Patterns of Admission in Intensive Care Unit of Tertiary Care Hospital

Background: It is well known that early appropriate referrals of critically ill patients to an ICU can significantly reduce the mortality. At the same time, improper admissions to ICU limits bed availability that adversely affects ICU functioning. Objective: To determine the patterns of admissions and outcome in Medical and Surgical Intensive care Units.Material & Methods: A retrospective review of all patients admitted in medical and surgical ICU of Pakistan Institute of Medical Sciences, Islamabad from 2014 to 2016 was done. Data was collected from admission registers and patients’ files. Data was analyzed using SPSS software version 20.0. Chi-square test was applied and P-value < 0.05 was considered significant.Results: Study recruited data of 1652 patients admitted to intensive care unit of PIMS hospital. There were 769(46.5%) males and 883(53.5%) females. Among all the patients, 503(30.4%) were admitted to medical intensive care unit while 1149(69.6%) were admitted to surgical intensive care Unit. 684(41.4%) had undergone mortality while 968(58.6%) remained alive. Overall mean length of hospital stay was 7.4±4.1SD, mean length of mechanical ventilation 4.1±2.1SD and mean length of supplemental ventilation was 1.5±0.11SD. Acute abdomen (13.1%) and head injuries (12%) were most common causes for admission in ICU. Statistically significant association between years (2014, 2015 & 2016) and disease (p=0.000), years and mortality (p=0.000), years and age (p=0.000), intensive care unit and gender (p=0.01), intensive care unit and age (p=0.02) was reported.Conclusion: Acute abdomen and Head injuries had highest number of admissions in Medical and Surgical intensive care unit of PIMS hospital. Developing a well-equipped trauma ICU with adequately trained staff will help improve the outcome of patients

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

Patterns of Admission in Intensive Care Unit of Tertiary Care Hospital

Background: It is well known that early appropriate referrals of critically ill patients to an ICU can significantly reduce the mortality. At the same time, improper admissions to ICU limits bed availability that adversely affects ICU functioning. Objective: To determine the patterns of admissions and outcome in Medical and Surgical Intensive care Units.Material &amp; Methods: A retrospective review of all patients admitted in medical and surgical ICU of Pakistan Institute of Medical Sciences, Islamabad from 2014 to 2016 was done. Data was collected from admission registers and patients’ files. Data was analyzed using SPSS software version 20.0. Chi-square test was applied and P-value &lt; 0.05 was considered significant.Results: Study recruited data of 1652 patients admitted to intensive care unit of PIMS hospital. There were 769(46.5%) males and 883(53.5%) females. Among all the patients, 503(30.4%) were admitted to medical intensive care unit while 1149(69.6%) were admitted to surgical intensive care Unit. 684(41.4%) had undergone mortality while 968(58.6%) remained alive. Overall mean length of hospital stay was 7.4±4.1SD, mean length of mechanical ventilation 4.1±2.1SD and mean length of supplemental ventilation was 1.5±0.11SD. Acute abdomen (13.1%) and head injuries (12%) were most common causes for admission in ICU. Statistically significant association between years (2014, 2015 &amp; 2016) and disease (p=0.000), years and mortality (p=0.000), years and age (p=0.000), intensive care unit and gender (p=0.01), intensive care unit and age (p=0.02) was reported.Conclusion: Acute abdomen and Head injuries had highest number of admissions in Medical and Surgical intensive care unit of PIMS hospital. Developing a well-equipped trauma ICU with adequately trained staff will help improve the outcome of patients

