Utility of shaking chills as a diagnostic sign for bacteremia in adults: a systematic review and meta-analysis.
Bacteremia
Chills
Rigor
Sepsis
Shivering
Journal
BMC medicine
ISSN: 1741-7015
Titre abrégé: BMC Med
Pays: England
ID NLM: 101190723
Informations de publication
Date de publication:
11 Jun 2024
11 Jun 2024
Historique:
received:
01
10
2023
accepted:
05
06
2024
medline:
12
6
2024
pubmed:
12
6
2024
entrez:
11
6
2024
Statut:
epublish
Résumé
Accurate prediction of bacteremia is essential for guiding blood culture collection and optimal antibiotic treatment. Shaking chills, defined as a subjective chill sensation with objective body shivering, have been suggested as a potential predictor of bacteremia; however, conflicting findings exist. To address the evidence gap, we conducted a systematic review and meta-analysis of studies to assess the diagnostic accuracy of shaking chills for predicting bacteremia among adult patients. We included studies reporting the diagnostic accuracy of shaking chills or chills for bacteremia. Adult patients with suspected bacteremia who underwent at least one set of blood cultures were included. Our main analysis focused on studies that assessed shaking chills. We searched these studies through CENTRAL, MEDLINE, Embase, the World Health Organization ICTRP Search Portal, and ClinicalTrials.gov. Study selection, data extraction, evaluation for risk of bias, and applicability using the QUADAS-2 tool were conducted by two independent investigators. We estimated a summary receiver operating characteristic curve and a summary point of sensitivity and specificity of the index tests, using a hierarchical model and the bivariate model, respectively. We identified 19 studies with a total of 14,641 patients in which the accuracy of shaking chills was evaluated. The pooled sensitivity and specificity of shaking chills were 0.37 (95% confidence interval [CI], 0.29 to 0.45) and 0.87 (95% CI, 0.83 to 0.90), respectively. Most studies had a low risk of bias in the index test domain and a high risk of bias and a high applicability concern in the patient-selection domain. Shaking chills are a highly specific but less sensitive predictor of bacteremia. Blood cultures and early initiation of antibiotics should be considered for patients with an episode of shaking chills; however, the absence of shaking chills must not lead to exclusion of bacteremia and early antibiotic treatment.
Sections du résumé
BACKGROUND
BACKGROUND
Accurate prediction of bacteremia is essential for guiding blood culture collection and optimal antibiotic treatment. Shaking chills, defined as a subjective chill sensation with objective body shivering, have been suggested as a potential predictor of bacteremia; however, conflicting findings exist. To address the evidence gap, we conducted a systematic review and meta-analysis of studies to assess the diagnostic accuracy of shaking chills for predicting bacteremia among adult patients.
METHODS
METHODS
We included studies reporting the diagnostic accuracy of shaking chills or chills for bacteremia. Adult patients with suspected bacteremia who underwent at least one set of blood cultures were included. Our main analysis focused on studies that assessed shaking chills. We searched these studies through CENTRAL, MEDLINE, Embase, the World Health Organization ICTRP Search Portal, and ClinicalTrials.gov. Study selection, data extraction, evaluation for risk of bias, and applicability using the QUADAS-2 tool were conducted by two independent investigators. We estimated a summary receiver operating characteristic curve and a summary point of sensitivity and specificity of the index tests, using a hierarchical model and the bivariate model, respectively.
RESULTS
RESULTS
We identified 19 studies with a total of 14,641 patients in which the accuracy of shaking chills was evaluated. The pooled sensitivity and specificity of shaking chills were 0.37 (95% confidence interval [CI], 0.29 to 0.45) and 0.87 (95% CI, 0.83 to 0.90), respectively. Most studies had a low risk of bias in the index test domain and a high risk of bias and a high applicability concern in the patient-selection domain.
CONCLUSIONS
CONCLUSIONS
Shaking chills are a highly specific but less sensitive predictor of bacteremia. Blood cultures and early initiation of antibiotics should be considered for patients with an episode of shaking chills; however, the absence of shaking chills must not lead to exclusion of bacteremia and early antibiotic treatment.
