations requiring high clinical suspicion to diagnose. Histopathology and IgG4 staining are vital to confirm the diagnosis of IgG4-RD, particularly in atypical cases not meeting the standard inclusion criteria. Immunoglobulin G4-related disease (IgG4-RD) is an inflammatory condition characterized by tissue infiltration with lymphocytes and IgG4-secreting plasma cells and associated fibrosis. Initially described in 2001 in patients with sclerosing cholangitis [A 69-year-old African American female visited the emergency department (ED) multiple times over two months for intermittent bilateral temple headaches and retro-orbital pain, with associated photophobia, phonophobia, and hypersensitivity to odors. The headache worsened with bending, exertion, and coughing and often resolved spontaneously. She was treated for migraine during the ED visits and was referred to the neurology clinic for further workup. Her medical history was significant for migraine, diagnosed as a teenager, on daily maintenance topiramate and as-needed zolmitriptan pills. In the clinic, she endorsed experiencing worsening headaches, including severity, duration of individual headaches, and overall frequency for the past year, which did not improve with her current medications. The patient denied visual disturbances, nausea or vomiting, and loss of weight or appetite. The patient denied smoking, alcohol use, or other recreational drug use. Other medications included ascorbic acid, astragalus root, cholecalciferol, ginkgo, and multivitamin pills. The patient had two first-degree relatives (mother and sister) who died from brain aneurysms.The patient’s vitals in the clinic were stable, with a blood pressure of 140 mmHg systolic and a heart rate of around 100 beats/minute. Her neurological examinations, including attention, concentration, memory, gait, visual fields, cranial nerves II-XII, power, tone, sensations , deep tendon reflexes, proprioception, and coordination, were within normal limits. The rest of the physical examination was unremarkable.Given her family history of brain aneurysms, magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA) of the brain were done that showed a partially visualized mass in the left upper neck involving the adenoids, abutting and possibly involving the pterygoid muscles, encasing a portion of the left internal carotid artery, and abutting the longus coli muscles (measuring at least 2.2 cm × 4 cm × 4.7 cm). The MRA did not show any evidence of flow-limiting stenosis intracranially or any sizable intracranial aneurysms.A subsequent computed tomography (CT) of the soft tissue of the neck showed an ill-defined contrast-enhancing trans-spatial mass in the left upper neck near the skull base (measuring approximately 4.5 cm × 3.0 cm × 4.1 cm) involving the posterior adenoids, torus tubarius, and left longus coli muscles. Posteriorly, it also encased the distal cervical left internal carotid artery and left internal jugular vein. Inferiorly, it extended to the superior margin of the left palatine tonsil. She also had a few level 2 left cervical lymph nodes that were asymmetric to the contralateral side but did not appear to be significantly enlarged (with the largest node measuring 1.1 cm × 0.8 cm)  . Other dBased on the current consensus recommendations , glucocoIgG4-RD can have a nonspecific and heterogenous presentation making the initial diagnosis challenging. Isolated parapharyngeal presentation is rare and often needs histopathology and IgG4 staining to confirm the diagnosis. Physicians should remain cognizant irrespective of the serum IgG4 levels.


IgG4-related digestive diseases encompass a group of chronic inflammatory disorders characterized by autoimmune reactions and fibrosis affecting multiple digestive organs. These diseases are identified by elevated serum levels of IgG4 and the presence of IgG4-positive plasma cell infiltration in the affected sites, along with storiform fibrosis, obliterative phlebitis, and eosinophilic infiltration. Although extensive research has been conducted, a comprehensive understanding of these conditions remains elusive. Current clinical diagnosis often relies on the application of integrated diagnostic criteria for IgG4-related diseases, combined with specific organ involvement criteria. Distinguishing them from malignancies poses considerable challenges. Moreover, further investigations are required to elucidate the underlying pathogenic mechanisms and explore potential therapeutic interventions. This review provides a systematic classification of IgG4-related digestive diseases while discussing their diagnostic strategies, clinical presentations, and treatment modalities. The comprehensive insights shared herein aim to guide clinicians in their practice and contribute to the advancement of knowledge in this field. In 2012, the international medical community standardized the nomenclature for this class of diseases as IgG4-RD . Currently, the understanding of the pathogenic mechanisms underlying this condition remains limited, with both genetic and environmental factors contributing to its development. The disease’s etiology primarily involves dysregulation of the immune system, encompassing innate and adaptive immunity, as well as interactions between B cells and T cells Figure 22IgG4-DSD is a type of IgG4-RD characterized by multi-organ fibroinflammatory involvement. Its clinical presentation is diverse, with a lack of specific biomarkers, imaging findings, and laboratory tests, making diagnosis challenging. Thus, IgG4-DSD is often confused with other diseases and malignancies, leading to misdiagnosis and underdiagnosis. To address this issue, a three-step classification for IgG4-RD was proposed by the European League Against Rheumatism and the American College of Rheumatology in 2019 2, whichHowever, due to the significant variations in clinical symptoms among different organ involvements, there is currently no unified diagnostic criteria. The updated comprehensive diagnostic criteria for IgG4-related disease in 2020 can be consulted . The folFirstly, elevated serum and tissue levels of IgG4 are important diagnostic criteria. The current consensus considers a serum IgG4 cutoff value of 1.35 g/L. However, different studies have defined this cutoff value differently. Research has shown that a serum IgG4 level greater than 2.5 g/L helps distinguish primary sclerosing cholangitis (PSC) from IgG4-related sclerosing cholangitis (IgG4-SC), with a sensitivity of 67%-89% and specificity of 95% . Some stUp to this point, the field of IgG4-DSD diagnosis and treatment has been characterized by a dearth of robust medical evidence and a lack of standardization in treatment protocols. The diagnostic procedures have largely relied on the 2011 Japanese comprehensive diagnostic criteria for IgG4-RD , as illu33.1Autoimmune pancreatitis (AIP) is a rare disease characterized by an autoimmune reaction and the total prevalence of the disease was 0.0101%, and the annual incidence was 0.0031% . AccordiThe onset of AIP is insidious, and typical symptoms include painless obstructive jaundice in elderly males, as well as nonspecific symptoms such as low-grade fever, fatigue, diarrhea, and weight loss. The disease often exhibits recurrent episodes. Acute painful pancreatitis is less common compared to IgG4-negative AIP . ResearcCurrently, the main guidelines used for diagnosing AIP include the International Association of Pancreatology 2011 guidelines , ChineseThe diagnostic pathway for AIP is depicted in 3.2IgG4-related sclerosing cholangitis (IgG4-SC) is a biliary manifestation belonging to the spectrum of IgG4-related diseases. It is the second most common disease within the IgG4-related diseases, sharing similar clinical and pathological features with AIP. Approximately 88% of IgG4-SC patients also have AIP , while iClinical diagnostic criteria for IgG4-SC include the IgG4-Related Disease consensus diagnostic criteria , IgG4-SCIn the diagnostic process, elevated levels of serum IgG4 are important evidence for diagnosing IgG4-SC. Approximately 90% of IgG4-SC patients have elevated serum IgG4 levels . HoweverImaging plays a pivotal role in the diagnosis of IgG4-SC, which typically exhibits features such as diffuse or segmental stenosis of intra- and extrahepatic bile ducts, thickening of the bile duct wall, and involvement of other organs. Various imaging modalities are employed, including ultrasound endoscopy (EUS), X-ray computed tomography (CT), magnetic resonance imaging (MRI), magnetic resonance cholangiopancreatic water imaging (MRCP), and endoscopic retrograde cholangiopancreatography (ERCP). Among these, EUS and biliary intraluminal ultrasound (IDUS) stand out for their ability to visualize the structural layers of the biliary wall and measure its thickness. EUS is particularly versatile, as it not only assesses wall thickness and identifies intraluminal lesions but also detects pancreatic swelling associated with AIP and allows for tissue biopsy. Typical sonographic features of IgG4-SC include uniformly hypoechoic circumferential thickening of the duct wall and a smooth inner rim . StudiesHistopathologically, IgG4-SC is characterized by abundant lymphocyte and plasma cell infiltration, IgG4-positive plasma cell infiltration, storiform fibrosis, and obliterative phlebitis, often accompanied by eosinophil infiltration. Lesions usually originate from the mucosal layer of the bile duct wall and