Developing a Diagnostic Multivariable Prediction Model for Urinary Tract Cancer in Patients Referred with Haematuria: Results from the IDENTIFY Collaborative Study

377siBackground: Patient factors associated with urinary tract cancer can be used to risk stratify patients referred with haematuria, prioritising those with a higher risk of cancer for prompt investigation. Objective: To develop a prediction model for urinary tract cancer in patients referred with haematuria. Design, setting, and participants: A prospective observational study was conducted in 10 282 patients from 110 hospitals across 26 countries, aged ≥16 yr and referred to secondary care with haematuria. Patients with a known or previous urological malignancy were excluded. Outcome measurements and statistical analysis: The primary outcomes were the presence or absence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC], and renal cancer). Mixed-effect multivariable logistic regression was performed with site and country as random effects and clinically important patient-level candidate predictors, chosen a priori, as fixed effects. Predictors were selected primarily using clinical reasoning, in addition to backward stepwise selection. Calibration and discrimination were calculated, and bootstrap validation was performed to calculate optimism. Results and limitations: The unadjusted prevalence was 17.2% (n = 1763) for bladder cancer, 1.20% (n = 123) for UTUC, and 1.00% (n = 103) for renal cancer. The final model included predictors of increased risk (visible haematuria, age, smoking history, male sex, and family history) and reduced risk (previous haematuria investigations, urinary tract infection, dysuria/suprapubic pain, anticoagulation, catheter use, and previous pelvic radiotherapy). The area under the receiver operating characteristic curve of the final model was 0.86 (95% confidence interval 0.85-0.87). The model is limited to patients without previous urological malignancy. Conclusions: This cancer prediction model is the first to consider established and novel urinary tract cancer diagnostic markers. It can be used in secondary care for risk stratifying patients and aid the clinician's decision-making process in prioritising patients for investigation. Patient summary: We have developed a tool that uses a person's characteristics to determine the risk of cancer if that person develops blood in the urine (haematuria). This can be used to help prioritise patients for further investigation.noneopenKhadhouri, Sinan; Gallagher, Kevin M.; MacKenzie, Kenneth R.; Shah, Taimur T.; Gao, Chuanyu; Moore, Sacha; Zimmermann, Eleanor F.; Edison, Eric; Jefferies, Matthew; Nambiar, Arjun; Anbarasan, Thineskrishna; Mannas, Miles P.; Lee, Taeweon; Marra, Giancarlo; Gómez Rivas, Juan; Marcq, Gautier; Assmus, Mark A.; Uçar, Taha; Claps, Francesco; Boltri, Matteo; La