Identifiants
pubmed: 38863066
doi: 10.1186/s12916-024-03467-z
pii: 10.1186/s12916-024-03467-z
doi:
Types de publication
Systematic Review
Journal Article
Meta-Analysis
Langues
eng
Sous-ensembles de citation
IM
Pagination
240Informations de copyright
© 2024. The Author(s).
Références
Weinstein MP, Towns ML, Quartey SM, Mirrett S, Reimer LG, Parmigiani G, et al. The clinical significance of positive blood cultures in the 1990s: a prospective comprehensive evaluation of the microbiology, epidemiology, and outcome of bacteremia and fungemia in adults. Clin Infect Dis. 1997;24:584–602.
pubmed: 9145732
doi: 10.1093/clind/24.4.584
Lindvig KP, Nielsen SL, Henriksen DP, Jensen TG, Kolmos HJ, Pedersen C, et al. Mortality and prognostic factors of patients who have blood cultures performed in the emergency department: a cohort study. Eur J Emerg Med. 2016;23:166–72.
pubmed: 25710084
doi: 10.1097/MEJ.0000000000000250
Opota O, Croxatto A, Prod’hom G, Greub G. Blood culture-based diagnosis of bacteraemia: state of the art. Clin Microbiol Infect. 2015;21:313–22.
pubmed: 25753137
doi: 10.1016/j.cmi.2015.01.003
Fujii K, Takada T, Kamitani T, Aoki T, Takeshima T, Kudo M, et al. Diagnostic performance of physician gestalt for bacteremia in patients in the process of being admitted with suspected infection. Clin Infect Dis. 2023;76:1074–9.
pubmed: 36306421
doi: 10.1093/cid/ciac854
Takeshima T, Yamamoto Y, Noguchi Y, Maki N, Gibo K, Tsugihashi Y, et al. Identifying patients with bacteremia in community-hospital emergency rooms: a retrospective cohort study. PLoS One. 2016;11:e0148078.
pubmed: 27023336
pmcid: 4811592
doi: 10.1371/journal.pone.0148078
Shapiro NI, Wolfe RE, Wright SB, Moore R, Bates DW. Who needs a blood culture? A prospectively derived and validated prediction rule. J Emerg Med. 2008;35:255–64.
pubmed: 18486413
doi: 10.1016/j.jemermed.2008.04.001
Lee C-C, Wu C-J, Chi C-H, Lee N-Y, Chen P-L, Lee H-C, et al. Prediction of community-onset bacteremia among febrile adults visiting an emergency department: rigor matters. Diagn Microbiol Infect Dis. 2012;73:168–73.
pubmed: 22463870
doi: 10.1016/j.diagmicrobio.2012.02.009
Tokuda Y, Miyasato H, Stein GH, Kishaba T. The degree of chills for risk of bacteremia in acute febrile illness. Am J Med. 2005;118:1417.e1-1417.e6.
doi: 10.1016/j.amjmed.2005.06.043
Taniguchi T, Tsuha S, Takayama Y, Shiiki S. Shaking chills and high body temperature predict bacteremia especially among elderly patients. Springerplus. 2013;2:624.
pubmed: 24298435
pmcid: 3841330
doi: 10.1186/2193-1801-2-624
Vandenberk M, De Bondt K, Nuyts E, Toelen J, Verbakel JY. Shivering has little diagnostic value in diagnosing serious bacterial infection in children: a systematic review and meta-analysis. Eur J Pediatr. 2021;180:1033–42.
pubmed: 33179117
doi: 10.1007/s00431-020-03870-7
McInnes MDF, Moher D, Thombs BD, McGrath TA, Bossuyt PM, the PRISMA-DTA Group, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA. 2018;319:388–96.
pubmed: 29362800
doi: 10.1001/jama.2017.19163
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
pubmed: 33782057
pmcid: 8005924
doi: 10.1136/bmj.n71
Nunnally ME, Jaeschke R, Bellingan GJ, Lacroix J, Mourvillier B, Rodriguez-Vega GM, et al. Targeted temperature management in critical care: a report and recommendations from five professional societies. Crit Care Med. 2011;39:1113–25.
pubmed: 21187745
doi: 10.1097/CCM.0b013e318206bab2
Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5:210.
pubmed: 27919275
pmcid: 5139140
doi: 10.1186/s13643-016-0384-4
Whiting PF, Rutjes AWS, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.
pubmed: 22007046
doi: 10.7326/0003-4819-155-8-201110180-00009
Deeks JJ, Bossuyt PM, Leeflang MM, Takwoingi Y, editors. Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy. Version 2.0 (updated July 2023). Cochrane. 2023. Available from https://training.cochrane.org/handbook-diagnostic-test-accuracy/current .