gradually extend outwardly, involving not only the strictured segment but also the dilated segments, while the biliary epithelium often remains unaffected . Immunoh3.3Among IgG4-DSD, apart from the pancreas and biliary tract, the salivary glands are the third most commonly affected organs and tissues. IgG4-related salivitis mainly includes IgG4-related Mikulicz Diseases (IgG4-MD) and IgG4-related Chronic Sclerosing Sialadentis (IgG4-CSS) .The current diagnostic criteria for IgG4-related salivary gland disease are summarized as follows, taking into account findings from both domestic and international research :Clinical Evaluation: Persistent enlargement of the submandibular gland or parotid gland should be observed through clinical examination and auxiliary tests.Laboratory Tests: Elevated levels of serum IgG and IgG4 concentrations (>1.35g/L) should be detected in laboratory tests.Histopathology: Histopathological examination is pivotal. Immunohistochemical results should be interpreted, focusing on positive cells localized within the cytoplasm of plasma cells when viewed under a microscope. Specifically, three areas with high-density positive cells should be selected, and the total count of IgG4-positive and IgG-positive cells should be determined in these three high-power fields. The average count of IgG4-positive and IgG-positive cells in each high-power field should then be calculated. A diagnosis is established if the number of IgG4-positive plasma cells per high-power field is ≥50. In biopsy cases, the criteria may be ≥10 IgG4-positive plasma cells per high-power field, and the ratio of IgG4-positive to IgG-positive plasma cells should be ≥40%.Based on the degree of fulfillment of the above three diagnostic criteria, the diagnosis is categorized as follows:Definitive Diagnosis: Positive for criteria 1, 2, and 3.Likely Diagnosis: Positive for criteria 1 and 3.Probable Diagnosis: Positive for criteria 1 and 2.IgG4-CSS and IgG4-MD exhibit distinct clinical manifestations and auxiliary examination findings, which are described as follows.3.3.1IgG4-CSS was first discovered and described by the renowned German physician Küttner in 1896. Seifert et al. renamed Küttner’s tumor as Chronic Sclerosing Sialadenitis (CSS) . In 2011IgG4-CSS predominantly affects middle-aged men and typically exhibits a protracted disease course. This condition primarily manifests as symmetrical enlargement of the submandibular gland, characterized by a constrained hard texture of the swelling. In some cases, the swelling may present nodular characteristics. Notably, the affected area typically maintains a normal coloration, and the borders of the swelling tend to be well-defined. Additionally, patients may experience mild to moderate dryness in the mouth as a concurrent symptom. Furthermore, IgG4-CSS can extend beyond the submandibular gland, involving other salivary glands such as the parotid gland and the sublingual gland. On rare occasions, this condition can also affect the lacrimal gland . ApproxiGenerally, laboratory investigations of CSS reveal elevated levels of IgG4. However, in cases of antigen excess during testing, a double band effect may occur, leading to normal IgG4 levels , 49. Fur3.3.2IgG4-MD, also known as Mikulicz syndrome, was first reported as early as 1892. This condition predominantly affects middle-aged and elderly individuals, with an average age of onset at 55 years. It is more common in males in Western countries, while females are predominantly affected in Japan .Clinically, IgG4-MD is characterized by painless, symmetrical, and persistent enlargement of the unilateral or bilateral submandibular, parotid, or lacrimal glands for more than three months. Mild dry mouth and dry eye symptoms may accompany the glandular enlargement, making it easily confused with Sjögren’s syndrome (SS).While both IgG4-associated Mikulicz’s disease (MD) and Sjögren’s syndrome share common features of glandular enlargement accompanied by lymphocytic infiltration, it’s crucial to recognize the substantial clinical and pathological distinctions between these two conditions . On imagSjögren’s syndrome is characterized by prominent symptoms of dry mouth and dry eyes, with relatively less significant glandular enlargement and notable reduction in glandular secretory function. Antinuclear antibodies and anti-SSA/SSB antibodies are frequently detected . To diff3.4In 2007, Umemura et al. reported the first case of IgG4-related autoimmune hepatitis (IgG4-AIH) , which eIgG4-AIH represents a subtype of AIH rather than an involved site of IgG4-RD. Similar situations have been observed in other IgG4-RDs, particularly in patients with autoimmune pancreatitis (AIP) where infiltration of IgG4-positive plasma cells is commonly found during liver biopsies, but can only be diagnosed as liver damage caused by IgG4-RD. Studies on a small number of patients have suggested that IgG4-AIH and non-IgG4-related AIH share similarities in laboratory findings and histopathological manifestations, with both demonstrating a certain degree of responsiveness to glucocorticoid therapy. However, IgG4-AIH patients may require a shorter duration for alanine aminotransferase normalization after glucocorticoid treatment compared to non-IgG4-related AIH . It is iCurrently, there is a lack of unified diagnostic criteria for IgG4-AIH, necessitating comprehensive consideration of clinical, biochemical, immunological, and liver histopathological examination results. Umemura et al. recommended including the following diagnostic criteria for IgG4-AIH: (1) fulfillment of the diagnostic criteria for AIH; (2) serum IgG4 ≥1.35 g/L; and (3) liver biopsy demonstrating >10 IgG4-positive plasma cells per high-power field in the portal area. Some researchers also propose that the ratio of IgG4-positive plasma cells to IgG1-positive plasma cells >1 in liver tissue can serve as one of the diagnostic criteria for this disease. Chung et al. considered a cut-off value of ≥5 IgG4-positive plasma cells per high-power field in the liver tissue as the diagnostic criterion for IgG4-AIH .3.5A study by Shinji et al. in 2004 found that patients with AIP have a significantly higher incidence of gastric ulcer compared to the control group . HistoloAIP-G is a subtype of AIP characterized by chronic gastritis. Endoscopic examination commonly shows gastric ulcers and chronic inflammation, with negative detection of Helicobacter pylori. Biopsy samples from the mucosal layer demonstrate abundant infiltration of plasma cells, lymphocytes, and eosinophils, particularly IgG4-positive plasma cells. Neutrophil infiltration, on the other hand, is rarely observed . AdditioUehara et al. summarized 39 cases of gastric involvement in IgG4-RD patients, of which only 40% presented typical gastric manifestations . The maj3.6IgG4-related disease involving the mesentery primarily presents as sclerosing mesenteritis, a rare chronic condition characterized by localized or diffuse fibrosis and inflammation of the mesentery in the small intestine. Patients affected by this condition typically exhibit nonspecific abdominal symptoms such as pain, bloating, diarrhea, or even ischemia. Clinical management of sclerosing mesenteritis can be quite challenging . On imag3.7Ormond’s Disease, also known as IgG4-related retroperitoneal fibrosis, is a form of IgG4-related disease primarily affecting the retroperitoneum. It is characterized by idiopathic fibrosis of the retroperitoneum and belongs to a group of chronic periaortitis disorders, including IgG4-related peritoneal fibrosis, periaortitis, and inflammatory aortic aneurysm. The typical clinical manifestations include vague pain localized in the back, flank, lower abdomen, and inner thigh, as well as lower limb edema and hydronephrosis . It is i4Treatment of IgG4-RD and IgG4-DSD follows similar approaches. In 2015, a consensus statement on the management and treatment of IgG4-RD was published .This sta4.1Glucocorticoids are the first-line therapy for the treatment of IgG4-DSD. Currently, the international consensus advocates for an initial treatment regimen of oral prednisone at a dose of 30-40 mg/day or 0.6 mg/(kg·day). After 2-4 weeks of treatment, the dose is gradually reduced by 5 mg every 1-2 weeks based on clinical manifestations, radiological findings, and laboratory results. The aim is to taper the dose to 5 mg/day over a period of 3-6 months and discontinue the medication . JapanesAlthough initial remission rates are high after short-term immunization shocks with glucocorticosteroids, outbreaks and relapses are still common . Therefo4.2DMARDs are used as adjunctive therapy to glucocorticoids in the treatment of IgG4-DSD . The pur4.3B-cell targeted therapy represents a precision clearance approach rooted in the elevated presence of B lymphocytes and CD4 T cells during the pathological progression of IgG4-related diseases. The underlying mechanism of action hinges on the depletion of B cells, which serves multifaceted purposes. This strategy effectively impedes the presentation of antigens to CD4 cytotoxic T lymphocytes, concurrently mitigating tissue fibrosis, and lowering serum IgG4 concentrations. By diminishing the production of immune complexes, this therapy safeguards tissues from damage, marking a pivotal breakthrough in recent research endeavors. In recent years, therapeutic interventions centered on B-cell targeting have garnered substantial attention and enthusiasm among