Montagna, Giuseppe; Burnhope, Tara; Nkwam, Nkwam; Austin, Tomas; Boxall, Nicholas E.; Downey, Alison P.; Sukhu, Troy A.; Antón-Juanilla, Marta; Rai, Sonpreet; Chin, Yew-Fung; Moore, Madeline; Drake, Tamsin; Green, James S.A.; Goulao, Beatriz; MacLennan, Graeme; Nielsen, Matthew; McGrath, John S.; Kasivisvanathan, Veeru; Chaudry, Aasem; Sharma, Abhishek; Bennett, Adam; Ahmad, Adnan; Abroaf, Ahmed; Suliman, Ahmed Musa; Lloyd, Aimee; McKay, Alastair; Wong, Albert; Silva, Alberto; Schneider, Alexandre; MacKay, Alison; Knight, Allen; Grigorakis, Alkiviadis; Bdesha, Amar; Nagle, Amy; Cebola, Ana; Dhanasekaran, Ananda Kumar; Kondža, Andraž; Barcelos, André; Galosi, Andrea Benedetto; Ebur, Andrea; Minervini, Andrea; Russell, Andrew; Webb, Andrew; de Jalón, Ángel García; Desai, Ankit; Czech, Anna Katarzyna; Mainwaring, Anna; Adimonye, Anthony; Das, Arighno; Figueiredo, Arnaldo; Villers, Arnauld; Leminski, Artur; Chippagiri, Arvinda; Lal, Asim Ahmed; Yıldırım, Asıf; Voulgaris, Athanasios Marios; Uzan, Audrey; Oo, Aye Moh Moh; Younis, Ayman; Zelhof, Bachar; Mukhtar, Bashir; Ayres, Ben; Challacombe, Ben; Sherwood, Benedict; Ristau, Benjamin; Lai, Billy; Nellensteijn, Brechtje; Schreiter, Brielle; Trombetta, Carlo; Dowling, Catherine; Hobbs, Catherine; Benitez, Cayo Augusto Estigarribia; Lebacle, Cédric; Ho, Cherrie Wing Yin; Ng, Chi-Fai; Mount, Chloe; Lam, Chon Meng; Blick, Chris; Brown, Christian; Gallegos, Christopher; Higgs, Claire; Browne, Clíodhna; McCann, Conor; Plaza Alonso, Cristina; Beder, Daniel; Cohen, Daniel; Gordon, Daniel; Wilby, Daniel; Gordon, Danny; Hrouda, David; Lau, David Hua Wu; Karsza, Dávid; Mak, David; Martin-Way, David; Suthaharan, Denula; Patel, Dhruv; Carrion, Diego M; Nyanhongo, Donald; Bass, Edward; Mains, Edward; Chau, Edwin; Canelon Castillo, Elba; Day, Elizabeth; Desouky, Elsayed; Gaines, Emily; Papworth, Emma; Yuruk, Emrah; Kilic, Enes; Dinneen, Eoin; Palagonia, Erika; Xylinas, Evanguelos; Khawaja, Faizan; Cimarra, Fernando; Bardet, Florian; Kum, Francesca; Peters, Francesca; Kovács, Gábor; Tanasescu, Geroge; Hellawell, Giles; Tasso, Giovanni; Lam, Gitte; La Montagna, Giuseppe; Pizzuto, Giuseppe; Lenart, Gordan; MacLennan, Graeme; Özgür, Günal; Bi, Hai; Lyons, Hannah; Warren, Hannah; Ahmed, Hashim; Simpson, Helen; Burden, Helena; Gresty, Helena; Rios Pita, Hernado; Clarke, Holly; Serag, Hosam; Kynaston, Howard; Crawford-Smith, Hugh; Mostafid, Hugh; Otaola-Arca, Hugo; Koo, Hui Fen; Ibrahim, Ibrahim; Ouzaid, Idir; Puche-Sanz, Ignacio; Tomašković, Igor; Tinay, Ilker; Sahibzada, Iqbal; Thangasamy, Isaac; Cadena, Iván Revelo; Irani, Jacques; Udzik, Jakub; Brittain, James; Catto, James; Green, James; Tweedle, James; Hernando, Jamie Borrego; Leask, Jamie; Kalsi, Jas; Frankel, Jason; Toniolo, Jason; Raman, Jay D.; Courcier, Jean; Kumaradeevan, Jeevan; Clark, Jennifer; Jones, Jennifer; Teoh, Jeremy Yuen-Chun; Iacovou, John; Kelly, John; Selph, John P.; Aning, Jonathan; Deeks, Jon; Cobley, Jonathan; Olivier, Jonathan; Maw, Jonny; Herranz-Yagüe, José Antonio; Nolazco, Jose Ignacio; Cózar-Olmo, Jose Manuel; Bagley, Joseph; Jelski, Joseph; Norris, Joseph; Testa, Joseph; Meeks, Joshua; Hernandez, Juan; Vásquez, Juan Luis; Randhawa, Karen; Dhera, Karishma; Gronostaj, Katarzyna; Houlton, Kathleen; Lehman, Kathleen; Gillams, Kathryn; Adasonla, Kelvin; Brown, Kevin; Murtagh, Kevin; Mistry, Kiki; Davenport, Kim; Kitamura, Kosuke; Derbyshire, Laura; Clarke, Laurence; Morton, Lawrie; Martinez, Levin; Goldsmith, Louise; Paramore, Louise; Cormier, Luc; Dell'Atti, Lucio; Simmons, Lucy; Martinez-Piñeiro, Luis; Rico, Luis; Chan, Luke; Forster, Luke; Ma, Lulin; Moore, Madeline; Gallego, Maria