Reitsma JB, Moons KGM, Bossuyt PMM, Linnet K. Systematic reviews of studies quantifying the accuracy of diagnostic tests and markers. Clin Chem. 2012;58:1534–45.
pubmed: 22991421
doi: 10.1373/clinchem.2012.182568
Bahagon Y, Raveh D, Schlesinger Y, Rudensky B, Yinnon AM. Prevalence and predictive features of bacteremic urinary tract infection in emergency department patients. Eur J Clin Microbiol Infect Dis. 2007;26:349–52.
pubmed: 17431694
doi: 10.1007/s10096-007-0287-3
Bates DW, Sands K, Miller E, Lanken PN, Hibberd PL, Graman PS, et al. Predicting bacteremia in patients with sepsis syndrome. Academic Medical Center Consortium Sepsis Project Working Group. J Infect Dis. 1997;176:1538–51.
pubmed: 9395366
doi: 10.1086/514153
Bates DW, Cook EF, Goldman L, Lee TH. Predicting bacteremia in hospitalized patients. A prospectively validated model. Ann Intern Med. 1990;113:495–500.
pubmed: 2393205
doi: 10.7326/0003-4819-113-7-495
Chassagne P, Perol MB, Doucet J, Trivalle C, Ménard JF, Manchon ND, et al. Is presentation of bacteremia in the elderly the same as in younger patients? Am J Med. 1996;100:65–70.
pubmed: 8579089
doi: 10.1016/S0002-9343(96)90013-3
Holmqvist M, Inghammar M, Påhlman L, Boyd J, Åkesson P, Linder A, et al. Risk of bacteremia in patients presenting with shaking chills and vomiting - a prospective cohort study. Epidemiol Infect. 2020. https://doi.org/10.1017/S0950268820000746 .
doi: 10.1017/S0950268820000746
pubmed: 32228723
pmcid: 7189349
Hoogendoorn M, van ’t Wout JW, Schijf V, van Dissel JT. Predictive value of chills in patients presenting with fever to urgent care department. Ned Tijdschr Geneeskd. 2002;146:116–20.
pubmed: 11826671
Komatsu T, Takahashi E, Mishima K, Toyoda T, Saitoh F, Yasuda A, et al. A simple algorithm for predicting bacteremia using food consumption and shaking chills: a prospective observational study. J Hosp Med. 2017;12:510–5.
pubmed: 28699938
doi: 10.12788/jhm.2764
McNab L, Lee R, Chiew AL. Evaluating clinical prediction rules for bacteremia detection in the emergency department: a retrospective review. J Emerg Med. 2023. https://doi.org/10.1016/j.jemermed.2023.12.005 .
Pfitzenmeyer P, Decrey H, Auckenthaler R, Michel JP. Predicting bacteremia in older patients. J Am Geriatr Soc. 1995;43:230–5.
pubmed: 7884108
doi: 10.1111/j.1532-5415.1995.tb07327.x
Sasaki S, Raita Y, Murakami M, Yamamoto S, Tochitani K, Hasegawa T, et al. Added value of clinical prediction rules for bacteremia in hemodialysis patients: an external validation study. PLoS One. 2021;16:e0247624.
pubmed: 33617601
pmcid: 7899347
doi: 10.1371/journal.pone.0247624
Sasaki S, Hasegawa T, Kawarazaki H, Nomura A, Uchida D, Imaizumi T, et al. Development and validation of a clinical prediction rule for bacteremia among maintenance hemodialysis patients in outpatient settings. PLoS One. 2017;12:e0169975.
pubmed: 28081211
pmcid: 5231279
doi: 10.1371/journal.pone.0169975
Takada T, Fujii K, Kudo M, Sasaki S, Yano T, Yagi Y, et al. Diagnostic performance of food consumption for bacteraemia in patients admitted with suspected infection: a prospective cohort study. BMJ Open. 2021;11:e044270.
pubmed: 34045215
pmcid: 8162084
doi: 10.1136/bmjopen-2020-044270
Takamatsu A, Mito H. Predicting bacteremia in the emergency department. J Gen Intern Med. 2016;31:S351–2.