the scientific community .Rituximab (RTX) stands out as the earliest and most extensively researched B-cell targeted therapy, demonstrating unequivocal efficacy . This drExcept for RTX, XmAb5871 represents a monoclonal antibody targeting FcγRIIb and CD19, effectively suppressing various facets of B-cell functionality, including activation, proliferation, and antigen presentation, employing multiple pathways . On anot4.4The pathogenesis of IgG4-related disease involves various types of T cells, including helper T cells 2 (Th2), regulatory T cells (Treg), and follicular helper T lymphocytes (Tfh), all of which play crucial roles in the disease progression. Consequently, targeting T cells has emerged as a promising therapeutic strategy for IgG4-RD, albeit with limited current treatment options. Abatacept is a recombinant fusion protein with its mechanism of action involving cytotoxic T lymphocyte-associated protein 4 (CTLA-4). It interferes with antigen presentation by competitively binding to CD80/86 on the surface of antigen-presenting cells, thereby inhibiting the activation of T cells. This mechanism holds potential for application in the treatment of IgG4-RD. Elotuzumab, on the other hand, is a monoclonal antibody that targets SLAMF7  protein. It operates by selectively inhibiting CD4+ cytotoxic T lymphocytes (CTLs) expressing SLAMF7, aiding in the control of the pathogenic process in IgG4-RD . Recent 4.5Biliary drainage is a necessary adjunctive treatment for patients with severe cholestasis or pressure symptoms caused by other organ involvement; surgery is also required for malignant tumors due to space-occupying lesions. However, the pros and cons of surgery need to be fully weighed, and there are many reports that surgery does not bring more benefit to the disease, or even does not alleviate the disease .5Recent years have witnessed an increasing recognition of IgG4-RD, an immune-mediated condition characterized by end-stage fibrosis that can lead to multi-organ failure and significantly impact patients’ quality of life. However, the lack of specific diagnostic and therapeutic tools often results in missed or misdiagnosed cases, leading to delayed treatment initiation. Notably, IgG4-DSD has emerged as the most prevalent subtype among IgG4-RD, prompting increasing attention from clinicians.Despite advancements in understanding IgG4-DSD, its pathogenesis remains incompletely elucidated, and there is a lack of standardized diagnostic criteria. Furthermore, the pros and cons of various treatment options have not been definitively established, and patients often experience high recurrence rates. Clinical studies have indicated that elevated serum IgG4 levels serve as a useful diagnostic marker, alongside imaging findings. However, the main challenge lies in differentiating IgG4-DSD from malignant tumors, with pathological diagnosis being considered the current “gold standard.” Moreover, the effective treatment of glucocorticoid can also be used as a reference.Controversies persist regarding the management of IgG4-DSD, with conventional interventions being commonly employed but numerous research questions remaining unanswered. Hence, healthcare providers should enhance their understanding of IgG4-DSD and undertake further research to explore its underlying mechanisms and clinical characteristics comprehensively. These endeavors aim to advance the diagnosis and treatment of this condition, and improve patient outcomes.SW: Writing – original draft. HW: Writing – review & editing.


A major driver of antimicrobial resistance (AMR) and poor clinical outcomes is suboptimal antibiotic use, although data are lacking in low-resource settings. We reviewed studies on systemic antibiotic use (WHO ATC/DDD category J01) for human health in Indonesia, and synthesized available evidence to identify opportunities for intervention.We systematically searched five international and national databases for eligible peer-reviewed articles, in English and Indonesian, published between 1 January 2000 and 1 June 2021 including: (1) antibiotic consumption; (2) prescribing appropriateness; (3) antimicrobial stewardship (AMS); (4) consumers’ and providers’ perceptions. Two independent reviewers included studies and extracted data. Study-level data were summarized using random-effects model meta-analysis for consumption and prescribing appropriateness, effect direction analysis for antimicrobial stewardship (AMS) interventions, and qualitative synthesis for perception surveys. (PROSPERO: CRD42019134641)Of 9323 search hits, we included 100 reports on antibiotic consumption (20), prescribing appropriateness (49), AMS interventions (13), and/or perception (25) (8 categorized in >1 domain). The pooled estimate of overall antibiotic consumption was 134.8 DDD per 100 bed-days (95%CI 82.5–187.0) for inpatients and 121.1 DDD per 1000 inhabitants per day (10.4-231.8) for outpatients. Ceftriaxone, levofloxacin, and ampicillin were the most consumed antibiotics in inpatients, and amoxicillin, ciprofloxacin, and cefadroxil in outpatients. Pooled estimates for overall appropriate prescribing (according to Gyssens method) were 33.5% (18.1–53.4) in hospitals and 49.4% (23.7–75.4) in primary care. Pooled estimates for appropriate prescribing (according to reference guidelines) were, in hospitals, 99.7% (97.4–100) for indication, 84.9% (38.5-98.0) for drug choice, and 6.1% (0.2–63.2) for overall appropriateness, and, in primary care, 98.9% (60.9-100) for indication, 82.6% (50.5–95.7) for drug choice and 10.5% (0.8–62.6) for overall appropriateness. Studies to date evaluating bundled AMS interventions, although sparse and heterogeneous, suggested favourable effects on antibiotic consumption, prescribing appropriateness, guideline compliance, and patient outcomes. Key themes identified in perception surveys were lack of community antibiotic knowledge, and common non-prescription antibiotic self-medication.Context-specific intervention strategies are urgently needed to improve appropriate antibiotic use in Indonesian hospitals and communities, with critical evidence gaps concerning the private and informal healthcare sectors.Wellcome Africa Asia Programme Vietnam. Indonesia, and the Southeast Asian region, is regarded a global hotspot for the emergence and spread of antimicrobial resistance (AMR) because of dense populations, unprecedented, yet uneven, economic development, fragile health systems with variations in access to quality health care, high infectious disease burdens, and weakly enforced antibiotic policies. Indonesia has seen an estimated 2.5-fold increase in nation-wide antibiotic consumption between 2000 and 2015, based on pharmaceutical sales data, mostly driven by broad-spectrum penicillins, fluoroquinolones and cephalosporins. Representative contemporary data on antibiotic use are lacking, although available data suggest antibiotic overuse in the healthcare system, widespread over-the-counter use in communities, and high levels of AMR among common Gram-negative bacteria. A comprehensive review on antibiotic use in human health in Indonesia has not been conducted to date.We reviewed government resources, situation analysis reports, websites of key global and government agencies, and searched PubMed with the terms “Indonesia”, “antibiotic use”, and “antibiotic consumption”, until December 1This review represents a first attempt at systematically assessing the peer-reviewed literature, including English and Indonesian language publications, on human antibiotic use in Indonesia spanning the past 20 years. This evidence synthesis provides a reference document, providing important insights in the magnitude, patterns and drivers of antibiotic use, as well as identifying areas where critical information is lacking. Available data suggested that only 34 and 49% of antibiotic prescriptions were appropriate in hospital and primary care settings, respectively, although the quality of the evidence was low. Studies to date evaluating bundled AMS interventions, although sparse and heterogeneous, suggested favourable effects on antibiotic consumption, prescribing appropriateness, guideline compliance, and patient outcomes. Perception surveys among healthcare providers and communities suggested important gaps in community antibiotic knowledge, and that non-prescription antibiotic self-medication is common practice, although data on health system-level drivers of antibiotic use were lacking.There are critical evidence gaps on antibiotic use in the informal and formal private health care sector as well as geographic areas outside of Java Island, and what are health system drivers of antibiotic use. There is a need to strengthen the local research base to develop context-specific sustainable AMS models that consider country-specific socio-cultural circumstances. Optimisation of antimicrobial use as a means to tackle AMR and improve the treatment of bacterial infections, should be a priority of the national agenda for universal health coverage.Alt-text: Unlabelled box,The global rise in antimicrobial resistance (AMR) is one of the greatest public health threats, with a disproportionate impact in low- and middle-income countries (LMICs).,Jaminan Kesehatan Nasional),,,Indonesia is a lower-middle-income country in Southeast Asia with the world's fourth largest population (274 million), and socio-economic conditions and health indicators vary widely across the archipelago. More