Camacho; Freire, Maria José; Emberton, Mark; Feneley, Mark; Antón-Juanilla, Marta; Rivero, Marta Viridiana Muñoz; Pirša, Matea; Tallè, Matteo; Crockett, Matthew; Liew, Matthew; Trail, Matthew; Peters, Max; Cooper, Meghan; Kulkarni, Meghana; Ager, Michael; He, Ming; Li, Mo; Omran Breish, Mohamed; Tarin, Mohamed; Aldiwani, Mohammed; Matanhelia, Mudit; Pasha, Muhammad; Akalın, Mustafa Kaan; Abdullah, Nasreen; Hale, Nathan; Gadiyar, Neha; Kocher, Neil; Bullock, Nicholas; Campain, Nicholas; Pavan, Nicola; Al-Ibraheem, Nihad; Bhatt, Nikita; Bedi, Nishant; Shrotri, Nitin; Lobo, Niyati; Balderas, Olga; Kouli, Omar; Capoun, Otakar; Oteo Manjavacas, Pablo; Gontero, Paolo; Mariappan, Paramananthan; Marchiñena, Patricio Garcia; Erotocritou, Paul; Sweeney, Paul; Planelles, Paula; Acher, Peter; Black, Peter C.; Osei-Bonsu, Peter K; Østergren, Peter; Smith, Peter; Willemse, Peter-Paul Michiel; Chlosta, Piotr L.; Ul Ain, Qurrat; Barratt, Rachel; Esler, Rachel; Khalid, Raihan; Hsu, Ray; Stamirowski, Remigiusz; Mangat, Reshma; Cruz, Ricardo; Ellis, Ricky; Adams, Robert; Hessell, Robert; Oomen, Robert J.A.; McConkey, Robert; Ritchie, Robert; Jarimba, Roberto; Chahal, Rohit; Andres, Rosado Mario; Hawkins, Rosalyn; David, Rotimi; Manecksha, Rustom P.; Agrawal, Sachin; Hamid, Syed Sami; Deem, Samuel; Goonewardene, Sanchia; Swami, Satchi Kuchibhotla; Hori, Satoshi; Khan, Shahid; Mohammud Inder, Shakeel; Sangaralingam, Shanthi; Marathe, Shekhar; Raveenthiran, Sheliyan; Horie, Shigeo; Sengupta, Shomik; Parson, Sian; Parker, Sidney; Hawlina, Simon; Williams, Simon; Mazzoli, Simone; Grzegorz Kata, Slawomir; Pinheiro Lopes, Sofia; Ramos, Sónia; Rai, Sonpreet; Rintoul-Hoad, Sophie; O'Meara, Sorcha; Morris, Steve; Turner, Stacey; Venturini, Stefano; Almpanis, Stephanos; Joniau, Steven; Jain, Sunjay; Mallett, Susan; Nikles, Sven; Shahzad, null; Yan, Sylvia; Lee, Taeweon; Uçar, Taha; Drake, Tamsin; Toma, Tarq; Cabañuz Plo, Teresa; Bonnin, Thierry; Muilwijk, Tim; Wollin, Tim; Chu, Timothy Shun Man; Appanna, Timson; Brophy, Tom; Ellul, Tom; Austin, Tomas; Smrkolj, Tomaž; Rowe, Tracey; Sukhu, Troy; Patel, Trushar; Garg, Tullika; Çaşkurlu, Turhan; Bele, Uros; Haroon, Usman; Crespo-Atín, Víctor; Parejo Cortes, Victor; Capapé Poves, Victoria; Gnanapragasam, Vincent; Gauhar, Vineet; During, Vinnie; Kumar, Vivek; Fiala, Vojtech; Mahmalji, Wasim; Lam, Wayne; Fung Chin, Yew; Filtekin, Yigit; Chyn Phan, Yih; Ibrahim, Youssed; Glaser, Zachary A; Abiddin, Zainal Adwin; Qin, Zijian; Zotter, Zsuzsanna; Zainuddin, ZulkifliKhadhouri, Sinan; Gallagher, Kevin M.; Mackenzie, Kenneth R.; Shah, Taimur T.; Gao, Chuanyu; Moore, Sacha; Zimmermann, Eleanor F.; Edison, Eric; Jefferies, Matthew; Nambiar, Arjun; Anbarasan, Thineskrishna; Mannas, Miles P.; Lee, Taeweon; Marra, Giancarlo; Gómez Rivas, Juan; Marcq, Gautier; Assmus, Mark A.; Uçar, Taha; Claps, Francesco; Boltri, Matteo; La Montagna, Giuseppe; Burnhope, Tara; Nkwam, Nkwam; Austin, Tomas; Boxall, Nicholas E.; Downey, Alison P.; Sukhu, Troy A.; Antón-Juanilla, Marta; Rai, Sonpreet; Chin, Yew-Fung; Moore, Madeline; Drake, Tamsin; Green, James S. A.; Goulao, Beatriz; Maclennan, Graeme; Nielsen, Matthew; Mcgrath, John