Taniguchi T, Tsuha S, Shiiki S, Narita M, Teruya M, Hachiman T, et al. High yield of blood cultures in the etiologic diagnosis of cellulitis, erysipelas, and cutaneous abscess in elderly patients. Open Forum Infect Dis. 2022;9:317.
pubmed: 35899281
pmcid: 9310324
doi: 10.1093/ofid/ofac317
Yoshino N, Kimura S-I, Matsuoka A, Meno T, Ishikawa T, Nakamura Y, et al. Clinical features of febrile neutropenia and bloodstream infection in autologous hematopoietic cell transplantation: comparison to those in intensive chemotherapy for acute myeloid leukemia. J Infect Chemother. 2023;29:384–90.
pubmed: 36669687
doi: 10.1016/j.jiac.2023.01.004
Choi DH, Lim MH, Kim KH, Shin SD, Hong KJ, Kim S. Development of an artificial intelligence bacteremia prediction model and evaluation of its impact on physician predictions focusing on uncertainty. Sci Rep. 2023;13:13518.
pubmed: 37598221
pmcid: 10439897
doi: 10.1038/s41598-023-40708-2
Falguera M, Trujillano J, Caro S, Menéndez R, Carratalà J, Ruiz-González A, et al. A prediction rule for estimating the risk of bacteremia in patients with community-acquired pneumonia. Clin Infect Dis. 2009;49:409–16.
pubmed: 19555286
doi: 10.1086/600291
Fontanarosa PB, Kaeberlein FJ, Gerson LW, Thomson RB. Difficulty in predicting bacteremia in elderly emergency patients. Ann Emerg Med. 1992;21:842–8.
pubmed: 1610043
doi: 10.1016/S0196-0644(05)81032-7
Fukui S, Inui A, Saita M, Kobayashi D, Naito T. Clinical prediction rule for bacteremia with pyelonephritis and hospitalization judgment: chi-square automatic interaction detector (CHAID) decision tree analysis model. J Int Med Res. 2022;50:3000605211065658.
pubmed: 34986702
doi: 10.1177/03000605211065658
Hodgson LE, Dragolea N, Venn R, Dimitrov BD, Forni LG. An external validation study of a clinical prediction rule for medical patients with suspected bacteraemia. Emerg Med J. 2016;33:124–9.
pubmed: 26246024
doi: 10.1136/emermed-2015-204926
Jaimes F, Arango C, Ruiz G, Cuervo J, Botero J, Vélez G, et al. Predicting bacteremia at the bedside. Clin Infect Dis. 2004;38:357–62.
pubmed: 14727205
doi: 10.1086/380967
Jessen MK, Mackenhauer J, Hvass AMSW, Ellermann-Eriksen S, Skibsted S, Kirkegaard H, et al. Prediction of bacteremia in the emergency department: an external validation of a clinical decision rule. Eur J Emerg Med. 2016;23:44–9.
pubmed: 25222426
doi: 10.1097/MEJ.0000000000000203
Kim KS, Kim K, Jo YH, Kim TY, Lee JH, Lee SJ, et al. A simple model to predict bacteremia in women with acute pyelonephritis. J Infect. 2011;63:124–30.
pubmed: 21722666
doi: 10.1016/j.jinf.2011.06.007
Kuruoglu T, Sensoy L, Atilla A, Temocin F, Gur D, Tanyel E. Evaluation of risk factors for the development of bacteremia and complications in patients with brucellosis: is it possible to predict the clinical course? J Infect Dev Ctries. 2023;17:1277–84.
pubmed: 37824349
doi: 10.3855/jidc.18164
Leibovici L, Greenshtain S, Cohen O, Mor F, Wysenbeek AJ. Bacteremia in febrile patients: a clinical model for diagnosis. Arch Intern Med. 1991;151:1801–6.
pubmed: 1888246
doi: 10.1001/archinte.1991.00400090089016
Nimitvilai S, Jintanapramote K, Jarupongprapa S. Predicting bacteremic urinary tract infection in community setting: a prospective observational study. Crit Care. 2016;20(Suppl 2):P065.