than 55% of the population is concentrated on Java Island, which has the best developed health infrastructure.We therefore systematically reviewed the scientific literature on antibiotic use for human health, in both hospital and primary care settings, in Indonesia spanning the past 20 years. This Review focused on four key domains: (1) antibiotic consumption; (2) appropriateness of antibiotic prescribing; (3) AMS interventions; (4) knowledge, attitudes and perceptions among consumers and providers. This Review also reflects on current progress in the National Action Plan for AMR, and defines evidence gaps and context-specific priorities for action.Table S1. Reference screening was used to identify additional relevant papers. The review was limited to antibacterials for systematic human use (J01 category in WHO ATC/DDD index). We did not contact study authors.This systematic review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines.1.Antibiotic consumption, expressed as WHO-defined defined daily dose (DDD) per 100 bed-days (inpatients) or 1000 inhabitants per day (outpatients) . We decided post-hoc to exclude paediatric studies because all studies incorrectly used DDD instead of days of therapy (DOT), as advised by WHO (dose recommendations may differ based on age and weight).2.,Audits of antibiotic prescribing appropriateness for treatment or prophylaxis, based on either Gyssens method or compliance with reference guideline(s). According to the Gyssens method,3.AMS intervention evaluation studies, with a clearly described pre-post or (quasi-) experimental design and outcome measures.4.Surveys assessing knowledge, attitudes and/or perceptions on antibiotic use, including factors related to health system, health care providers and/or consumers.We categorised the included reports within one or more of the following domains as follows:Table S2). All steps in this systematic literature search were conducted using Mendeley reference management software. Two reviewers  separately screened all titles and abstracts, and removed duplicates. Full-text articles were independently judged for relevance and quality by at least two reviewers . Any disagreements were resolved by a senior researcher (RLH).We excluded non-human studies; studies exclusively describing other (non-J01) drugs; describing or comparing the effectiveness, cost, quality and/or molecular profiles of antibiotics; exclusively targeting particular diagnoses and its treatment; non-peer-reviewed papers, student theses, conference proceedings, and studies with irretrievable full-text. Because the included studies were mostly neither randomised controlled studies nor comparative studies, traditional methods for assessment of risk of bias were not applicable. To ensure quality, we excluded studies that did not report an essential set of STROBE checklist core items,We extracted and tabulated data on study design, location, size, population, health care setting, year of study, indicators, interventions, outcome measures and effects, and emerging themes, as appropriate and relevant, based on the author-reported summary estimates . Data were extracted by two reviewers  onto a predesigned form.2 statistic  and chi-squared test (p < 0.10). When two or more studies involved overlapping populations, data synthesis was prioritised to studies with larger sample sizes. Subgroup analyses were then performed by dichotomising the studies based on health care setting , study location, year of study, AWaRe classification (for DDD only), and age groups (for appropriateness only). We also performed sensitivity analyses by sequentially excluding individual studies (for DDD and Gyssens), and by replicating the analysis using other transformations and without transformation (for Gyssens only). All meta-analyses were performed in R version 4.1.0. When appropriate (k≥10), publication bias assessments were performed by visually inspecting funnel plots, generated by plotting the inverse square root of study sizes against the effect estimates,p < 0.10).Where possible, data on antibiotic consumption and appropriateness of antibiotic prescribing were pooled with random-effects meta-analyses. Data on antibiotic consumption were pooled with meta-analyses of rates using the generic inverse variance method, with DDD per 100 bed-days for inpatients and DDD per 1000 inhabitants per day (DID) for outpatients as the rates, and sample sizes as the denominator. Furthermore, we also reported the top-15 antibiotics with the highest DDDs for inpatients and outpatients, provided that the antibiotic was reported in at least two studies, and grouped them according to the 2021 WHO AwaRe  classification.Due to substantial clinical heterogeneity in studies evaluating AMS interventions, we synthesised the findings using a vote-counting method based on effect direction. The interventions were classified as structural, enabling, persuasive, restrictive, or combined (bundled).The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.The search strategy collectively gave 9 323 hits. After title and abstract screening and duplicate removal, 551 articles remained . After f2=100%; Figure S1) for inpatients and 121.1 DID  for outpatients. Among inpatients, ceftriaxone was the most consumed antibiotic (60.0 DDD per 100 bed-days [95%CI 22.9-97.2]), followed by levofloxacin (21.3 DDD per 100 bed-days [95%CI 0.0-44.0]) and ampicillin  that reported data on antibiotic consumption, of which 16 patientsn < 10), publication bias assessment was only performed for inpatients, which showed an asymmetrical funnel plot , indicating potential reporting bias or true heterogeneity in antibiotic consumption patterns between studies, hospitals and/or geographic areas.Among inpatients, subgroup analyses  showed h,,There were 49 reports that reported data on the appropriateness of antibiotic prescribing, of which 182=97.2%) . Confidence analysis showed that the overall estimate was not dominated by a single study  and was similar between approximation methods . The symmetrical funnel plot  indicated low risk of bias from small-study effects. Subgroup analyses showed higher appropriateness of antibiotic prescribing in adults (43.1% [95%CI 25.9-62.2%] than in children (8.4% [95%CI 0.6-57.9%]), but there were no significant differences between primary care 49.4% [95% CI 23.7-75.4%]) vs hospitals (33.5% [95%CI 18.1-53.4%]), Java (31.4% [95%CI 18.8-47.6%]) vs outside of Java  and no contraindication/allergy label . Possible small-study effects were found for indication and duration . Subgroup analysis showed higher appropriateness of duration in hospitals (80.0% [95%CI 66.0-89.2%]) than primary care (34.5% [95%CI 4.3-86.1%]), and in adults , and higher appropriateness of drug choice, dosing, and overall appropriate use outside of Java  –although the latter differences were not statistically significant. There were no significant differences for no contraindication/allergy label, indication, dosing frequency, or administration route .Based on reference guidelines, most individual indicators of appropriateness scored excellent (>80%), except for duration (65.8% [95%CI 38.6-85.5%]) B and ove,,,,There were 13 reports that reported data on the effect of AMS interventions in hospitals (11 reports),,89,Studies that evaluated bundled interventions (5 reports) reported favourable effects on antibiotic consumption, prescribing appropriateness, guideline compliance, blood culture sampling, HAI rates, hand hygiene compliance, and mortality, although the authors of one study concluded that the multifaceted intervention had limited success, with an important drawback being the absence of adequate microbiological diagnostics.,,,,,,,,89,Studies that evaluated the implementation of antibiotic prescribing guidelines or clinical pathway (7 reports) reported mixed effects on antibiotic consumption and favourable effects on prescribing appropriateness.The one study that evaluated antibiotic restriction with pre-approval found that consumption of restricted antibiotics decreased and of unrestricted narrow-spectrum antibiotics increased.There were 25 reports that reported data on knowledge, attitudes, and perceptions among communities (consumers) (22),,,,96,,,,,,,96,,,,,,,,,,,,,,,,,,Among community respondents, there was a substantial lack of AMR awareness (10 reports) and knowledge about antibiotics (16), with wide variations between communities; overall, 23–26% did not know that antibiotics treated bacterial infections and 58-74% stated that antibiotics can cure viral infections.Among health care providers, antibiotic dispensing without prescription was the most important theme reported with conflicting findings. A survey among 250 community pharmacists in Yogyakarta (Java), 68% reported that they would dispense antibiotics without prescription,This systematic review represents a first attempt of an evidence synthesis of human antibiotic use in Indonesia, spanning the past 20 years. The evidence collected in this Review comes from a range of health care and community settings, including hospitals, primary care, pharmacies and communities, and includes a range of interventions targeting different types of health providers and consumers. The rising number of scientific reports published in the most recent years reflects the increasing momentum of AMR on the national health agenda. Nonetheless, the evidence base is uneven with hospital and urban contexts over-represented, and