S.; Kasivisvanathan, Veeru; Chaudry, Aasem; Sharma, Abhishek; Bennett, Adam; Ahmad, Adnan; Abroaf, Ahmed; Suliman, Ahmed Musa; Lloyd, Aimee; Mckay, Alastair; Wong, Albert; Silva, Alberto; Schneider, Alexandre; Mackay, Alison; Knight, Allen; Grigorakis, Alkiviadis; Bdesha, Amar; Nagle, Amy; Cebola, Ana; Dhanasekaran, Ananda Kumar; Kondža, Andraž; Barcelos, André; Galosi, Andrea Benedetto; Ebur, Andrea; Minervini, Andrea; Russell, Andrew; Webb, Andrew; de Jalón, Ángel García; Desai, Ankit; Czech, Anna Katarzyna; Mainwaring, Anna; Adimonye, Anthony; Das, Arighno; Figueiredo, Arnaldo; Villers, Arnauld; Leminski, Artur; Chippagiri, Arvinda; Lal, Asim Ahmed; Yıldırım, Asıf; Voulgaris, Athanasios Marios; Uzan, Audrey; Oo, Aye Moh Moh; Younis, Ayman; Zelhof, Bachar; Mukhtar, Bashir; Ayres, Ben; Challacombe, Ben; Sherwood, Benedict; Ristau, Benjamin; Lai, Billy; Nellensteijn, Brechtje; Schreiter, Brielle; Trombetta, Carlo; Dowling, Catherine; Hobbs, Catherine; Benitez, Cayo Augusto Estigarribia; Lebacle, Cédric; Ho, Cherrie Wing Yin; Ng, Chi-Fai; Mount, Chloe; Lam, Chon Meng; Blick, Chris; Brown, Christian; Gallegos, Christopher; Higgs, Claire; Browne, Clíodhna; Mccann, Conor; Plaza Alonso, Cristina; Beder, Daniel; Cohen, Daniel; Gordon, Daniel; Wilby, Daniel; Gordon, Danny; Hrouda, David; Lau, David Hua Wu; Karsza, Dávid; Mak, David; Martin-Way, David; Suthaharan, Denula; Patel, Dhruv; Carrion, Diego M; Nyanhongo, Donald; Bass, Edward; Mains, Edward; Chau, Edwin; Canelon Castillo, Elba; Day, Elizabeth; Desouky, Elsayed; Gaines, Emily; Papworth, Emma; Yuruk, Emrah; Kilic, Enes; Dinneen, Eoin; Palagonia, Erika; Xylinas, Evanguelos; Khawaja, Faizan; Cimarra, Fernando; Bardet, Florian; Kum, Francesca; Peters, Francesca; Kovács, Gábor; Tanasescu, Geroge; Hellawell, Giles; Tasso, Giovanni; Lam, Gitte; La Montagna, Giuseppe; Pizzuto, Giuseppe; Lenart, Gordan; Maclennan, Graeme; Özgür, Günal; Bi, Hai; Lyons, Hannah; Warren, Hannah; Ahmed, Hashim; Simpson, Helen; Burden, Helena; Gresty, Helena; Rios Pita, Hernado; Clarke, Holly; Serag, Hosam; Kynaston, Howard; Crawford-Smith, Hugh; Mostafid, Hugh; Otaola-Arca, Hugo; Koo, Hui Fen; Ibrahim, Ibrahim; Ouzaid, Idir; Puche-Sanz, Ignacio; Tomašković, Igor; Tinay, Ilker; Sahibzada, Iqbal; Thangasamy, Isaac; Cadena, Iván Revelo; Irani, Jacques; Udzik, Jakub; Brittain, James; Catto, James; Green, James; Tweedle, James; Hernando, Jamie Borrego; Leask, Jamie; Kalsi, Jas; Frankel, Jason; Toniolo, Jason; Raman, Jay D.; Courcier, Jean; Kumaradeevan, Jeevan; Clark, Jennifer; Jones, Jennifer; Teoh, Jeremy Yuen-Chun; Iacovou, John; Kelly, John; Selph, John P.; Aning, Jonathan; Deeks, Jon; Cobley, Jonathan; Olivier, Jonathan; Maw, Jonny; Herranz-Yagüe, José Antonio; Nolazco, Jose Ignacio; Cózar-Olmo, Jose Manuel; Bagley, Joseph; Jelski, Joseph; Norris, Joseph; Testa, Joseph; Meeks, Joshua; Hernandez, Juan; Vásquez, Juan Luis; Randhawa, Karen; Dhera, Karishma; Gronostaj, Katarzyna; Houlton, Kathleen; Lehman, Kathleen; Gillams, Kathryn; Adasonla, Kelvin; Brown, Kevin; Murtagh, Kevin; Mistry, Kiki; Davenport, Kim; Kitamura, Kosuke; Derbyshire, Laura; Clarke, Laurence; Morton, Lawrie; Martinez, Levin; Goldsmith, Louise; Paramore, Louise; Cormier, Luc; Dell'Atti, Lucio; Simmons, Lucy; Martinez-Piñeiro, Luis; Rico, Luis; Chan, Luke; Forster, Luke; Ma, Lulin; Moore, Madeline; Gallego, Maria Camacho; Freire, Maria