Phungoen P, Lerdprawat N, Sawanyawisuth K, Chotmongkol V, Ienghong K, Sumritrin S, et al. Clinical factors associated with bloodstream infection at the emergency department. BMC Emerg Med. 2021;21:30.
pubmed: 33711935
pmcid: 7953601
doi: 10.1186/s12873-021-00426-2
Ratzinger F, Eichbichler K, Schuardt M, Tsirkinidou I, Mitteregger D, Haslacher H, et al. sis in standard care: patients’ characteristics, effectiveness of antimicrobial therapy and patient outcome—a cohort study. Infection. 2015;43:345–52.
pubmed: 25840554
doi: 10.1007/s15010-015-0771-0
Singh N, Paterson DL, Gayowski T, Wagener MM, Marino IR. Predicting bacteremia and bacteremic mortality in liver transplant recipients. Liver Transpl. 2000;6:54–61.
pubmed: 10648578
Su C-P, Chen TH-H, Chen S-Y, Ghiang W-C, Wu GH-M, Sun H-Y, et al. Predictive model for bacteremia in adult patients with blood cultures performed at the emergency department: a preliminary report. J Microbiol Immunol Infect. 2011;44:449–55.
pubmed: 21684227
doi: 10.1016/j.jmii.2011.04.006
Tromp M, Lansdorp B, Bleeker-Rovers CP, Gunnewiek JMK, Kullberg BJ, Pickkers P. Serial and panel analyses of biomarkers do not improve the prediction of bacteremia compared to one procalcitonin measurement. J Infect. 2012;65:292–301.
pubmed: 22710263
doi: 10.1016/j.jinf.2012.06.004
van Werkhoven CH, Huijts SM, Postma DF, Oosterheert JJ, Bonten MJM. Predictors of bacteraemia in patients with suspected community-acquired pneumonia. PLoS One. 2015;10:e0143817.
pubmed: 26599636
pmcid: 4658054
doi: 10.1371/journal.pone.0143817
Xu T, Wu S, Li J, Wang L, Huang H. Development of a risk prediction model for bloodstream infection in patients with fever of unknown origin. J Transl Med. 2022;20:575.
pubmed: 36482449
pmcid: 9733314
doi: 10.1186/s12967-022-03796-8
Zhou T, Ren Z, Ma Y, He L, Liu J, Tang J, et al. Early identification of bloodstream infection in hemodialysis patients by machine learning. Heliyon. 2023;9:e18263.
pubmed: 37519767
pmcid: 10375788
doi: 10.1016/j.heliyon.2023.e18263
Rhee C, Chiotos K, Cosgrove SE, Heil EL, Kadri SS, Kalil AC, et al. Infectious diseases society of America position paper: recommended revisions to the national severe sepsis and septic shock early management bundle (SEP-1) sepsis quality measure. Clin Infect Dis. 2021;72:541–52.
pubmed: 32374861
doi: 10.1093/cid/ciaa059
Liu VX, Fielding-Singh V, Greene JD, Baker JM, Iwashyna TJ, Bhattacharya J, et al. The timing of early antibiotics and hospital mortality in sepsis. Am J Respir Crit Care Med. 2017;196:856–63.
pubmed: 28345952
pmcid: 5649973
doi: 10.1164/rccm.201609-1848OC
Seymour CW, Gesten F, Prescott HC, Friedrich ME, Iwashyna TJ, Phillips GS, et al. Time to treatment and mortality during mandated emergency care for sepsis. N Engl J Med. 2017;376:2235–44.
pubmed: 28528569
pmcid: 5538258
doi: 10.1056/NEJMoa1703058
Whiles BB, Deis AS, Simpson SQ. Increased time to initial antimicrobial administration is associated with progression to septic shock in severe sepsis patients. Crit Care Med. 2017;45:623–9.
pubmed: 28169944
pmcid: 5374449
doi: 10.1097/CCM.0000000000002262
Van Heuverswyn J, Valik JK, van der Werff SD, Hedberg P, Giske C, Nauclér P. Association between time to appropriate antimicrobial treatment and 30-day mortality in patients with bloodstream infections: a retrospective cohort study. Clin Infect Dis. 2022;76:469–78.
pmcid: 9907509
doi: 10.1093/cid/ciac727