informal and formal private health providers, who play a major role in antibiotic distribution, particularly underrepresented.Based on our review, most of the antibiotics listed in the top-15 most consumed antibiotics were beta-lactams, especially cephalosporins and penicillins. Among adult hospital inpatients , ceftriaxone and levofloxacin (both Watch) and ampicillin (Access) were the most consumed, and consumption was highest in the recent five years, and outside of Java. Available data among primary care outpatients were limited , with amoxicillin, cefadroxil (both Access), and ciprofloxacin (Watch) being the most consumed antibiotics. According to national pharmaceutical sales data (2000-2015), antibiotic consumption increases were largely driven by the major classes broad-spectrum penicillins (2.6-fold), fluoroquinolones (7.1-fold), and cephalosporins (5.1-fold).,By comparison, the WHO Report on Surveillance of Antibiotic Consumption 2016-2018, representing 2015 data from 65 countries, including mostly high-income countries and no countries in Southeast Asia, found wide intra- and interregional variation in the total amount of antibiotics and the choice of antibiotics consumed,,,In Indonesia, among the studied populations, appropriateness of antibiotic prescribing was found to be poor overall (35.3%), 49.4% in primary care versus 33.5% in hospitals, despite nationwide implementation of hospital AMS programmes during the past five years.,,,Reports from high-income settings have shown that AMS can optimise the use of antimicrobials, improve patient outcomes, reduce AMR and health-care-associated infections, and save health-care costs amongst others.The few AMS intervention studies conducted to date reported clear benefits from implementing bundled interventions combining antibiotic prescribing guidelines, trainings, review and feedback, restriction with pre-approval, among others. These findings demonstrate that AMS interventions are feasible in the local context and that there is considerable potential for reducing antibiotic consumption, particularly of restricted antibiotics, improving prescribing appropriateness, and reducing prescriptions without indication. However, the interventions evaluated to date were mostly single-centre and short-term (<1 year), and data are lacking about the sustained benefits of AMS programmes in the Indonesian context.,147Previous evidence has shown that given the varying priorities and contextual issues in LMICs, such as health system processes, patient demands, varying cultures of care, availability of universal access to quality antimicrobials, laboratory infrastructure and surveillance systems, multipronged interventions combining different restrictive and enabling strategies are most likely to be effective.Key themes identified from perception surveys were a substantial lack of AMR awareness and knowledge about antibiotics, particularly among the poor and lower educated, widespread antibiotic self-medication without prescription, and over-the-counter non-prescription antibiotic dispensing in community pharmacies −although representative data are lacking to quantify these issues. A recent mixed-method study in drug outlets in urban (West Java) and rural  settings in Indonesia reported antibiotic dispensing without prescription in 69% of simulated-patient visits, with non-prescription antibiotic sales being driven by strong patient demand, unqualified drug sellers dispensing medicines, business interests, and weak enforcement of regulations.The data included in this Review highlighted several critical evidence gaps. First, there were important limitations in data heterogeneity and study methodology, study-level confounding, and publications were predominantly from Java Island, which limited our ability to draw firm conclusions on the contemporary nationwide antibiotic use situation in Indonesia. This is especially relevant given the substantial within-country variations in access to quality health care,,Progress in implementing Indonesia's National Action Plan on AMR to date includes strengthened national capacities for microbiological laboratories and surveillance,In conclusion, this Review can be a guiding tool for policy-makers and academics as it summarizes the state of antibiotic use in humans in Indonesia over the past 20 years, and highlights important areas where critical information is lacking. There are critical evidence gaps on antibiotic use in the informal and formal private health care sectors as well as geographic areas outside of Java Island, and what are health system drivers of antibiotic use. There is a need to strengthen the local research base to develop context-specific sustainable AMS models that consider country-specific socio-cultural circumstances. Optimisation of antimicrobial use, based on robust surveillance data and feasible interventions, should be a priority of the national agenda for universal health coverage.RLH conceptualised the study. RLH and RL obtained the funding. RL, PD and RLH designed the study protocol and data extraction instrument. PD, GL, MM, and MA collected and verified the data, overseen by RL and RLH. RL, GL and RLH performed the data analysis and had full access to all study data. RL, GL, PD, and RLH drafted the paper, with critical inputs from EJN, RS, AK and HRvD. All authors had full access to all the data in the study, critically revised the manuscript, accept responsibility to submit for publication, and gave approval for the final version to be published.No additional data are available.AK serves as the current Chair of the National AMR Committee (KPRA). HRVD serves as an Executive Board Member of The Surveillance and Epidemiology of Drug-resistant Infections Consortium (SEDRIC). The other authors declare no competing interests.


Critically ill patients suffering from severe infections are prone to pathophysiological pharmacokinetic changes that are frequently associated with inadequate antibiotic serum concentrations. Minimum inhibitory concentrations (MICs) of the causative pathogens tend to be higher in intensive care units. Both pharmacokinetic changes and high antibiotic resistance likely jeopardize the efficacy of treatment. The use of extracorporeal circulation devices to support hemodynamic, respiratory, or renal failure enables pharmacokinetic changes and makes it even more difficult to achieve an adequate antibiotic dose. Besides a clinical response, antibiotic pharmacokinetic optimization is important to reduce the selection of strains resistant to common antibiotics. In this review, we summarize the present knowledge regarding pharmacokinetic changes in critically ill patients and we discuss the effects of extra-corporeal devices on antibiotic treatment together with potential solutions. Serious infections are both the cause and consequence of critical conditions in intensive care units (ICUs). Once an infection is diagnosed, the appropriate (by antibiogram) and adequate (by pharmacokinetic and pharmacodynamic parameters (Pk/Pd)) administration of antibiotics is the primary intervention that the attending physician can use to improve patient prognosis . In critThe use of extracorporeal circuits to support or replace dysfunctional organs may further change Pk properties, making antibiotic treatment failure more likely.In this article, we review the pathophysiological changes that affect the pharmacokinetics (Pk) of antibiotics in critically ill patients, the effect that the use of extracorporeal circulation can have on drugs, and how to achieve Pk/Pd objectives.The most common Pk changes in critically ill patients are an increased antibiotic-free fraction resulting from hypoalbuminemia, an increased volume of distribution (Vd), and liver and kidney dysfunction, which either alter renal clearance or cause acute renal failure and antibiotic accumulation . Based oCurrently, adjusting dose regimens through the therapeutic drug monitoring (TDM) of plasma concentrations has become increasingly recommended, being considered an essential element in the management of septic patients ,9,10,11.Critically ill patients may require renal replacement therapy (RRT) support and a therapeutic adjustment is essential to avoid treatment failure, toxicity, or antibiotic drug resistance. In recent years, many patients undergoing RRT did not achieve therapeutic goals at standard doses . Among tIntermittent hemodialysis results in a temporary reduction in plasma levels of large Vd drugs, which is followed by a post-treatment “rebound.” Meanwhile, in continuous RRT (CRRT), clearance and redistribution equilibrium is commonly established .The three main modalities of CRRT include hemofiltration (CVVH), hemodialysis (CVVHD), and hemodiafiltration (CVVHDF), based on convection, diffusion, or both, respectively. Clearance efficiency is higher in CVVHDF, followed by CVVHD, and finally, CVVH ,43. GlomThe membrane type  and membrane surface area can also impact antibiotic CL. The membranes used for intermittent hemodialysis usually have small pores and do not allow the removal of molecules larger than 500 daltons (Da). During CRRT, large pores increase the size of the dialyzed molecules (>1000 Da). In general, the effect of adhesion to the membrane is negligible for most antibiotics. However, some studies describe a decline in serum concentrations for piperacillin, amikacin, or levofloxacin ,45.Another CRRT factor that plays an important role in the CL is the prescribed flow ,46. VariThe primary patient-related factors that can increase total CL in patients with CRRT include hypoalbuminemia, increased hepatic and biliary metabolism, and residual diuresis. One study also found a relationship between hematocrit and the efficiency of the drug transfer through the filter . PatientOn the other hand, it is essential to take into account the Pk characteristics of the drugs to assess the measure through which they will be cleared by RRT. In general, molecules with high molecular weight, a high binding rate to plasma proteins (>80%), lipophilic antibiotics, high Vd (>1–2 L/kg), and nonrenal clearance antibiotics, will have low or no elimination through the hemofilter . NeverthFinally, the interaction between the drug and the electrical charges of the dialysis membrane is described by the Gibbs–Donnan effect, in which anionic proteins present in the blood, such as albumin, tend to retain cationic molecules (aminoglycosides and levofloxacin), while facilitating the passage of anionic drugs  . HoweverThe sieving coefficient (SC), which is a specific parameter for each antibiotic for a given membrane, has been used to determine the CL in the RRT. The value of the SC goes from 1, which indicates a high clearance in RRT, to 0, which indicates no RRT clearance . DiffereIn clinical practice, there is a wide heterogeneity in the CRRT dose, blood and dialysate flow, types of filters and dialysis, and the surface membranes selected. Therefore, antibiotic dose optimization is highly challenging. Some recommendations have been published, but not all of them have been validated in clinical practice, nor do they consider all of the factors that may affect CRRT . In geneThere is a high risk of infection during extracorporeal membrane oxygenation (ECMO), which is associated with high mortality (up to 50% in some publications) . TherefoECMO support can influence the Pk and, therefore, the achievement of the Pk/Pd target. The main changes include variability in the elimination of the drug  and an increase in the Vd resulting from hemodilution  or sequestration of the drug in the circuit  . The intRenal and hepatic CL appears to decrease in ECMO patients because of reduced organ perfusion, although the initial hyperdynamic state of the critically ill patient with intense fluid therapy and vasoactive agents could increase the initial CL .In recent years, there have been efforts to determine the variations in some drugs in patients with ECMO; however, many studies have not been able to optimize treatment posology for these patients. Furthermore, many ECMO patients are also treated with RRT, which suggests the importance of TDM ,56,59. HIn recent decades, antibiotic therapeutic drug monitoring (TDM) has evolved from toxicity prevention of drugs with a narrow therapeutic index to an essential tool to improve the response to antibacterial treatment and prevent the emergence of resistance. There is now a strong rationale to individualize antibiotic dosing in critically ill patients with the aid of TDM ,63, beinSeveral studies have shown that the application of TDM leads to improvements in Pk/Pd achievement, leading to improved clinical outcomes for patients ,65. HoweOptimization of Pk/Pd parameters to minimize antibiotic resistance has not received sufficient attention in clinical practice. Pharmacokinetic goals are generally focused on maximizing clinical and microbiological outcomes, without considering resistance suppression. Nevertheless, given the progressive increase in resistance observed at the usual doses for most antibiotics, clinical data are needed to define thresholds that can minimize the emergence of resistance without compromising patient safety.Acquired antibiotic resistance mechanisms can be divided into four main categories: modifying the antibiotic target , limiting uptake (decreased numbers of porins), antibiotic inactivation (β-lactamases) and active drug efflux pumps. Gram-negative bacteria can use all four main mechanisms, whereas gram-positive bacteria less commonly use limiting the uptake of a drug, and certain types of drug efflux mechanisms are not usable. Clinical and in vitro studies have shown that the low antibiotic dose and treatment duration can influence the selection of antibiotic-resistant mutants . HoweverThere is poor knowledge of the optimal dosing strategies to treat bacterial infections while simultaneously preventing the selection and emergence of resistance. It is known that a subpopulation of resistant bacteria often exists and can be selected at certain drug concentrations, leading to a regrowth during treatment. Low antibiotic concentrations can select for low-level resistance, which could have a major effect on the emergence of high-level antibiotic resistance . On the The Pk/Pd index relates antibiotic exposure to the antibiotic susceptibility of an infecting pathogen, in which susceptibility is described as the MIC, thus providing a dosing target. However, in vitro studies simulating current antibiotic dosing highlight the limited ability to suppress the emergence of antibiotic-resistant bacteria . BecauseThe mutant prevention concentration (MPC), which is defined as the lowest concentration that blocks the emergence of first-step resistant mutants in a large susceptible population , has beePreclinical studies have indicated that exposures of Cmin/MIC ≥ 6–8 suppress the emergence of resistance of highly susceptible isolates ,75. OtheFluoroquinolone use is strongly associated with the development of resistance. Some in vitro studies have suggested that the index associated with the suppression of resistance is an AUC/MIC ratio > 200 . HoweverThe Pk/Pd target for preventing the emergence of resistance depends on the specific molecule. With a once-daily administration, a lower dose is necessary to suppress re-sistance compared with a two-dose a day schedule (Cmax/MIC ratio 13 vs. Cmax/MIC ratio 20) . In vitrThe Pk/Pd parameter that is associated with a lower risk of resistance is the AUC/MIC ratio. In an in vitro model, an AUC 0–24/MIC ratio > 3136 was adequate for the suppression of resistance development in E. coli with a MIC of 1 mg/L. and a daily dose of 24 g was needed to achieve the Pk/Pd target . HoweverA. baumannii developed resistance even at a colistin exposure > 10 mg/L, which is a much higher concentration compared with the usual clinical dose [The Pk/Pd parameter that best describes the success of therapy and probability of suppression of the emergence of resistance with colistin is the AUC/MIC ratio. In a clinical setting, when a 9 M IU loading dose was given, followed by 4.5 MIU/8 h, no resistance emerged in 127 ICU patients . Howevercal dose . BecauseFew studies have described the linezolid Pk/Pd ratios required to prevent the emergence of resistance. An AUC/MIC > 124 was shown to suppress resistance against clinical MRSA isolates. Another study indicated that the dose required to achieve a linezolid steady-state concentration approximately equivalent to the pathogen MIC may promote the emergence of resistance . These dS. aureus dap-tomycin resistance emergence in a dynamic one-compartment in vitro infection model [A total AUC/MIC > 200 has been associated with an avoidance of on model . A dose on model , possiblon model .S. aureus in vitro infection model [Various studies have identified vancomycin AUC/MIC > 200 as sufficient to suppress resistance emergence in an on model , suggeston model  demonstron model .In recent years, artificial intelligence and machine learning techniques have emerged as new tools to predict the risk, and even to prevent, colonization and infection by MDR bacteria as well as the development of resistance associated with the use of antibiotics ,95. ThesThere are some examples in the literature in which machine learning has been used to predict Pk data ,97. ThesBig data analysis for Pk/Pd optimization has also received significant attention recently ,102. CurDespite the high variability in antibiotic concentrations and the risk of underdosing in critically ill patients, most patients continue to receive standard dosing regardless of the underlying disease or existing comorbidities. Although therapeutic antibiotic monitoring has grown significantly in many hospitals, it has produced mixed results and has major downsides, including the time consumed until dose optimization following the initiation of antibiotic therapy.The development of real time closed-loop decision support systems at the bedside may be a major step forward , even wiThe complexity of the critically ill patient affects the Pk/Pd of antibiotics and can lead to an erroneous dosing and a poor prognosis. Currently, specialists in the treatment of infection in critically ill patients must be aware of all aspects concerning the patient, the infectious foci, the microorganism, and the drug involved in the episode, to properly modify the antibiotic dosage regimen. Special attention should be paid to the study of the notorious effects that extracorporeal circulation systems have on the Pk of most antibiotics. Because of the consequences of the progressive increase in the rate of multidrug-resistant strains, pharmacokinetic optimization must be applied to avoid the emergence of resistant strains. In the near future, artificial intelligence and ML techniques may enable the optimization of antibiotic treatment and improve overall patient prognosis.


Accidental falls represent a major cause of fatal injuries for construction workers. Failure to seek medical attention after a fall can significantly increase the risk of death for construction workers. Wearable sensors, computer vision, and manual techniques are common modalities for detecting worker falls in the literature. However, they are severely constrained by issues such as cost, lighting, background, clutter, and privacy. To address the problems associated with the existing proposed methods, a new method has been conceived to identify construction worker falls by analyzing the CSI signals extracted from commercial Wi-Fi routers. In this research context, our study aimed to investigate the potential of using Channel State Information (CSI) to identify falls among construction workers. To achieve the aim of this study, CSI data corresponding to 360 sets of activities were collected from six construction workers on real construction sites. The results indicate that (1) the behavior of construction workers is highly correlated with the magnitude of CSI, even in real construction sites, and (2) the CSI-based method for identifying construction worker falls has an accuracy of 99% and can also accurately distinguish between falls and fall-like actions. The present study makes a significant contribution to the field by demonstrating the feasibility of utilizing low-cost Wi-Fi routers for the continuous monitoring of fall incidents among construction workers. To the best of our knowledge, this is the first investigation to address the issue of fall detection using commercial Wi-Fi devices in real-world construction environments. Considering the dynamic nature of construction sites, the new method developed in this study helps to detect falls at construction sites automatically and helps injured construction workers to seek medical attention on time. Construction workers are often subjected to physically demanding work, and the construction industry records a significant number of workplace injuries, making it the most perilous occupation in the United States . Falls aPrevious studies aiming to mitigate the hazards associated with fall accidents mainly focus on (1) using accident reports to analyze and avoid the main causes of falls ,12,13 orGiven the limitations of previous studies, there is an increasing demand for automated, non-invasive, and continuous monitoring methods that can effectively monitor falls among construction workers. The Wi-Fi-based approach is an emerging solution for fall recognition that addresses the above limitations . ChannelThis paper is structured as follows: Falls on construction sites are a common cause of accidents for workers , which aOver the years, construction companies have tried to use adequate safety training and the intervention of safety managers to reduce the likelihood of worker accidents ,41. HoweRecently, many studies have demonstrated the effectiveness of wearable technology for worker fall monitoring. Wearable technology can collect a large amount of data from recognized physical responses and thus be used to monitor physical changes while working in the workplace. These devices include accelerometers, gyroscopes, and other technologies that provide solutions for measuring falls ,43,44. TSimilarly, wearable insole pressure systems are used to measure plantar pressure and ground reaction forces to extract information for fall detection in construction workers . Only ifComputer-vision-based fall detection relies on cameras mounted at specific locations to capture images or video sequences for activity recognition and classification. The fall activity is separated from other events using an activity classification algorithm. The latest research based on infrared and depth cameras has expanded their range of applications and has demonstrated their high recognition accuracy ,25,51. HActivity recognition technology using wireless signals is a non-intrusive and privacy-protective method ,53. BaseThe transmission of a signal by a transmitter undergoes a series of attenuations and reflections before it reaches the receiver, and this variation is referred to as the Channel State Information (CSI). CSI captures the path of a wireless signal at a specific carrier frequency from the transmitting antenna to the receiving antenna. The basis of CSI-based activity recognition lies in the fact that the amplitude and phase of the CSI signal will deviate from their normal measurements when an object or a person moves between the transmitter and the receiver antenna, thereby inducing movement-related perturbations.We can measure the value of CSI propagated by the transmitter and receiver for behavior recognition purposes. As shown in d and h are the propagation distance and indoor space height, respectively; and Δ denotes the approximate amount of signal disturbance caused by the presence of personnel.The formula of the overall propagation model is as follows:CSI describes the quality change in the environmental reflection experienced by the signal during the propagation process and is based on the evaluation matrix of the signal propagation quality at the signal-receiving end in Orthogonal Frequency Division Multiplexing (OFDM) technology . The phyAs described in The collection of CSI data is a crucial step in the process of fall detection in construction sites. Channel State Information (CSI) is a wireless communication concept that pertains to information about the characteristics of the wireless channel between a transmitter and a receiver. It encompasses crucial information, including the signal’s amplitude, phase, and frequency response, which can be utilized to extract various signal features. CSI is particularly sensitive to movement and location changes of objects and people in the environment. The foundation of CSI-based activity recognition is grounded in the observation that the amplitude and phase of the CSI signal will undergo alterations from their typical measurements when an object or person moves between the transmitter and receiver antenna. This causes movement-related perturbations, which can be detected and utilized to recognize various activities.The widespread usage of commercial routers in these environments makes them an attractive choice for data collection. Two popular tools used for CSI data acquisition are the Linux 802.11n CSI Tool and the Atheros CSI Tool. The Linux 802.11n CSI Tool, although effective, requires outdated hardware and often necessitates modifications to the computer being used. As a result, the Atheros CSI Tool is preferred, as it is an open-source tool that enables the extraction of wireless communication data from Wi-Fi network cards. This information includes CSI, the received packet payload, and other relevant details, such as the Timestamp, RSSI per antenna, and Data Rate.The receivers and transmitters are two Wi-Fi routers with built-in Atheros AR9580 NICs equipped with OpenWrt systems. In this study, the injector monitor mode was used to send and receive CSI data. The monitor mode allows the modulation of the transmission rate, the number of packets sent, the number of transmitting antennae, and the short/long guard interval. It is essential to invoke the monitor mode, which allows for more standard CSI data to be obtained for subsequent model training. Two laptops with Intel Core i5 series processors, Windows 10, Xshell6, and Winscp were selected as the processing terminals to extract the received CSI data.This study represents a significant advancement in prior research through the design of a system that incorporates Tx-Rx communication to calculate the Channel State Information (CSI) and collect data for analysis. The system operates by having the transmitter continuously transmit Wi-Fi packets while the receiver receives the data and computes the CSI. In order to address the limitation of the router’s limited data storage capacity, the system has been optimized through the following measures: (1) the transmitter transmits data to the receiver, which then calculates the CSI; (2) the raw CSI data are extracted from the receiver by the user’s laptop and processed, saved, and visualized using MATLAB R2021a. The procedure for obtaining CSI data is illustrated in CSI data consist of two components: phase and amplitude. During the subsequent data analysis in this paper, we use only amplitude information for fall identification. As the transmit power and rate vary, unpredictable impulsive noise is generated between the transmitter and receiver. The raw CSI data received have a lot of noisy information that is irrelevant to the worker’s actions. To avoid losing any possible data information, the pre-processing of CSI data in this paper is limited to the removal of obvious noise. In this study, a median filter was introduced for noise reduction. The change in the amplitude of CSI data before and after noise reduction is shown in Previous studies have investigated the application of various machine-learning algorithms for fall recognition, including deep recurrent neural networks (RNNs), support vector machines (SVMs), and logistic regression algorithms. The selection of a particular algorithm is based on its ability to analyze and classify the collected CSI data, leading to accurate fall detection. The action recognition process is akin to speech recognition. The utilization of Long Short-Term Memory (LSTM) can mitigate the potential for gradient disappearance or explosion during neural network training and result in high recognition accuracy .Fall behavior often exhibits both pre-fall features, such as body tilt, and post-fall features, such as body smoothness. To consider both past and future information, bidirectional LSTM (BLSTM) is used for activity recognition in this paper. BLSTM provides a comprehensive understanding of both pre-fall and post-fall features. The use of LSTM offers two advantages. Firstly, LSTM is capable of automatically extracting features, obviating the need for pre-processing data, which meets our expectations. Secondly, LSTM preserves the temporal state information of the activity, enabling differentiation between similar activities such as “lie down” and “fall”. Although these activities exhibit similar velocity characteristics, they have distinctive pre-states and post-states. The memory capacity of LSTM allows for the identification of these activities.The experiment was carried out using two Wi-Fi routers with Atheros 9580 NIC chips and two laptops. One laptop served as a transmitter, and the other acted as a receiver; both were connected to a single network. Data are sent and received through a local area network between the transmitter and receiver before being sent to the computer performing the processing. The transmission rate must be high enough (around 1 kHz) to record the instant of a recently completed fall for the CSI to demonstrate substantial changes brought on by movement. This is because when the sampling rate is around 50 Hz, we observe serious degradation in the performance of the classification method, even though it runs much faster. The cost of denoising and feature extraction increases when the sampling rate is increased because more samples are taken. Accurate recognition may not be improved by increasing the sample rate. Therefore, a good compromise between the computational cost and accuracy can be obtained by choosing a suitable sampling rate (approx. 1 kHz). In total, 1000 Wi-Fi packets are delivered every second, and the Atheros CSI Tool extracts the CSI from the Wi-Fi signal. In the experiment, two receiving antennae and one broadcasting antenna were set up, making a total of two communication lines. Personnel operation information was collected at a 2.4 GHz center frequency.To collect the most realistic experimental data on the fall behavior of construction workers, the experiment was set up on an actual construction site. The distance between the transmitter and receiver was set at 4.0 m, and the height was set at 0.5 m for line-of-sight circumstances . The transmitter and receiver were positioned 1 m above the ground to provide a clear signal path. The perceived real-life experimental scenario and its planar structure are shown in Six construction workers who were present at the site provided the CSI data for this experiment (two carpenters and four electricians). Traditional CSI-based behavior recognition typically focuses on undisturbed laboratory environments, but actual construction sites are subject to numerous disruptive factors, such as construction noise, vibrations, and irregular building walls, which can affect the propagation of CSI. To demonstrate the experiment’s rigor, the test site was located in a wastewater treatment facility renovation project in Chengdu, Sichuan Province, which included an operating tower crane and excavator. Collecting data in this way realistically captures CSI fluctuations due to background factors. Data collection began on 4 September 2022. Four men and two women, ages 20 to 50, with five to sixteen years of work experience in the construction industry, made up the participants. None of the individuals reported having any clinical issues that would limit their capacity for everyday activities on a physical or mental level. The six construction workers’ demographic details and the number of groups for which data were gathered are shown in The various characteristics of different individuals can increase the variety of training samples and make it easier to identify various worker falls using artificial neural networks. There may be differences in the detection rates among workers based on their height, weight, and gender. The accuracy of CSI-based fall detection depends on the signal strength and quality of the received Wi-Fi signals, which may be affected by the worker’s body composition and orientation. For instance, taller or heavier workers may cause more signal attenuation due to the increased number of obstacles and absorption of the Wi-Fi signal. Similarly, the orientation of the worker’s body may also affect the signal. Gender may also play a role in the accuracy of fall detection since men and women tend to have different body compositions and postures, leading to differences in signal attenuation and variations in the received Wi-Fi signal.These factors can be mitigated by increasing the sample size. For example, collecting data from more workers can reduce the impact of individual worker characteristics, such as height, weight, and gender, on the accuracy of the test. This approach can help in obtaining more reliable results and enhancing the generalizability of the findings. There is no clear rule for how many samples are required to train a neural network; instead, it is an iterative process. The quantity of data required for the dataset depends on the difficulty of the activity and the technique used. A total of 60 sets of experiments were conducted by each of the six construction employees who were given the task of participating in the study. These activities were “LieDown”, “FallDown”, “Jump”, “Sit”, “StandUp”, and “Walking”. The details of these activities can be seen in CSI data for actions other than falls were collected to demonstrate that a CSI-based fall recognition model can accurately distinguish between falls and fall-like behaviors. Only predefined actions were executed at intermediate intervals during the entire data acquisition process. More specifically, the worker was virtually steady at the start and finish of the data collection. The experiment was manually run, so there was always a chance that the times it took to start and end would vary slightly. Each worker performed each action ten times, with the duration of individual tasks set at approximately 15 to 25 s. The overall image was recorded at the same time as the data were collected, thus ensuring that the timestamps correspond to the data annotation at a later stage. A total of 360 data streams  were gathered for this study. Each action dataset contains 56 subcarriers, each containing approximately 20,000 samples. The relationship corresponding to the fall occurrence and the change in CSI signal amplitude is shown in The CSI amplitudes of the 56 subcarriers collected for the 6 actions as a function of time are shown in −4. One disadvantage is the lengthy training period associated with employing LSTM in this manner. However, one may also leverage GPUs and accelerate training by utilizing deep learning tools such as TensorFlow. The test may be completed quickly after LSTM has been trained. To assess the effectiveness of the classification model, we measured the precision, loss rate, and accuracy.The LSTM technique differs from traditional approaches in that it can directly extract CSI features without using PCA or STFT. The network receives 56 × 19,000 (feature samples) features as its input and outputs a probability for each of the six classes. Two hundred hidden units are picked, with just one hidden layer being taken into consideration. We utilized Stochastic Gradient Descent (SGD) for the numerical optimization of cross-entropy with a batch size of 200 and a learning rate of 1 × 10The CSI values for various activities vary, which affects the recognition accuracy. For each activity, we use a confusion matrix  to indicate how well our suggested classifier performed. The rows correspond to the predicted categories, while the columns correspond to the actual classes. The results in the confusion matrix  show an Activities that involve more prominent limb movements, such as “FallDown”, “Jump”, and “Walking”, exhibit higher recognition accuracy  for activity recognition in the literature can be attributed to the presence of errors, including Carrier Frequency Offset (CFO) and Sampling Frequency Offset (SFO). Nevertheless, these errors can be effectively mitigated by subtracting the phase information from neighboring antennae, resulting in the calculation of the phase difference. The phase difference is correlated with the Angle of Arrival (AOA); any variations in the target’s position lead to corresponding fluctuations in the AOA and, subsequently, the phase difference. The rapid and substantial motion of the target scatters the signal in a more randomized manner, leading to a more dynamic and rapid change in the AOA and phase difference. Utilizing these variations in phase difference and amplitude as features for activity classification through the implementation of a suitable machine-learning algorithm remains an area for future investigation.The focus of this work is on the use of CSI-based methods for fall detection on construction sites. However, finding the best location to install a Wi-Fi router to ensure good signal coverage and excellent detection performance is not easy. In the future, we plan to investigate the best locations to place the routers to optimize signal coverage and fall detection.The present study focused on the recognition of falls in a single construction worker. However, recognizing falls among multiple workers simultaneously presents a more complex and intriguing challenge. The deployment of multiple receivers may offer an added advantage in accurately differentiating between the activities of multiple individuals. Further investigation in this direction is an area for future study.This study investigated the potential of using CSI data from commercial Wi-Fi routers to monitor construction workers’ falls at construction sites. To achieve this, data were collected from six construction workers in a fall experiment with 360 sets of activities. The results showed that (1) there was a significant correlation between changes in the CSI amplitude and construction workers’ fall behavior and (2) CSI signals extracted from commercial routers could accurately discriminate between falls and fall-like movements, identifying fall movements with 99% accuracy. The main contribution of this study is to demonstrate the feasibility of using commercial Wi-Fi routers for construction worker fall monitoring. This research is the first attempt to use the new CSI data for the fall identification of construction workers on construction sites. The objective and continuous fall monitoring of construction workers, in a non-invasive manner, is important due to the complexity and dynamic nature of their behavior. This study will enable timely access to medical care for injured workers and improve the overall safety of the construction site.This study also suggests future research directions for using CSI data for fall detection on construction sites. One area is utilizing the phase information of CSI in addition to the magnitude of activity recognition. The study also highlights the need to determine the optimal placement location for Wi-Fi routers to ensure good signal coverage and excellent detection performance. Simultaneously recognizing falls among multiple workers is another area for future investigation, which may involve deploying multiple receivers.