José; Emberton, Mark; Feneley, Mark; Antón-Juanilla, Marta; Rivero, Marta Viridiana Muñoz; Pirša, Matea; Tallè, Matteo; Crockett, Matthew; Liew, Matthew; Trail, Matthew; Peters, Max; Cooper, Meghan; Kulkarni, Meghana; Ager, Michael; He, Ming; Li, Mo; Omran Breish, Mohamed; Tarin, Mohamed; Aldiwani, Mohammed; Matanhelia, Mudit; Pasha, Muhammad; Akalın, Mustafa Kaan; Abdullah, Nasreen; Hale, Nathan; Gadiyar, Neha; Kocher, Neil; Bullock, Nicholas; Campain, Nicholas; Pavan, Nicola; Al-Ibraheem, Nihad; Bhatt, Nikita; Bedi, Nishant; Shrotri, Nitin; Lobo, Niyati; Balderas, Olga; Kouli, Omar; Capoun, Otakar; Oteo Manjavacas, Pablo; Gontero, Paolo; Mariappan, Paramananthan; Marchiñena, Patricio Garcia; Erotocritou, Paul; Sweeney, Paul; Planelles, Paula; Acher, Peter; Black, Peter C.; Osei-Bonsu, Peter K; Østergren, Peter; Smith, Peter; Willemse, Peter-Paul Michiel; Chlosta, Piotr L.; Ul Ain, Qurrat; Barratt, Rachel; Esler, Rachel; Khalid, Raihan; Hsu, Ray; Stamirowski, Remigiusz; Mangat, Reshma; Cruz, Ricardo; Ellis, Ricky; Adams, Robert; Hessell, Robert; Oomen, Robert J. A.; Mcconkey, Robert; Ritchie, Robert; Jarimba, Roberto; Chahal, Rohit; Andres, Rosado Mario; Hawkins, Rosalyn; David, Rotimi; Manecksha, Rustom P.; Agrawal, Sachin; Hamid, Syed Sami; Deem, Samuel; Goonewardene, Sanchia; Swami, Satchi Kuchibhotla; Hori, Satoshi; Khan, Shahid; Mohammud Inder, Shakeel; Sangaralingam, Shanthi; Marathe, Shekhar; Raveenthiran, Sheliyan; Horie, Shigeo; Sengupta, Shomik; Parson, Sian; Parker, Sidney; Hawlina, Simon; Williams, Simon; Mazzoli, Simone; Grzegorz Kata, Slawomir; Pinheiro Lopes, Sofia; Ramos, Sónia; Rai, Sonpreet; Rintoul-Hoad, Sophie; O'Meara, Sorcha; Morris, Steve; Turner, Stacey; Venturini, Stefano; Almpanis, Stephanos; Joniau, Steven; Jain, Sunjay; Mallett, Susan; Nikles, Sven; Shahzad, Null; Yan, Sylvia; Lee, Taeweon; Uçar, Taha; Drake, Tamsin; Toma, Tarq; Cabañuz Plo, Teresa; Bonnin, Thierry; Muilwijk, Tim; Wollin, Tim; Chu, Timothy Shun Man; Appanna, Timson; Brophy, Tom; Ellul, Tom; Austin, Tomas; Smrkolj, Tomaž; Rowe, Tracey; Sukhu, Troy; Patel, Trushar; Garg, Tullika; Çaşkurlu, Turhan; Bele, Uros; Haroon, Usman; Crespo-Atín, Víctor; Parejo Cortes, Victor; Capapé Poves, Victoria; Gnanapragasam, Vincent; Gauhar, Vineet; During, Vinnie; Kumar, Vivek; Fiala, Vojtech; Mahmalji, Wasim; Lam, Wayne; Fung Chin, Yew; Filtekin, Yigit; Chyn Phan, Yih; Ibrahim, Youssed; Glaser, Zachary A; Abiddin, Zainal Adwin; Qin, Zijian; Zotter, Zsuzsanna; Zainuddin, Zulkifl

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60&nbsp;years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death.&nbsp;The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

Background: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). Methods: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. Results: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]). Conclusions: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

Background: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). Methods: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. Results: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83–7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97–2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14–1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25–1.30]). Conclusions: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable